Skip to content
Publicly Available Published by De Gruyter December 1, 2022

Online Activities and Extremist Attitudes in Adolescence: An Empirical Analysis with a Gender Differentiation

Online-Aktivitäten und extremistische Einstellungen im Jugendalter: Eine empirische Analyse mit einer Geschlechterdifferenzierung
Laura-Romina Goede EMAIL logo , Carl Philipp Schröder , Lena Lehmann and Thomas Bliesener

Abstract

Radicalization research is dedicated to analyzing factors related to radicalization processes, which in turn can lead to extremism. One factor is frequently discussed: the role of the Internet. This paper examines the relationship between active and passive online activities, including consumption, networking, and posting, and extremist attitudes in the field of Islamism and right-wing extremism among adolescents. Data from a school survey (N = 6,715) show that right-wing attitudes are particularly correlated with consumption of political websites, though this effect is weaker among females. However, posting shows only a small effect and networking shows no effect at all. Islamist attitudes, on the other hand, are related to the extent to which one consumes violent Islamist videos, meets other Muslims online, and posts Islamic content.

Zusammenfassung

Die Radikalisierungsforschung untersucht Faktoren und Bedingungen von Prozessen, die hin zu Extremismus führen können. Ein häufig genannter Faktor ist das Internet. Diese Arbeit untersucht den Zusammenhang zwischen verschiedenen passiven und aktiven Internetaktivitäten, wie das Konsumieren, Vernetzen und Posten mit extremistischen Einstellungen im Bereich Islamismus und Rechtsextremismus bei Jugendlichen. Daten einer Schüler*innenbefragung (N = 6,715) zeigen, dass rechtsextreme Einstellungen insbesondere bei Jungen mit dem Konsum politischer Websites einhergehen, während Posting nur geringe und das Netzwerken keine Zusammenhänge mit rechtsextremen Einstellungen zeigen. Bei islamistischen Einstellungen zeigen sich dagegen Zusammenhänge mit dem Konsum von islamistischen Gewaltvideos, dem Vernetzen mit anderen Muslim*innen und dem Posten islamischer Inhalte.

1 Introduction

These days, young people spend a lot of time online. Some common activities are watching videos, listening to music, and reading articles. People can also communicate with friends and strangers via social media. Exchanging ideas, getting to know one another, discussing topics, or arranging to meet can all be done through social media. Young people can use these tools to discuss topics such as sports, fashion, and leisure opportunities, but also to talk about religion or politics. Overall, the Internet facilitates the use of uncontrolled, quick, and cheap information transfer. On the one hand, this technological development can lead to positive new opportunities. On the other hand, social media, for example, can pose a risk for young people to get caught up in radicalization processes. Dienstbühl and Weber (2014) attribute online radicalization and extremism to emotional aspects rather than discussion of politics and society. This may be because involvement in virtual groups provides a sense of belonging based on shared emotions and ideals. Furthermore, the Internet provides a space in which people can consume all types of propaganda (Rieger et al., 2017). However, the question remains, which online activities lead into or go along with radicalization. Since the question of causal reasons for radicalization is methodologically difficult to fathom, we shift our focus to the analysis of risk factors for extremist attitudes. This field has been researched intensively in recent years (Wolfowicz et al., 2020). Although the number of studies focusing on online activity has increased (Wolfowicz et al., 2022), the question of which specific online activities are related to extremist attitudes and how these activities relate to one another is still ignored, at least in quantitative research.

Radicalization research also indicates that gender differences exist within different ideologies, particularly in relation to recruitment processes and general gender roles (Orav et al., 2018). Empirical studies on right-wing attitudes in particular show higher values among male adults (Decker et al., 2022; Küpper et al., 2021) and male ninth graders (Krieg et al., 2022). An earlier paper based on the data of the current article showed that certain risk factors for Islamist attitudes (segregation, violence-legitimizing norms of masculinity, Islamic-traditional understanding of gender roles and family-related or school-related strains) barely differ between Muslim girls and boys (Goede & Lopez Trillo, 2020). Even though Almenayes (2014) indicated that Islamist females use social media more often than Islamist males. In addition, studies show gender differences in general Internet use (JIM Study, 2021). Based on these results, we assume different effects for male and female participants and will therefore analyze the connection between online activities and extremist attitudes with a gender differentiation. This approach will enable both comparison of the impact of online activities and identification of gender differences within these effects. The research question for this paper addresses: What is the relationship between various online activities and extremist attitudes among adolescent girls and boys? Such research is required for the development of prevention efforts, which can be addressed in the aftermath of this contribution.

The link between online activities and extremist attitudes will be analyzed in the theoretical framework of the Social Learning Theory by Akers (1977). On this basis, the internet can be understood as a room for socialization processes in which radicalization can occur. We further outline definitions of the relevant terms radicalization and extremism, followed by a short summary of the state of research in the fields of general radicalization in adolescence and online radicalization. After the explanation of the methodology and the sample description, relevant descriptive and multivariate results are presented.

1.1 Radicalization and Extremism

Given that most radicalization researchers agree on defining radicalization as the process of becoming an extremist (Neumann, 2013), a clear definition of extremism is needed. Of the numerous definitions that exist in the scientific discourse, we will refer to the one from Beelmann (2020). According to Beelmann, »political, religious, and otherwise conceived extremism [is defined] as a significant deviation in attitudes and behavior from basic legal and political norms and values within a social system (society or state) that seek their (at least partial) abolition and replacement (Beelmann et al., 2017). The process by which such patterns of attitudes and action emerge individually and ontogenetically over the course of development can then be labeled radicalization« (Beelmann, 2020, 2).

1.2 Social Learning Theory

As a theoretical framework for the explanation of radicalization processes, we refer to the Social Learning Theory of Akers, which has previously been applied in this field successfully (Wolfowicz et al., 2020; Pauwels & Schils 2016). Based on the assumptions of differential association theory (Sutherland, 1939), differential reinforcement theory (Burgess & Akers, 1966) and social cognitive learning theory (Bandura, 1977), Akers (1977) formulated the criminological theory of social learning. Akers assumes that deviant attitudes and behaviors are learned through interaction. The concept of differential association explains the process of learning deviant attitudes and values through direct social interaction with others (Akers, 1998). Differential reinforcement involves the perception of the consequences of specific actions, which can be rewarding or punishing. When actions are rewarded by others, this reinforces the likelihood of the action happening again (Akers, 1998). The adoption of deviant behaviors previously observed in others is referred to as imitation. Here, the extent of adoption depends on the observed consequences. If the consequences are observed to be rewarding, this promotes the adoption of the behaviors. Imitation is particularly important for the initial acquisition and execution of new behaviors. Through differential association and imitation, definitions are learned and reinforced, i.e., individuals acquire attitudes toward certain values and classifications of behaviors as right or wrong (Akers, 1998). It is further postulated that social contact, especially with peers, has an influence on deviant behavior. The theory was initially intended to explain only deviant behavior, but a large number of studies have applied it to the field of extremism as well (Akins & Winfree, 2016; Becker, 2019; Goede & Lopez Trillo, 2020; Lafree et al., 2018; Pauwels & Schils, 2016; Wolfowicz et al., 2021). While the influence of family on extremist attitudes and behaviors has been studied less frequently than that of radical peers, it has nevertheless been confirmed (Lafree et al., 2018; Becker, 2019). The Internet and especially social media can, in the sense of the theory, be seen as a place for socialization and social learning, since differential association as well as differential reinforcement can be experienced via social media.

1.3 Radicalization in Adolescence

During adolescence, individuals begin to search for their own identities, thus making them susceptible to new attitudes and more likely to join new peers. Adolescents are considered a particularly vulnerable group to engage in radicalization processes because they begin to seek belonging, recognition, and identity (Greve, 2007). They also seek adventure, thrills, and provocation (Benslama, 2017). In addition, the relationship between parents and children changes as adolescents. Some risk factors for radicalization, such as identity problems and other psycho-social aspects, play a particularly important role during adolescence (Benslama, 2017; Emmelkamp et al., 2020). They can be caused by the biological and psychological development of adolescents and are thus common in this age group. Adolescence is also an important period for political socialization (Beelmann, 2020; Niemi & Hepburn, 2010; Torney-Purta, 2004; Watts, 1999) and the development of attitudes that generally remain stable over one's lifetime (Sears, 1983, 1990). Young people initially experiment with different political positions, which encourages both the adoption of extreme political positions and short-term changes in basic positions (Alwin & Krosnick, 1991; Rekker et al., 2015). Extreme political positions and values are also considered an early feature of individual radicalization (Bliesener et al., 2021). In general, extremist attitudes are widespread among adolescents, as numerous studies from different countries have shown (Baier et al., 2019; Cherney et al., 2020; Krieg et al., 2022; Krieg et al., 2018; Muxel, 2020; Pfundmair et al., 2020; Pauwels & Waele, 2014).

1.4 Online Radicalization

One risk factor for radicalization that is often mentioned is the Internet. There is a consensus that the Internet in general cannot be a causal factor, but several types of Internet use can be considered relevant risk factors among others (Hohnstein & Glaser, 2017; Ducol et al., 2016; Behr et al., 2013). In other words, the Internet is not the only reason for radicalization. Instead, functions of the Internet can be described as catalysts that facilitate and speed up the process of radicalization (Pauwels et al., 2014).

Following the emergence of online communication, radicalization processes shifted from face-to-face interaction to online platforms (Koehler, 2014). Furthermore, the Internet is used to find answers to political, theological, or social questions (Holbrook, 2015). Hussain and Saltman (2014) point out the role of search engines in finding extremist content and the lack of counter-speech sites supporting moderate views. For individuals without prior knowledge of extremism, it is difficult to evaluate whether content is extremist or not (Hussain & Saltman, 2014).

People who have already been radicalized use the Internet to seek practical and ideological support (Leimbach, 2017). Besides websites and forums, such support is particularly found in social media (Guhl et al., 2020). Online magazines, such as the »Inspire« magazine of Al-Qaida, can also influence radicalization processes. Reasons for Internet use by extremist organizations include propaganda, recruitment, and funding, as well as logistics and planning (Winter et al., 2020). For such groups, the Internet has various functions, including networking, swapping of ideological ideas, disseminating extremist music, building an ideological worldview that is isolated from the »outside«, destroying the credibility of the mass media, and establishing an enemy image of the state and the media (Neumann, 2015).

However, most researchers do not provide specific definitions of ‘using the Internet’ or ‘being online’. The Internet offers a variety of functions and activities. The Internet also has cognitive (gaining knowledge) and social (communication with like-minded peers) incentives (Ducol et al., 2016). To prevent radicalization processes, it is important to know which online activities influence which kind of people and to what extent. The specific link between online activities and radicalization processes is unclear (Jukschat & Kudlacek, 2018). »Today’s Internet does not simply allow for the dissemination and consumption of ‘extremist material’ in a one-way broadcast from producer to consumer, but also high levels of online social interaction around this material. It is precisely the functionalities of the social Web that causes many scholars, policymakers, and others to believe that the Internet is playing a significant role in contemporary radicalization processes« (Conway, 2017, 80).

1.5 Empirical Findings

Pauwels and Schils (2016) examine the link between extremist content in new social media and self-reported political violence by distinguishing between active and passive forms. In their analysis of data from surveys with a total of 6,020 young Belgian people, they find that actively seeking extremist contacts online, participating in discussions with extremist content, and consuming more extremist online content are all significantly positively related to politically motivated violence against property. Similar results could also be obtained regarding politically motivated violence against people. Considering other variables, such as impulsivity, juvenile delinquency, or religious authoritarianism, they showed that contacts in the real world are just as significant as online contacts (Pauwels & Schils, 2016). Moreover, using the same sample, Pauwels and Hardyns (2018) find that active exposure to social media in terms of communication about extremist content reinforces the already positive effect of endorsement of extremism on self-reported political aggression.

The search for extremist online material was also analyzed by Frissen (2021). He analyzes the relationship between seeking online extremist material and cognitive radicalization among young Muslims in Belgium. He finds that consumption of beheading videos was sought by 36.11 % of the convenience sample, which is a relatively large amount compared to the share of participants consuming other materials, such as jihadist magazines or content in Facebook groups. However, beheading videos have only a small effect on cognitive radicalization and this type of material was the least associated in the model (Frissen, 2021).

Posting, as an active form of online behavior and general communication in right-wing online forums, has been analyzed by Scrivens, Wojciechowski et al. (2021) and Scrivens, Osuna et al. (2021), who find differences between violent and non-violent right-wing extremists. They find more posting activity among non-violent extremists in online forums (Scrivens, Wojciechowski et al., 2021). The authors argue that this may be explained by the clandestine character of violent extremists’ online behavior due to fear of law enforcement agencies. Wolfowicz et al. (2022) included four experimental and 49 observational studies with media-related risk factors for cognitive and behavioral radicalization in their systematic review. According to their review, passive and active forms of engagement with radical content on the Internet reveal small but potentially significant correlations with cognitive radicalization (Wolfowicz et al., 2022).

The extent to which the influence of the Internet on radicalization depends on gender has largely been ignored. Sanchez (2014) notes that the Internet has an influence on women who live in traditional societies. For example, the Internet allows girls and women to interact with strangers outside of the family’s control. Although much is known about gender dynamics in the radicalization processes with reference to different phenomena, only a few studies have explored female usage of the Internet in extremist contexts (Winter et al., 2020). For boys, the misogynistic ›Incel‹ culture shows an example of how gender-specific online activities manifest themselves with close ties to right-wing extremism (O’Malley et al., 2020; Pelzer et al., 2021). Since studies show differences between men and women in the extent of extremist attitudes and online behavior (Almenayes et al., 2014; Krieg et al., 2022; Decker et al., 2022; Goede & Lopez Trillo, 2020; JIM Study, 2021; Küpper et al., 2021), a more in-depth look at online radicalization with a gender differentiation is needed.

Methodologically, the body of literature on online radicalization contains a gap between a vast number of qualitative studies and only a few quantitative studies. Qualitative studies mostly focus on content that is published in extremist forums and social media (Gill, 2007; Gill et al., 2017; Jukschat & Kudlacek, 2017; Meier et al., 2022; Struck, 2019; Struck et al., 2020; Harrendorf et al., 2020; Mischler et al., 2019; Holbrook, 2015). Only a few attempts have been made to analyze these behaviors using a large quantitative sample, such as survey data (Gill et al., 2017; Wolfowicz et al., 2022). Some studies only include single case studies or anecdotes (Gill et al., 2015; Pearson, 2015).

1.6 Hypotheses

This study specifically analyses the link between different online activities and extremist attitudes in the field of Islamism and right-wing extremism among ninth graders in Germany. Based on Social Learning Theory (Akers, 1977), we expect that there is an association. Young people learn extremist views on the Internet through direct contact with extremists or through disseminated propaganda and subsequently develop extremist views themselves.

Because current research lacks a differentiation of various online activities, this study highlights those areas that we believe may be related to extremism. These activities can be active or passive. In particular, we focus on the consumption of political or religious content (passive behavior), and on the posting of political or religious content via social media (active behavior). Furthermore, we consider networking via social media as an important aspect, since previous research only included mostly (deviant) offline peers or friends (Wolfowicz et al., 2020). Other online activities such as gaming, learning, shopping, or streaming can theoretically be part of extremist activities, but are not the focus of this contribution. We assume that these activities must be distinguished because they are of different importance for extremist endeavors. While consumption is a key element of indoctrination, there is not necessarily a direct contact to extremist groups. It is possible that extremist content can be consumed and critically reflected upon.

Many radicalization models and theories assume that a radicalization process consists of multiple stages (Bliesener et al., 2021). Some note that the radicalization process begins with sensitivity (Doosje et al., 2016), a cognitive opening (Wiktorowicz, 2005), the urge to do something about injustice (Moghaddam, 2005), or moral outrage (Sagemann, 2008). Based on this, we deduce that there are also different stages during online radicalization. It is assumed that passive consumption is the first part of the radicalization process. Consumption could also include youthful experimental behavior that does not necessarily lead to radicalization. Only later on does it become clear whether consumption resulted from simple youthful interest or from the beginnings of radicalization.

Networking with people who already belong to a certain group or share certain dissenting views would represent a next stage in online radicalization and provide a space for social learning. Networking is also necessary for clandestine groups to disseminate and plan things that need to be kept away from the public.

Posting, on the other hand, is central to the spread of ideology in the digital age. For users, posting can be experienced as active participation in a social endeavor. For their audiences, who they often consider friends, these users can, intentionally or not, make their posted content seem trustworthy and disguise its extremist character. Only when extremist attitudes are hardened through consumption and networking does active posting occur. Thus, we see the active posting of extremist content as the latter part of online radicalization. Therefore, the specific link between different online activities and extremist attitudes can be analyzed.

The study also considers gender differences within the correlation between online activities and extremist attitudes. While in the offline world, Islamist women tend to be ascribed a passive role, studies have found that women take an active role on the Internet (Nisa, 2019; Nisa 2013). Since explicit Islamist propaganda on the Internet is also directed at girls and women, we assume that they are more active than boys, who are also active in the offline world. In the area of right-wing extremism, there is a classic gender role distribution in which males take the more active and dominant role. Therefore, we expect boys to be more active than girls in both the offline and online worlds. Following the Social Learning Theory, more activity leads to more extremist definitions, which can be referred to as extremist attitudes. This leads to the following Hypotheses:

Islamism:

Hypothesis A1: The more frequently young Muslims consume violent Islamist videos, the more likely they are to have Islamist attitudes.

Hypothesis A2: The more frequently young Muslims meet Muslim friends via the Internet, the more likely they are to have Islamist attitudes.

Hypothesis A3: The more frequently young Muslims post Islamic content on their social media profiles, the more likely they are to have Islamist attitudes.

Hypothesis A4: Muslims with Islamist attitudes use online activities with Islamic or violent Islamist content more frequently than young people with no Islamist attitudes.

Hypothesis A5: There are more young people who initially only passively consume Islamist content than young people who actively post. The number of young people who network online is somewhere in between.

Moreover, gender differences in attitudes and in Internet use in general lead to Hypothesis A6: In the field of Islamism, the use of the Internet plays a bigger role for girls than for boys.

Right-wing extremism:

Hypothesis B1: The more frequently young people visit websites with politically right-wing content, the more likely they are to have right-wing attitudes.

Hypothesis B2: The more frequently young people communicate with right-wing persons on the Internet, the more likely they are to have right-wing attitudes.

Hypothesis B3: The more frequently young people post things with right-wing political content on the Internet, the more likely they are to have right-wing attitudes.

Hypthesis B4: Adolescents with right-wing attitudes use online activities with right-wing content more frequently than young people with no right-wing attitudes.

Hypothesis B5: There are more young people who initially only passively consume right-wing extremist content than young people who actively post. The number of young people who network online lies somewhere in between.

According to research on some specific online activities among male adolescents (O’Malley et al., 2020), we put forth Hypothesis B6: In the field of right-wing extremism, the use of the Internet plays a bigger role for boys than for girls.

2 Method

2.1 The Current Study

The quantitative youth study »JuPe (Perspectives of adolescents)« was conducted within the framework of the joint project »Radicalization within the digital age« and was funded by the German Federal Ministry of Education and Research. The youth study was developed within the framework of subproject II, carried out by the Criminological Research Institute of Lower Saxony, and focuses on the identification of potential risks and the exploration of vulnerable groups.

The aim of the youth study was to investigate socially relevant attitudes and behaviors in the context of radicalization. The survey was conducted in schools and provided information on a wide range of topics, including political views, religion, family, friends, and leisure activities. Psychological and sociological risk factors for radicalization, identified through previous research, were integrated (Goede et al., 2020). The questionnaire also included measures on extremist attitudes and behaviors.

2.2 Data and Participants

The study is based on cross-sectional data, which was gathered through an online school survey of ninth-grade students of all types of school forms except Special Educational Needs and vocational schools. In 11 of 16 federal German states, the authorities gave permission for the survey. The study used an oversampling of cities classified as having an extremism problem. We primarily focused on those cities that had been highlighted in reports by the Federal Office for the Protection of the Constitution, which is the domestic intelligence agency responsible for the detection of extremist attempts (German Federal Ministry of the Interior, Building and Community, 2022). Cities we selected had also been noted in police and media reports for their problems with Islamism or political extremism (Goede et al., 2020). Given that one of the original goals of the project was to analyze Islamist radicalization, we assumed a higher prevalence rate of extremist ideological beliefs in these cities and thus chose them in order to reach a sufficiently large number of relevant participants. Therefore, the sample is not representative of Germany as a whole.

The survey took place from January to December of 2018. All information was self-reported by the students. The questionnaire lasted around 90 minutes and was filled out online using a computer during school time. A trained test supervisor oversaw the standardized interview situation and a teacher was present. The parents were informed about the content of the study approximately one week before and had to provide consent for their child to participate in the study. Additionally, students had the right to not participate or to only answer some of the questions. Participation in the survey was voluntary and anonymous (Goede et al., 2020).

In total, 209 (19.1 %) of the contacted schools participated. Within the selected classes, 65.0 % of students participated in the survey. Following the data correction process, 6,715 from the originally 6,863 questioned students were included in the final sample. The participants were mostly 14 or 15 years old (M = 14.65; SD = 0.72). In terms of gender, 47.3 % were male, 52.5 % were female, and 0.2 % identified as neither male nor female or did not answer the question for other reasons. Of all participants, 43.4 % indicated a migration background, which means that the person or at least one parent was not born in Germany or does not have German citizenship.

2.3 Measurement

Reviews of the current literature show that there is no consensus on how to measure extremist attitudes (Beelmann, 2020; Goede et al., 2020; Lehmann & Jukschat, 2019; Schröder et al., 2020). We decided to measure extremist attitudes based on the definition of Beelmann (2020) but separately by phenomenon, which means that we use two dependent variables. The dependent variables are mean scales which contain items that are in accordance with the above definition. For this purpose, it was checked whether the respective items of the questionnaire were in line with the definition.

Since there are currently no validated scales that measure extremist Internet use, the authors have independently developed items for each examined extremist phenomenon. These original items are critically discussed in the conclusion.

2.3.1 Dependent Variables

Islamist attitudes. The term Islamism refers to a form of political extremism. Followers of Islamism understand Islam to be not only a religion, but also a political system (German Federal Ministry of the Interior, Building and Community, 2022). Most of the items have been developed by Bergmann et al. (2017), with reference to studies by Brettfeld and Wetzels (2007) or Frindte et al. (2011). In this study, six items such as »Islamic rules of the Sharia are better than the German laws« measure Islamist attitudes in the sense of Beelmann’s (2020) definition (see Appendix A).

Answer categories for all the presented statements were given on a five-point Likert scale that were labeled »1 – completely disagree«, »2 – rather disagree«, »3 – partly this/partly that«, »4 – rather agree« and »5 – completely agree«. The dependent variable to measure Islamist attitudes is a mean scale. Cronbachs α shows a satisfactory result of .79.

Right-wing attitudes. On the political level, right-wing extremism includes an affinity for authoritarian regimes, chauvinism, and the trivialization or justification of National Socialism. Through antisemitic, xenophobic, and social Darwinist attitudes, this ideology is reanchored to the social level (Kiess & Decker, 2016). Decker & Brähler (2006) developed a scale considering these dimensions. In Germany, two studies regularly focus on right-wing attitudes of the German population using this scale (Küpper et al., 2021; Decker et al., 2022). On this basis, the same dimensions and similar items were used in our questionnaire. With the aim of using appropriate wording for adolescent students, some items were adjusted to make the content more understandable. Some new items were also developed by the authors. After carefully reviewing the items in light of Beelmann’s (2020) definition of extremism, nine items such as »Without the Holocaust, Hitler would be considered a great statesman today« were used to measure right-wing attitudes (see Appendix A).

The dependent variable for right-wing attitudes is a mean scale of the nine items. Answers were also given on a five-point Likert scale. The analysis of Cronbach’s α shows a satisfactory result of .86.

2.3.2 Independent Variables

Religious and political online activities. Since there is a lack of empirical data in current research that shows the individual influence of different online activities, we decided to consider different aspects of political and religious Internet use. The statements we used have been abbreviated as consumption, networking, and posting. Those statements contain examples of each phenomenon. The reason for this differentiation was the assumed relation with extremist attitudes that have also been considered in previous research. Since the effects of consuming (Frissen, 2021; Wolfowicz et al., 2020) or posting political or religious content (Klausen, 2015; Scrievens, Osuna et al., 2021; Scrievens, Wojciechowski et al., 2021) as well as meeting new people via networking (e.g. Klausen et al., 2018; Pauwels and Schils, 2016; Winter et al., 2020) are potentially relevant for extremist attitudes but have never been compared systematically, online activities are represented by these three items. Furthermore, we assume that the three different activities occur at different stages of radicalization and thus progress from a rather passive, content experimentation behavior to active online behavior. We consider the development of the items as an initial attempt and will discuss this in the conclusion of the paper, which leads to our suggestions for further quantitative research. Answer categories were »1 = never,« »2 = seldom,« »3 = sometimes,« and »4 = often.« The items can be found in Table 2 for Islamism and Table 4 for right-wing extremism.

2.3.3 Control Variables

For the following analyses, Gender is measured binarily, since only 0.2 % did not identify as male or female. Therefore, the relevant categories are »1 – male« and »2 – female.«

General Internet use is measured by six items such as »How often do you use the Internet?« (see Appendix B). The answer categories ranged from 1 to 5 and were labeled »1 – not at all« to »5 – very often« for the first item and »1 – completely disagree« to »5 – completely agree« for the other items.

Socioeconomic background is measured by three items such as »My family manages well with the money they have each month« (see Appendix B). All items could be answered by a five-point Likert scale from »1 – completely disagree« to »5 – completely agree.«

Predicted school-leaving qualification is measured by one item that includes the categories »1 – other« and »2 – A-levels (Abitur).«

2.4 Analytical Strategy

Descriptive results are presented first. Then, first for Islamism and then for right-wing extremism, the level of Internet activity is evaluated on the basis of mean comparisons, differentiated by extremist/non-extremist and gender. The dependent variables are mean scales with a range from 1 to 5. At point 3.00, these scales are dichotomized. Students with a value higher than 3.00 are considered to have extremist attitudes, since answer categories for the single items chosen higher than 3 (»4 – rather agree« and »5 – completely agree«) can be considered as agreement to the statements. The purpose of the dichotomization are mean comparisons of the groups. Due to the skewed distribution of the Internet items, the Mann-Whitney-U-Test is used.

To measure the intercorrelations of the different types of online activity and extremist attitudes, we conducted linear regression models with standardized beta coefficients and the two mean scales for extremist attitudes as dependent variables using IBM SPSS Statistics (Version 24). Therefore, not only extremist youth were included, but all participants, in order to take advantage of the entire variance of the data. For the area of Islamism, only Muslim youths could be considered in this study since the Internet items with Islamic content could only be answered by Muslims. For this, a filter was set in the questionnaire. All independent Internet items, as well as gender, age, socioeconomic status, and predicted school-leaving qualification, were entered as control variables.

Additionally, we calculated interaction effects to measure the interactions between gender and the examined main effects. Therefore, we z-transformed the relevant variables (Aiken & West, 1991). The interaction variables (Internet items X gender) were also entered.

3 Results

3.1 Descriptive Results

Table 1 shows the descriptive results of extremist attitudes, control variables, and online activities. In this study, 14.8 % (n = 975) considered themselves to be Muslim. The analysis shows that 7.2 % of the Muslim students show Islamist attitudes (7.1 % among male students and 7.3 % among female students). In the following, we will refer to this group as Islamists. Of all Islamists in the sample, 47.5 % are male and 52.5 % female. Of all students, 6.4 % show right-wing attitudes (8.9 % among male students and 4.0 % among female students). This group is called the right-wing extremists and of those, 67.0 % are male and 33.0 % female. The distinction between extremists and non-extremists is carried out to subsequently compare the frequency of Internet use for political or religious motives between the extremist-minded youth and the total sample.

Table 1:

Means, standard deviations, and range of study variables.

Proportion (%) M SD Range
Dependent variables
Islamist attitudes (n = 819) 7.2 1.89 0.74 1 5
Right-wing attitudes (n = 5,586) 6.4 1.87 0.72 1 5
Control variables
Gender (1 = male, 2 = female) 47.4 male, 52.6 female 1.53 0.50 1 2
Socioeconomic background 3.86 0.80 1 5
Predicted school-leaving qualification 2.63 0.62 1 3
General Internet use 3.60 0.73 1 5
Internet variables – Islamism (nmin = 878) Consumption 1.39 0.70 1 4
Networking 1.58 0.84 1 4
Posting 1.63 0.88 1 4
Internet variables – Right-wing(n min = 6,105)Consumption Networking Posting 1.331.251.16 0.660.600.51 111 444

3.2 Analysis of Islamism

The purpose of Table 2 is to illustrate how frequently Muslim students use the Internet for Islamic or Islamist purposes, and which online activity is used most often. First, it can be shown that most of the Muslim students do not use the Internet for online activities with Islamic content, such as posting suras or quotes or meeting Muslims friends. For example, 71.4 % said they have never seen an Islamist violence video and 62.5 % have never met Muslim friends over the Internet. Of all Muslim students, 17.6 % »sometimes« or »often« meet Muslim friends via the Internet. Almost one fifth (19.5 %) »sometimes« or »often« posts Islamic content on their social media profile. Second, 8.6 % of the Muslim students »sometimes« or »often« watch videos with violent Islamist content. It can be deduced that active posting of Islamic content, followed by networking with other Muslims, is the most frequently used activity.

Table 2

Online activities with Islamic or violent Islamist content of all Muslims (nmin = 878); data in valid percentages

never seldom sometimes often
I watch videos in which Muslims use violence to fight the West and non-believers. (consumption) 71.4 19.9 6.7 1.9
I meet Muslim friends over the Internet. (networking) 62.5 19.9 14.8 2.8
I post Islamic suras or quotes on my social media profiles. (posting) 60.3 20.3 15.7 3.8

The purpose of Table 3 is to illustrate the mean values of each item representing online activities. We distinguished between adolescents with Islamist attitudes >3 on a fivepoint Likert scale and those with less or no approval to the statements. Mean values for the whole sample are reported as well.

The mean values indicate that online activities are not very prevalent in general. When the sample is split into extremists and non-extremists and by gender, the mean values range between 1.32 and 2.16 on a scale from 1 to 4. Differences between the groups are analyzed with Mann-Whitney-U-Tests. Extremists and non-extremists show significant differences for consumption and networking, but not for posting if gender is not differentiated (Table 3). The mean values of extremists are higher than those of non-extremists.

Differences between boys and girls are found among extremists for consumption and posting (Table 3). Girls have higher mean values among these items. Among non-extremists, only posting shows differences between boys and girls. Girls have a higher mean value here as well. When the whole sample is considered, it is again only posting that shows significant differences among genders, with girls having a higher mean value than boys.

Table 3:

Religious and Islamist online activities. Mean values, standard deviations, and asymptotic significance for differences between genders. Sample includes Muslim students only.

Item Extremists 1 Non-Extremists All
all male female sig. (gender) all male female sig. (gender) sig. (extr.) all male female sig. (gender)
Consumption Mean 1.80 1.54 2.03 .023 1.35 1.38 1.32 .426 .000 1.38 1.40 1.38 .905
sd 0.92 0.84 0.95 0.64 0.68 0.61 0.68 0.71 0.69
n 59 28 31 727 352 375 786 413 465
Networking Mean 1.97 1.75 2.16 .072 1.56 1.56 1.56 .733 .001 1.59 1.56 1.60 .530
sd 1.00 1.04 0.93 0.83 0.81 0.85 0.85 0.82 0.86
n 59 28 31 726 351 375 785 413 466
Posting Mean 1.76 1.46 2.03 .019 1.62 1.49 1.74 .000 .434 1.63 1.47 1.77 .000
sd 1.04 0.88 1.11 0.87 0.79 0.92 0.88 0.79 0.93
n 59 28 31 727 352 375 786 413 466

1 Islamist attitudes >3

The results of the linear regression models with Islamist attitudes as the dependent variable can be found in Table 4. Interactions between online activities and gender are included in Model 1 b. The results for Model 1 a (F(7,767)=21,761, p < .001) are mostly as expected, though socio-economic background shows no statistically significant correlation with Islamist attitudes. Gender (β = -.07*) is negatively related to Islamist attitudes, but the effect is very small. Also as predicted, school-leaving qualification (Abitur) (β = -.17***) is negatively related to Islamist attitudes. The lower the predicted qualification, the higher the Islamist attitudes. Consumption (β = .19***) and posting (β = .17***) are positively related to Islamist attitudes, which means that students who use the Internet for Islamic or violent Islamist content show more Islamist attitudes. Networking also shows a significant positive effect (β = .13**). The explanation of variance can be described as moderate according to Cohen (1988). Since Model 1 b (F(10,761)=15,506, p < .001) shows no significant effects for the interactions, it can be discarded. This means that there are no gender-related differences in terms of Internet activities and their effects.

Table 4

Linear regression predicting Islamist attitudes across online activities with Islamic or violent Islamist content.

Model 1a Model 1b
β β
Gender (1 = male, 2 = female) -.07* -.07*
Socioeconomic background .04 .04
Level of predicted school-leaving qualification -.17*** -.17***
General Internet use -.04 -.05
Consumption .19*** .04
Networking .13** .17
Posting .17*** .11
Consumption x Gender .16
Networking x Gender -.05
Posting x Gender .06
Adj. R² .158 .158
N 774 774
Note. * p < .05, ** p < .01, *** p < .001

3.3 Analysis of right-wing Extremism

Table 5 shows the frequencies of online activities with right-wing content of all surveyed adolescents. First, more than 75 % of the students do not use the Internet to consume right-wing content, whilst 7.6 % do this »sometimes« or »often«. Second, 5.8 % of the students »sometimes« or »often« meet people with right-wing attitudes via the Internet, and 3.9 % of the students »sometimes« or »often« post right-wing content on social media. From this it can be deduced that young people most often use the passive form of online activity, namely consuming right-wing content. Active posting of right-wing content is done only by very few young people.

Table 5

Frequencies of online activities with right-wing content of all adolescents (All) (nmin = 6,120), data in valid percentages

never seldom sometimes often
I like to visit websites that have political right-wing content. (consumption) 75.7 16.7 6.1 1.5
I meet people with right-wing attitudes over the Internet. (networking) 82.3 11.9 4.4 1.4
I post things like pictures, links or texts with political right-wing content on social media (such as Facebook). (posting) 89.3 6.8 2.7 1.2

The mean values indicate that online activities are not very prevalent in general. When the sample is split into extremists and non-extremists and by gender, the mean values range between 1.11 and 1.96 on a scale from 1 to 4 (Table 6).

Extremists and non-extremists show significant differences according to Mann-Whitney-U-Tests for consumption, networking, and posting if gender is not differentiated (Table 6). Extremists show higher mean values than non-extremists. Differences between boys and girls are found among extremists for consumption and networking (Table 6). In both cases, boys show higher mean values than girls. Among non-extremists, only networking shows differences between boys and girls. Boys show higher mean values here as well. When the whole sample is considered, all three areas of online activities show significant differences between genders. In all three areas, boys show higher mean values than do girls.

Table 6:

Online activities with right-wing content. Mean values, standard deviations and asymptotic significance for differences between genders.

Item Extremists 1 Non-Extremists All
all male female sig. (gender) all male female sig. (gender) sig. (extr.) all male female sig. (gender)
Consumption Mean 1.87 1.96 1.69 .017 1.29 1.30 1.28 .463 .000 1.33 1.36 1.31 .016
sd 1.07 1.08 1.02 0.60 0.61 0.59 0.66 0.69 0.63
n 346 232 114 5,124 2,360 2,757 5,470 2,861 3,287
Networking Mean 1.65 1.78 1.52 .019 1.22 1.26 1.19 .000 .000 1.25 1.31 1.20 .000
sd 0.99 1.03 0.89 0.55 0.60 0.51 0.60 0.67 0.53
n 344 231 113 5,111 2,353 2,751 5,455 2,843 3,269
Posting Mean 1.53 1.59 1.41 .142 1.12 1.13 1.11 .126 .000 1.15 1.18 1.14 .001
sd 0.87 0.93 0.75 0.44 0.46 0.42 0.49 0.55 0.48
n 345 232 113 5,121 2,359 2,755 5,466 2,857 3,276

1 Right-wing attitudes >3

The results of the linear regression models for the relationship between right-wing attitudes and online activities with right-wing content are shown in Table 7. Model 2 a shows the coefficients for the independent variables without interaction terms of online activities and gender (F(7,5389)=182,979, p < .001). Model 2 b considers the interaction terms and one such interaction is identified (F(10,5386)=132,214, p < .001). In Model 2 b, the predicted school-leaving qualification Abitur (β = -.21***) shows a negative effect on extremist attitudes. Students who are posting (β = .17***) right-wing content are more likely to show right-wing attitudes. The effect of networking on right-wing attitudes is not significant. Exploring the interaction between the three different Internet items with gender, one can see that gender decreases the effect of consumption on right-wing attitudes (β = -.20***). This means that the impact of consumption is lower on right-wing attitudes among females and higher among males. The general effect of gender is negative in this Model, which indicates higher extremist attitudes among males. The adjusted R² with .191 for Model 2 a and .196 for Model 2 b is, according to Cohen (1988), a moderate explanation of variance.

Table 7

Linear regression predicting right-wing attitudes across online activities with political content.

Model 2a Model 2b
β β
Gender (1 = male, 2 = female) -.10*** -.10***
Socioeconomic background -.02 -.02
Level of predicted school-leaving qualification -.21*** -.21***
General Internet use .09*** .09***
Consumption .19*** .39***
Networking .04** .01
Posting .12*** .17***
Consumption x Gender -.20***
Networking x Gender .03
Posting x Gender -.06
Adj. R² .191 .196
N 5,396 5,396
Note. * p < .05, ** p < .01, *** p < .001

To visualize the significant interaction found in Model 2 b, the effects of consumption on right-wing attitudes were differentiated by gender (Figure 1). The graphical representation of the interaction effect clearly shows that, for boys, frequent consumption of right-wing content on the Internet leads them to display stronger right-wing extremist attitudes than would be the case for girls.

Figure 1 
            Effects of consumption among male and female students on right-wing attitudes.
Figure 1

Effects of consumption among male and female students on right-wing attitudes.

4 Limitations

Before discussing the results and drawing conclusions, some general limitations must be mentioned. All empirical analyses in this article are based on cross-sectional data. Results are thus unable to indicate causal relations between the considered constructs. The results are not able to indicate whether online activities influence attitudes or if attitudes influence online behavior. However, the causal implications are derived from theoretical assumptions. Conclusions drawn apply only to ninth-grade students in parts of Germany; no representative sample was used. The sample design is nevertheless robust and suitable for the purpose of the analysis. The data analyzed were self-reported by the young people on a very sensitive topic. Therefore, social desirability and the possibility of incorrect answers should be considered when interpreting the data. To minimize these potential limitations, extensive pre-testing and data cleaning were conducted and the anonymity of the survey was emphasized. It should also be mentioned that the analyses of different phenomena of extremism do not indicate similar importance or a similar threat associated with the different phenomena. Every form of extremism (in this article, right-wing and Islamist) is measured by items that reflect different aspects of the ideologies. The threat of these phenomena and the importance of the single forms of extremism within research should be discussed. The adjusted R² differs from .16 to .20 between the models, which indicates a moderate quality of the models to explain the variance of the dependent variables, although this is quite satisfactory given the number of independent variables in the regression models. The low variance resolution of the models can also be interpreted as an indication that further influencing factors become effective in the development process, which should be further investigated. In addition, the wording of the items is critical because neither the motivation to visit websites or social media platforms is clear, nor are the reasons for meeting people. It can also not be ruled out that the term »right-wing content« was understood in different ways or that participants were unable to identify right-wing content and therefore did not indicate this online activity. The statement used to measure consumption of Islamist videos included the aspect of violence in the videos. Violence was not an explicit part of the statement used to measure right-wing consumption of videos. This complicates a comparison between right-wing and Islamist consumption measurements.

5 Discussion

The purpose of this article was to investigate the link between extremist attitudes and online activities. Thus, in this contribution, online activities included consumption, networking, and posting in an Islamic or political context. Extremist attitudes were defined according to Beelmann’s (2020) definition of extremism and were represented through Islamist and right-wing statements.

Regarding Hypothesis A1, it can be stated that consumption of Islamic or violent Islamist content showed a small positive association with Islamist attitudes. With regard to Hypothesis A2, the results indicated a small connection between networking among Muslim students and extremist attitudes. Hypothesis A3 could also be confirmed: posting Islamic content slightly increased the likelihood of having Islamist attitudes. Even though there were no significant differences found in bivariate analysis between extremists and non-extremists, the regression model indicates an effect. Hypothesis A4 must be rejected since extremists and non-extremists show no significant differences for posting. Significant differences between the two study groups can only be found for networking and consumption. Hypothesis A5 must be rejected because the mean values for consumption are lower than for posting and networking. Posting (male only) and networking have higher mean values and posting has the highest mean value among girls. Regarding gender effects, Hypothesis A6 must also be rejected. Although gender differences were found for consumption and posting, a multivariate analysis revealed no significant interaction effects for online activities and gender on Islamist attitudes.

Hypothesis B1 states that the consumption of right-wing websites increases the likelihood of having right-wing attitudes. This Hypothesis can be confirmed. However, the association depends on the gender if the interaction of consumption and gender is considered and is lower among females. Hypothesis B2 cannot be confirmed. The main effect of meeting right-wing people on the Internet on extremist attitudes was not significant. Regarding Hypothesis B3, a small effect of posting right-wing content on right-wing attitudes can be confirmed. Hypothesis B4 can be confirmed, since extremists and non-extremists show significant differences for the extent of online activities. Hypothesis B5 can also be confirmed since consumption is the most prevalent online activity, followed by networking and posting, even though the differences are very small and overlap if different subsamples are considered. Taking the gender differentiation into account, one significant interaction effect was found for consumption of right-wing websites and gender. Consumption had a smaller effect on right-wing attitudes among females. Accordingly, Hypothesis B6 can be only partly confirmed because it applied for only one of the three online activities.

In summary, the results of the regression models indicated significant effects of most Internet activities on both phenomena. The positive effects showed that more online activities with Islamic/Islamist or right-wing content indicate more Islamist and right-wing attitudes. This supports the theoretical assumption that definitions, measured as extremist attitudes, are more prevalent among those, whose differential association is online and who therefore potentially imitate extremist online behavior. As a first stage of a radicalization process, consuming e.g. propaganda can lead to a cognitive opening and sensitivity for extremist content (Wictorowicz, 2005; Doosje et al., 2016). Networking, much comparable to offline social interactions and therefore seen as the differential association in the Social Learning Theory, can potentially lead to imitation of all kinds of extremist behavior. However, in our study, networking is not as important as consumption and posting for the context of right-wing attitudes. Posting, as an active form, can lead to positive reactions and enables differential reinforcement.

For right-wing attitudes, the prevalence of the three types of activities is in line with expectations, but for Islamism, posting and networking are more prevalent than consumption. This can be due to the different formulation of the items. Results for the effects of interactions of online activities with gender on extremist attitudes are mostly not as expected as well. In general, findings that argue against our hypotheses, which had been derived from theory, cannot be easily explained. More detailed analyses in future research are needed to avoid making the interpretation of the results found here too speculative. Nevertheless, it can be said that the links between online activities and extremist attitudes are more complex than assumed.

6 Conclusion

Nowadays, adolescents grow up as so-called digital natives. The Internet and social media in particular are used almost naturally in everyday life. The online sphere facilitates a place for socialization and countless interactions. Akers’ (1977, 1998) Social Learning Theory considers social learning to be a core element of the development of deviant attitudes among others. Based on his theory, we analyzed political and religious online activities, which, we believe, potentially constitute the process of social learning via the Internet and can consequently lead to extremist attitudes.

The items consumption, networking, and posting were used to measure online activities. Extremist attitudes were measured according to Beelmann’s (2020) definition of extremism. Islamist attitudes were related to all three types of online activities. For right-wing attitudes, consumption plays a particular role, whereas posting only shows a small effect and networking shows no effect at all.

As one of the first studies, our approach distinguished between the different functions of the Internet, which were only singularly considered in previous quantitative research (Frissen, 2021; Pauwels & Schils, 2016; Pauwels & Hardyns, 2018) or not considered at all (Ducol et al., 2016, Gill et al., 2017, Knipping-Sorokin & Stumpf, 2018). Regarding the development of measurement instruments for online activities, further research is needed. A more robust set of items of validated quality should be developed in further studies. However, it can be stated that the distinction between consumption, posting, and networking was worthwhile for the analysis. The different effects of the two phenomena support the relevance of this distinction. The results can be utilized not only by future research projects, but also by prevention efforts. For example, the analyses offer a better understanding of the (digital) world young people live in. The correlations between attitudes and online behavior can provide hints for prevention efforts about potentially successful content and places to position their efforts. While for Islamism, consumption, networking, posting, and educational aspiration all play a role in the development of extremist attitudes among youth, in right-wing extremism it is primarily consumption and educational aspiration. Gender played a role in both phenomena, although the gender differentiation regarding online activities was limited for Islamism since significant differences were only found in online activities when differentiated for extremists and non-extremists, but not in a multivariate model. The next step should be to look at whether the content consumed online differ between girls and boys. It is possible that it is not the level of Internet activity that differs, but merely the content to which young people are directed by gender-specific extremist propaganda. Our analysis shows which activities are relevant in the lives of young people with extremist attitudes. Tailored intervention measures are necessary to counter extremism and minimize restrictions on the freedom of the public. This research can assist in the development of such measures and should be expanded upon.

References

Aiken, L. S. & West, S. G. (1991). Multiple Regression: Testing and Interpreting Interactions. Search in Google Scholar

Akers, R. L. (1977). Deviant Behavior. A Social Learning Approach. Wadsworth Publishing Company.Search in Google Scholar

Akers, R. L. (1998). Social Learning and Social Structure. A General Theory of Crime and Deviance. Northeastern Univ. Press.Search in Google Scholar

Akins, J. K. & Winfree, L. T. (2016). Social Learning Theory and Becoming a Terrorist: New Challenges for a General Theory. In G. Lafree & J. D. Freilich (Eds.), The Handbook of the Criminology of Terrorism (Wiley handbooks in criminology and criminal justice, 8th Ed. pp. 133-149). John Wiley & Sons, Inc.10.1002/9781118923986.ch8Search in Google Scholar

Almenayes, J. J. (2014). Religiosity and the perceived consequences of social media usage in a Muslim country. Journal of Arts and Humanities, 3(5), 108-117. https://doi.org/10.18533/journal.v3i5.439Search in Google Scholar

Alwin, D. F., & Krosnick, J. A. (1991). Aging, Cohorts, and the Stability of Sociopolitical Orientations over the Life Span. American Journal of Sociology, 97(1), 169-195. http://dx.doi.org/10.1086/229744.10.1086/229744Search in Google Scholar

Baier, D., Manzoni, P., Haymoz, S., Isenhardt, A., Kamenowski, M., & Jacot, C. (2019). Politischer Extremismus unter Jugendlichen in der Schweiz [Political Extremism among Young People in Switzerland]. Zeitschrift für Jugendkriminalrecht und Jugendhilfe, 30(1), 4–11.Search in Google Scholar

Bandura, A. (1977). Social learning theory. Prentice-Hall.Search in Google Scholar

Becker, M. H. (2019). When Extremists Become Violent: Examining the Association Between Social Control, Social Learning, and Engagement in Violent Extremism. Studies in Conflict & Terrorism, 44(12), 1104-1124.10.1080/1057610X.2019.1626093Search in Google Scholar

Beelmann, A., Jahnke, S., & Neudecker, C. (2017). Prävention von Radikalisierungsprozessen: Grundlagen entwicklungsorientierter Maßnahmen [Prevention of radicalization processes: Foundations of Development-Oriented Measures]. Neue Kriminalpolitik, 29(4), 440-49. http://doi.org/10.5771/0934-9200-2017-4-44010.5771/0934-9200-2017-4-440Search in Google Scholar

Beelmann, A. (2020). A Social-Developmental Model of Radicalization: A Systematic Integration of Existing Theories and Empirical Research. International Journal of Conflict and Violence, 14, 1-14. https://doi.org/10. 4119/ijcv- 3778Search in Google Scholar

Behr, I. von, Reding, A., Edwards, C. & Gribbon, L. Radicalisation in the digital era: The use of the internet in 15 cases of terrorism and extremism 2013.Search in Google Scholar

Benslama, F. (2017). Der Übermuslim: Was junge Menschen zur Radikalisierung treibt [What Drives Young People to Radicalization]. Matthes & Seitz.Search in Google Scholar

Bergmann, M.C., Baier, D., Rehbein, F. & Mößle, T. (2017). Jugendliche in Niedersachsen: Ergebnisse des Niedersachsensurveys 2013 und 2015 [Young People in Lower Saxony: Results of the Lower Saxony Survey 2013 and 2015]. (KFN-Research Reports, Vol. 131). Kriminologisches Forschungsinstitut Niedersachsen.Search in Google Scholar

Bliesener, T., Schröder, C. P. & Lehmann, L. (2021). Pathways to radicalization in adolescence: The development of ideological beliefs, acceptance of violence, and extremist behavior. Monatsschrift für Kriminologie und Strafrechtsreform / Journal of Criminology an Penal Reform, 104(3), 231-242. https://doi.org/10.1515/mks-2021-012410.1515/mks-2021-0124Search in Google Scholar

Brettfeld, K. & Wetzels, P. Muslime in Deutschland (2007). Integration, Integrationsbarrieren, Religion sowie Einstellungen zu Demokratie, Rechtsstaat und politisch-religiös motivierter Gewalt. Ergebnisse von Befragungen im Rahmen einer multizentrischen Studie in städtischen Lebensräumen [Muslims in Germany (2007). Integration, barriers to integration, religion, and attitudes toward democracy, the rule of law, and politico-religiously motivated violence. Results of Surveys in the Context of a Multicenter Study in Urban Living Spaces]. Hamburg.Search in Google Scholar

Burgess, R. L. & Akers, R. L. (1966). A Differential Association-Reinforcement Theory of Criminal Behavior. Social Problems 14(2), 128-147. https://doi.org/10.1525/sp.1966.14.2.03a0002010.1525/sp.1966.14.2.03a00020Search in Google Scholar

Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. Routledge.Search in Google Scholar

Conway, M. (2017). Determining the Role of the Internet in Violent Extremism and Terrorism: Six Suggestions for Progressing Research. Studies in Conflict & Terrorism, 40(1), 77-98. https://doi.org/10.1080/1057610X.2016.115740810.1080/1057610X.2016.1157408Search in Google Scholar

Cherney, A., Belton, E., Norham, S. A. B., & Milts, J. (2020). Understanding youth radicalisation: an analysis of Australian data. Behavioral Sciences of Terrorism and Political Aggression.https://doi.org/10.1080/19434472.2020.181937210.1080/19434472.2020.1819372Search in Google Scholar

Decker, O., Kiess, J., Heller, A., Schuler, J., & Brähler, E. (2022). Die Leipziger Autoritarismus-Studie 2022: Methode, Ergebnisse und Langzeitverlauf [The Leipzig Authoritarianism Study 2022: Method, Results, and Long-Term Trajectory]. In O. Decker, J. Kiess, A. Heller & E. Brähler (Eds.), Autoritäre Dynamiken in unsicheren Zeiten. Neue Herausforderungen – alte Reaktionen?Leipziger Autoritarismus Studie 2022 (pp. 31–90). Psychosozial-Verlag.Search in Google Scholar

Decker, O. & Brähler, E. (2006). Vom Rand zur Mitte: Rechtsextreme Einstellungen und ihre Einflussfaktoren in Deutschland [From the Fringe to the Center: Right-Wing Attitudes and Their Influencing Factors in Germany]. Friedrich-Ebert-Stiftung, Forum Berlin.Search in Google Scholar

Dienstbühl, D. & Weber, M. (2014). Rekrutierung im Cyberspace – wie Extremisten das Internet nutzen [Recruitment in cyberspace – how extremists use the Internet]. Journal EXIT-Deutschland. Zeitschrift für Deradikalisierung und demokratische Kultur, 35-45.Search in Google Scholar

Doosje, B., Moghaddam, F. M., Kruglanski, A. W., Wolf, A. d., Mann, L. & Feddes, A. R. (2016). Terrorism, radicalization and de-radicalization. Current Opinion in Psychology 11, 79–84. https://doi.org/10.1016/j.copsyc.2016.06.00810.1016/j.copsyc.2016.06.008Search in Google Scholar

Ducol, B., Bouchard, M., Davies, G., Ouellet, M. & Neudecker, C.: Assessment of the State of Knowledge: Connections Between Research on the Social Psychology of the Internet and Violent Extremism 2016.Search in Google Scholar

Edwards, C. & Gribbon, L. (2013). Pathways to Violent Extremism in the Digital Era. The RUSI Journal 158, 40-47. https://doi.org/10.1080/03071847.2013.84771410.1080/03071847.2013.847714Search in Google Scholar

Emmelkamp, J., Asscher, J. J., Wissink, I. B., & Stams, G. J. J.M. (2020). Risk factors for (violent) radicalization in juveniles: A multilevel meta-analysis. Aggression and Violent Behavior, 55.https://doi.org/10.1016/j.avb.2020.10148910.1016/j.avb.2020.101489Search in Google Scholar

Frindte, W., Boehnke, K., Kreikenbom, H. & Wagner, W. (2011). Lebenswelten junger Muslime in Deutschland: Ein sozial- und medienwissenschaftliches System zur Analyse, Bewertung und Prävention islamistischer Radikalisierungsprozesse junger Menschen in Deutschland [Lifeworlds of Young Muslims in Germany].Search in Google Scholar

Frissen, T. (2021). Internet, the great radicalizer? Exploring relationships between seeking for online extremist materials and cognitive radicalization in young adults. Computers in Human Behavior 114(1), 1-13. https://doi.org/10.1016/j.chb.2020.10654910.1016/j.chb.2020.106549Search in Google Scholar

German Federal Ministry of the Interior, Building and Community. (2022). Verfassungsschutzbericht 2021 [Report 2019]. https://www.bmi.bund.de/SharedDocs/downloads/DE/publikationen/themen/sicherheit/vsb-2019-gesamt.pdf?__blob=publicationFile&v=10Search in Google Scholar

Gill, P. (2007). A multi-dimensional approach to suicide bombing. International Journal of Conflict and Violence, 142-159.Search in Google Scholar

Gill, P., Corner, E., Conway, M., Thornton, A., Bloom, M. & Horgan, J. (2017). Terrorist Use of the Internet by the Numbers. Criminology & Public Policy 16, 99-117. https://doi.org/10.1111/1745-9133.1224910.1111/1745-9133.12249Search in Google Scholar

Gill, P., Corner, E., Thornton, A. & Conway, M. (2015). What are the roles of the Internet in terrorism? Measuring online behaviours of convicted UK terrorists.Search in Google Scholar

Goede, L.-R. & Lopez Trillo, A. (2020). Islamistischer Extremismus: anderes Geschlecht, andere Risikofaktoren? [Islamic Extremism: different gender different risk factors?]. RPsych, 6(4), 533–558.10.5771/2365-1083-2020-4-533Search in Google Scholar

Goede, L.-R., Schröder, C.P. & Lehmann, L. (2020). Perspektiven von Jugendlichen: Ergebnisse einer Befragung zu den Themen Politik, Religion und Gemeinschaft im Rahmen des Projektes „Radikalisierung im digitalen Zeitalter (RadigZ)“ [Perspectives of adolescents: Results of a Survey on Politics, Religion, and Community as Part of the Project „Radicalization within the Digital Age (RadigZ)“]. (KFN-Research Reports, Vol. 151). Kriminologisches Forschungsinstitut Niedersachsen.Search in Google Scholar

Greve, W. (2007). Selbst und Identität im Lebenslauf [Self and identity in the life course]. In J. Brandstädter & U. Lindenberger (Eds.), Entwicklungspsychologie der Lebensspanne (pp. 305–336). Kohlhammer.Search in Google Scholar

Guhl, J., Ebner, J. & Rau, J. (2020). Das Online-Ökosystem Rechtsextremer Akteure [The online ecosystem of far-right actors].Search in Google Scholar

Harrendorf, S., Müller, P. & Mischler, A. (2020). Das Zeitalter des digitalen Extremismus? Einige Befunde zu politisch extremer Kommunikation in Social Media [The Age of Digital Extremism? Some Findings on Politically Extreme Communication in Social Media]. Zeitschrift für Internationale Strafrechtsdogmatik, 411-420.Search in Google Scholar

Hohnstein, S. & Glaser, M. (2017). Wie tragen digitale Medien zu politischweltanschaulichem Extremismus im Jugendalter bei und was kann pädagogische Arbeit dagegen tun? Ein Überblick über Forschungsstand, präventive und intervenierende Praxis im Themenfeld [How do digital media contribute to political-ideological extremism in adolescence and what can educational work do about it?]: In S. Hohnstein und M. Herding (Eds.), Digitale Medien und politisch-weltanschaulicher Extremismus im Jugendalter: Erkenntnisse aus Wissenschaft und Praxis (pp. 243-281).Search in Google Scholar

Holbrook, D. (2015). A critical analysis of the role of the internet in the preparation and planning of acts of terrorism. Dynamics of Asymmetric Conflict, 121-131. https://doi.org/10.1080/17467586.2015.106510210.1080/17467586.2015.1065102Search in Google Scholar

Hussain, G. & Saltman, E.M. (2014). Jihad Trending: A Comprehensive Analysis of Online Extremism and How to Counter it.Search in Google Scholar

JIM Study [JIM-Studie] (2021). Jugend, Information, Medien. Basisuntersuchung zum Medienumgang 12- bis 19-Jähriger. [JIM Study 2021. Youth, Information, Media. Basic study on media use among 12- to 19-year-olds.] https://www.mpfs.de/fileadmin/files/Studien/JIM/2021/JIM-Studie_2021_barrierefrei.pdfSearch in Google Scholar

Jukschat, N. & Kudlacek, D. (2018). Neue Medien und gewaltorientierter Islamismus: Stand der Forschung und offene Fragen [New Media and Violence-Oriented Islamism: State of Research and Open Questions]. In M. Glaser, A. Frank und M. Herding (Eds.), Gewaltorientierter Islamismus im Jugendalter: Perspektiven aus Jugendforschung und Jugendhilfe (2. Ed. Sozialmagazin, pp. 52-61).Search in Google Scholar

Jukschat, N. & Kudlacek, D. (2017). Ein Bild sagt mehr als tausend Worte? Zum Potenzial rekonstruktiver Bildanalysen für die Erforschung von Radikalisierungsprozessen in Zeiten des Internets – eine exemplarische Analyse [A picture is worth a thousand words? On the Potential of Reconstructive Image Analyses for Researching Radicalization Processes in Times of the Internet – an Exemplary Analysis]. In: S. Hohnstein und M. Herding (Eds.), Digitale Medien und politisch-weltanschaulicher Extremismus im Jugendalter: Erkenntnisse aus Wissenschaft und Praxis (pp. 59-82).Search in Google Scholar

Koehler, D. (2014). The Radical Online: Individual Radicalization Processes and the Role of the Internet. Journal for Deradicalization, Winter 2014/2015(1), 116-134.Search in Google Scholar

Kiess, J. & Decker, O. (2016). Comparing right-wing extremist attitudes: Lack of research or lack of theory? In J. Kiess, O. Decker and E. Brähler (Eds.), German Perspectives on Right-Wing Extremism: Challenges for Comparative Analysis (pp. 11-29).Search in Google Scholar

Küpper, B., Zick, A. & Rump, M. (2021). Rechtsextreme Einstellungen in der Mitte 2020/21 [Right-wing attitudes in the middle 2020/21]. In A. Zick and B. Küpper (Eds.), Die geforderte Mitte: Rechtsextreme und demokratiegefährdende Einstellungen in Deutschland 2020/21 [The required center: right-wing and democracy-threatening attitudes in Germany 2020/2021] (pp. 75-111). Dietz.Search in Google Scholar

Klausen, T. (2015). Tweeting the Jihad: Social Media Networks of Western Foreign Fighters in Syria and Iraq. Studies in Conflict & Terrorism, 38(1), 1-22. https://doi.org/10.1080/1057610X.2014.97494810.1080/1057610X.2014.974948Search in Google Scholar

Klausen, J., Marks, C. E. & Zaman, T. (2018). Finding Extremists in Online Social Networks. Operations Research 66(4), 957-976. https://doi.org/10.48550/arXiv.1610.06242Search in Google Scholar

Knipping-Sorokin, R. & Stumpf, T. (2018). Radikal Online: Das Internet und die Radikalisierung von Jugendlichen: eine Metaanalyse zum Forschungsfeld [Radical Online: The Internet and Youth Radicalization: A Meta-Analysis of the Research Field]. kommunikation@ gesellschaft, 1-29.Search in Google Scholar

Krieg, Y., Beckmann, L., & Kliem, S. (2018). Regionalanalyse Rechtsextremismus in Schleswig-Holstein 2018 [Regional Analysis of Right-Wing Extremism in Schleswig-Holstein 2018] (KFN-Research Reports, Vol. 149). Kriminologisches Forschungsinstitut Niedersachsen.Search in Google Scholar

Krieg, Y., Rook, L., Beckmann, L. & Kliem, S. (2022). Adolescents in Lower Saxony. Results of the Lower Saxony Survey 2019 (KFN-Research Reports, Vol. 165). Criminological Research Institute of Lower Saxony. Search in Google Scholar

Lafree, G., Jensen, M. A., James, P. A. & Safer-Lichtenstein, A. (2018). Correlates of Violent Political Extremism in the United States. Criminology, 56(2), 233-268. https://doi.org/10.1111/1745-9125.1216910.1111/1745-9125.12169Search in Google Scholar

Lehmann, L. & Jukschat, N. (2019). »Linksextremismus« ein problematisches Konzept für die Präventionsarbeit.: Perspektiven verschiedener Praxis-Akteure ["Left-wing extremism« a problematic concept for prevention work: perspectives from various practitioners]. SIAK Journal.Search in Google Scholar

Leimbach, K. (2017). Die (De-)Konstruktion eines extremistischen Weltbildes. Eine Mixed-Methods Analyse von Al-Qaidas Online Magazin »Inspire« [The (De-)Construction of an Extremist Worldview. A Mixed-Methods Analysis of Al-Qaeda's Online Magazine »Inspire"]. Journal for Deradicalization, 148-217.Search in Google Scholar

Meier, J., Bögelein, N. & Neubacher, F. (2022). A Biographical Perspective on Processes of Radicalisation. European Journal on Criminal Policy and Research, 28(2), 155-176. https://doi.org/10.1007/s10610-021-09498-z10.1007/s10610-021-09498-zSearch in Google Scholar

Mischler, A., Müller, P., Geng, B. & Harrendorf, S. (2019). Neue Wege in den Terrorismus? Deutungsmuster extremistischer Ideologien in Social Media [New Paths to Terrorism: Patterns of Interpretation of Extremist Ideologies in Social Media]. RW Rechtswissenschaft, 481-524.Search in Google Scholar

Moghaddam, F. M. (2005). The staircase to terrorism: a psychological exploration. The American psychologist, 60(2), 161-169.10.1037/0003-066X.60.2.161Search in Google Scholar

Muxel, A. (2020). Political Radicalism Among the Younger Generations. Youth and Globalization, 2(2), 123-136.10.1163/25895745-02020001Search in Google Scholar

Neumann, K. (2015). Zwischen NS-Propaganda und Facebook: Eine Analyse der Nutzung und Relevanz von Massenmedien und internen Medien innerhalb der rechtsextremen Szene in Deutschland [Between Nazi Propaganda and Facebook: An Analysis of the Use and Relevance of Mass Media and Internal Media within the Right-Wing Extremist Scene in Germany]. Journal EXIT-Deutschland. Zeitschrift für Deradikalisierung und demokratische Kultur, 71–90.Search in Google Scholar

Neumann, P. R. (2013). The Trouble with Radicalization. International Affairs, 89(4), 873-93. https://doi.org/10.1111/1468-2346.1204910.1111/1468-2346.12049Search in Google Scholar

Niemi, R. G., & Hepburn, M. A. (2010). The rebirth of political socialization. Perspectives on Political Science, 24(1), 7–16. https://doi.org/10.1080/10457097.1995.994186010.1080/10457097.1995.9941860Search in Google Scholar

Nisa, E.F. (2019). Internet and Muslim Women. In M. Woodward & R. Lukens-Bull (Eds), Handbook of Contemporary Islam and Muslim Lives. Springer, Cham. https://doi.org/10.1007/978-3-319-73653-2_71-110.1007/978-3-319-73653-2_71-1Search in Google Scholar

Nisa, E. F. (2013). The internet subculture of Indonesian face-veiled women. International Journal of Cultural Studies, 16(3), 241–255. https://doi.org/10.1177/136787791247453410.1177/1367877912474534Search in Google Scholar

Orav, A., Shreeves, R., & Radjenovic, A. (2018). Radicalisation and counter-radicalisation: A gender perspective. European Parliamentary Research Service.Search in Google Scholar

O’Malley, Roberta Liggett; Holt, Karen & Holt, Thomas J. (2020). An Exploration of the Involuntary Celibate (Incel) Subculture Online. Journal of Interpersonal Violence, 37(7-8), NP4981-NP5008. http://doi.org/10.1177/088626052095962510.1177/0886260520959625Search in Google Scholar

Pauwels, L. & Hardyns, W. (2018). Endorsement for Extremism, Exposure to Extremism via Social Media and Self-Reported Political/Religious Aggression. International Journal of Developmental Science 12, 51-69. https://doi.org/0.3233/DEV-17022910.3233/DEV-170229Search in Google Scholar

Pauwels, L. & Schils, N. (2016). Differential Online Exposure to Extremist Content and Political Violence: Testing the Relative Strength of Social Learning and Competing Perspectives. Terrorism and Political Violence, 28(1), 1-29. https://doi.org/10.1080/09546553.2013.87641410.1080/09546553.2013.876414Search in Google Scholar

Pauwels, L., Brion, F., Schils, N., Laffineur, J., Verhage, A., Ruyver, B. de & Easton, M. (2014). Explaining and understanding the role of exposure to new social media on violent extremism: an integrative quantitative and qualitative approach.Search in Google Scholar

Pauwels, L., & Waele, M. de (2014). Youth Involvement in Politically Motivated Violence: Why do social Integration, Perceived Legitimacy, and Perceived Discrimination Matter? International Journal of Conflict and Violence, 8(1), 134–153. https://doi.org/10.4119/ijcv-3050Search in Google Scholar

Pearson, E. (2015). The Case of Roshonara Choudhry: Implications for Theory on Online Radicalization, ISIS Women, and the Gendered Jihad. Policy & Internet, 8(1). 5-33. https://doi.org/10.1002/poi3.10110.1002/poi3.101Search in Google Scholar

Pelzer, B., Kaati, L., Cohen, K. & Fernquist, J. (2021). Toxic language in online incel communities. SN Soc Sci, 1, 213. http://doi.org/10.1007/s43545-021-00220-810.1007/s43545-021-00220-8Search in Google Scholar

Pfundmair, M., Paulus, M., & Wagner, E. (2020). Activism and radicalism in adolescence: an empirical test on age-related differences. Psychology, Crime & Law, 27(8), 815-830. https://doi.org/10.1080/1068316X.2020.185072510.1080/1068316X.2020.1850725Search in Google Scholar

Rekker, R., Keijsers, L., Branje, S., & Meeus, W. (2015). Political attitudes in adolescence and emerging adulthood: Developmental changes in mean level, polarization, rank-order stability, and correlates. Journal of adolescence, 41, 136-147. https://doi.org/10.1016/j.adolescence.2015.03.01110.1016/j.adolescence.2015.03.011Search in Google Scholar

Rieger, D., Frischlich, L., Bente, G. (2017). Propaganda in an insecure, unstructured world: How psychological uncertainty and authoritarian attitudes shape the evaluation of right-wing extremist internet propaganda. Journal for Deradicalization 19, 203-229.Search in Google Scholar

Sageman, M. (2008). Leaderless Jihad: Terror networks in the twenty-first century. University of Pennsylvania Press.10.9783/9780812206784Search in Google Scholar

Sanchez, S.E. (2014). The Internet and the Radicalization of Muslim Women.Search in Google Scholar

Schröder, C. P., Goede, L.-R. & Lehmann, L. (2020). Perspektiven von Studierenden. Ergebnisse einer Befragung zu den Themen Politik, Religion und Gemeinschaft im Rahmen des Projektes „Radikalisierung im digitalen Zeitalter (RadigZ)“ [Perspectives of university students: Results of a Survey on Politics, Religion, and Community as Part of the Project “Radicalization within the Digital Age (RadigZ)“]. (KFN-Research Reports, Vol. 156). Kriminologisches Forschungsinstitut Niedersachsen.Search in Google Scholar

Scrivens, R., Osuna, A. I., Chermak, S. M., Whitney, M. A. & Frank, R. (2021). Examining Online Indicators of Extremism in Violent Right-Wing Extremist Forums. Studies in Conflict & Terrorism.http://doi.org/10.1080/1057610X.2021.191381810.1080/1057610X.2021.1913818Search in Google Scholar

Scrivens, R., Wojciechowski, T. W., Freilich, J. D., Chermak, S. M. & Frank, R. (2021). Comparing the Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists. Terrorism and Political Violence.http://doi.org/10.1080/09546553.2021.189189310.37805/pn2021.21.remveSearch in Google Scholar

Sears, D. O. (1983). The persistence of early political predispositions: The roles of attitude object and life stage. In L. Wheeler & P. Shaver (Eds.), Review of Personality and Social Psychology (4th ed., pp. 79-116). SAGE Publications.Search in Google Scholar

Sears, D. O. (1990). Whither Political Socialization Research? The Question of Persistence. In O. Ichilov (ed.), Political Socialization, Citizenship Education, and Democracy (pp. 69-97). Teachers College PressSearch in Google Scholar

Struck, J. (2019). Digitale Vorwärtspanik.: Situative Dynamiken von gewalthaltigen Äußerungen gruppenbezogener Menschenfeindlichkeit auf digitalen Netzwerkplattformen [Digital forward panic: Situational dynamics of violent expressions of group-based misanthropy on digital network platforms]. Monatsschrift für Kriminologie und Strafrechtsreform/ Journal of Criminology an Penal Reform, 102, 54-64. http://doi.org/10.1515/mks-2019-000210.1515/mks-2019-0002Search in Google Scholar

Struck, J., Müller, P., Mischler, A. & Wagner, D. (2020). Volksverhetzung und Volksvernetzung: Eine analytische Einordnung rechtsextremistischer Onlinekommunikation [An Analytical Classification of Right-Wing Extremist Online Communication]. Kriminologie – Das Online-Journal, 310-337. https://doi.org/10.18716/ojs/krimoj/2020.2.12Search in Google Scholar

Sutherland, E. H. (1939). Principles of Criminology. Lippincott.Search in Google Scholar

Torney-Purta, J. (2004). Adolescents’ Political Socialization in Changing Contexts: An International Study in the Spirit of Nevitt Sanford. Political Psychology, 25(3), 465-478. http://dx.doi.org/10.1111/j.1467-9221.2004.00380.x10.1111/j.1467-9221.2004.00380.xSearch in Google Scholar

Watts, M. W. (1999). Are There Typical Age Curves in Political Behavior? The »Age Invariance« Hypothesis and Political Socialization. Political Psychology, 20(3), 477-499. https://doi.org/10.1111/0162-895X.0015310.1111/0162-895X.00153Search in Google Scholar

Wiktorowicz, Q. (2005). Radical Islam Rising: Muslim Extremism in the West. Rowman & Littlefield Publishers.Search in Google Scholar

Winter, C., Neumann, P., Meleagrou-Hitchens, A., Ranstorp, M., Vidino, L. & Fürst, J. (2020). Online extremism: Research trends in internet activism, radicalization, and counter-strategies. International Journal of Conflict and Violence, 14(2), 1-20. https://doi.org/10.4119/ijcv-3809Search in Google Scholar

Wolfowicz, M., Hasisi, B. & Weisburd, D. (2022). What are the effects of different elements of media on radicalization outcomes? A systematic review. Campbell Systematic Reviews, 18(2). https://doi.org/10.1002/cl2.124410.1002/cl2.1244Search in Google Scholar

Wolfowicz, M., Litmanovitz, Y., Weisburd, D., & Hasisi, B. (2020). A Field-Wide Systematic Review and Meta-analysis of Putative Risk and Protective Factors for Radicalization Outcomes. Journal of Quantitative Criminology, 36(3), 407-447. https://psycnet.apa.org/doi/10.1007/s10940-019-09439-410.1007/s10940-019-09439-4Search in Google Scholar

Wolfowicz, M., Litmanovitz, Y., Weisburd, D. & Hasisi, B. (2021). Cognitive and behavioral radicalization: A systematic review of the putative risk and protective factors. Campbell Systematic Reviews, 17(3). https://doi.org/10.1002/cl2.117410.1002/cl2.1174Search in Google Scholar

Appendix A. Measurement of extremist attitudes

Extremist attitudes

Islamist attitudes
Islamic rules of the Sharia are better than the German laws.
It’s a good thing that the Muslims living in the Middle East are building an Islamic state by war.
Peace is only succeeded by building an Islamic theocracy.
A religious leader is a better regime than a democracy.
I support people traveling to Syria to join IS.
IS fighters are not terrorists, but freedom fighters.
Right-wing extremism
In the national interest and under certain circumstances, a dictatorship is the best form of government.
We should have a leader who rules Germany with a strong hand for the good of all.
As in nature, the strongest should always prevail in society.
There are valuable and unworthy lives.
Without the Holocaust, Hitler would be considered a great statesman today.
National Socialism also had positive aspects.
When jobs become scarce, foreigners living in Germany should be sent back to their home countries.
Leftists need not be surprised when they are attacked.
You have to show the refugees, even with violence, that they are not welcome here.

Appendix B. Measurement of control variables

Control variables

General Internet use
How often do you use the Internet?
I have made new friends on the Internet.
I can no longer imagine life without the Internet.
I enjoy »liking« on the Internet.
I communicate a lot with friends via messenger (e.g., WhatsApp, Telegram).
I often check social media to see what’s new (e.g., Facebook, Instagram, Snapchat, Twitter).
Socioeconomic background
My family manages well with the money they have each month.
I can afford anything I want.
Compared to my friends, I have less money at my disposal. (Inverted)
Published Online: 2022-12-01
Published in Print: 2022-11-24

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 29.1.2023 from https://www.degruyter.com/document/doi/10.1515/mks-2022-0021/html
Scroll Up Arrow