The digital setting empowers users to actively engage in communicative actions. The problem is that this active communication can increase misjudgment in determining the facts around social issues. When this communication is integrated with partisan biases, the effects can be particularly detrimental. Our study tested whether active communication actions regarding social issues and different trust levels toward presidential administrations (Trump vs. Biden) would increase belief in conspiracy theories.
To examine this, the study used online survey datasets (Amazon Mechanical Turk, N = 1355) collected during July and August 2021 concerning three political issues: the Afghanistan issue, the Black Lives Matter issue, and the Voter Fraud issue.
The findings show that among participants with more active communication actions, the higher Trump government trust is and the lower Biden government trust is, the more belief in conspiracy theories increases. Interestingly, interaction effects of trust in government and active communicative actions were found among both Trump and Biden supporters.
Combined with preexisting efforts to tackle misinformation online, there are extensive efforts underway to educate laypeople about the dangers of misinformation. People must understand that any person could fall into belief in conspiracy theories if they do not carefully diagnose their information behaviors.
Our study can increase knowledge about people’s situational belief in conspiracy theories based on their political stance. The study can support future research, promoting a deeper understanding of belief in conspiracy theories.
Digital media facilitates the unconstrained spread of unverified conspiracy theories. There are many organizational- and institutional-level efforts to tackle the diffusion of conspiracy theories. Fact-check centers (e.g., politifact.com, factcheck.org, snopes.com), the academic community, and tech companies (e.g., Twitter, Meta) have developed systems and/or algorithms to promptly detect misinformation and take it down. However, do these efforts enable us to eliminate the fundamental problem that conspiracy theories create? To understand this problem, the present study tests the relationship between individuals’ trust in the Trump and Biden administrations and the extent to which they believe in conspiracy theories.
Fact-checking organizations attempt to verify whether conspiracy theories are false through a series of systemic research tools which analyze and compare the claims with the original sources with experts or advice groups (Ball and Amy 2020; Mantzarlis 2018). However, as this is human-based work, it is difficult to catch up with the quick electronic dissemination of conspiracy theories. The fact-checking process can only be done after conspiracy theories have spread, which necessitates an ad-hoc approach to solving the problem. Mantzarlis (2018) identified this fact-checking process as “ex-post, on claims of public relevance (p. 83).”
Academic efforts have shown tremendous productivity in identifying conspiracy theories dispersed through social media platforms (e.g., Manzoor & Jimmy Singla 2019; Shu et al. 2017, 2019). This approach is different from the post hoc approach of fact-checking, and gives some hope that we can be more effective in stopping misinformation before it spreads.
The main objective of academic research in detecting conspiracy theories is to find them before they spread through online channels. Mantzarlis (2018) categorized this approach as an “ex-ante” verification method that “seeks primary evidence” based on various tactics such as geolocation and reverse engineering (p. 88). There is much technical progress in understanding the structure of conspiracy theories and detecting their dispersion. Vosoughi et al. (2018) reported on the pattern of how false news spreads, and concluded that lies were disseminated much faster than the truth. They examined the velocity of dispersed rumors versus true news, and found that rumors reached 1000 and 10,000 people much faster than the true information.
In fact, people generally have low attention to the truthfulness of information (Craft et al. 2017). In determining truthfulness of facts, individual confirmation bias cannot be overcome by attempts to correct conspiracy theories or prevent the spread. For this reason, when a conspiratorial idea starts to grow online, it is not easily tackled nor completely removed by fact-checking (Ball and Amy 2020; Ransack 2017). As digital communication offers users unprecedented power to control the flow of information they consume, the authority of institutional endeavors cannot fully influence individuals’ decisions on whether information is true or false.
The difficulty is that it is human nature for individuals to want to confirm their beliefs. Therefore, people selectively seek information that is palatable to their preexisting thoughts or opinions. Thus, individuals are not prone to communications which fulfill the accuracy motivation (Chaiken et al. 1996). Instead, other motivations steer individuals’ information behaviors, prompting them to utilize heuristics, judgment shortcuts which essentially say that if the results are what the individual wants in the end, it does not matter if the facts along the way are true. These heuristics are highly dependent on preexisting beliefs, thoughts, and preferences.
Partisanship or political stance is a great cue for information selection. For example, according to a study by Lau and Redlawsk (2001), participants who were more politically knowledgeable and politically sophisticated used more five different political heuristics (e.g., party, candidates’ appearance) to evaluate candidates in elections. If you have firm background knowledge or beliefs, cues for assessing the problem are more accessible. This means that those who use heuristics to judge a situation would be biased at the beginning of information search or processing. In this sense, people’s active information behaviors can increase misgivings about “factful” information (Ball and Amy 2020; Craft et al. 2017). The positive relationship between active information behaviors and beliefs in conspiracy theories will be elaborated upon further in the Literature Review section.
The situational theory of problem solving (hereafter STOPS) (Kim et al. 2011) explains that communicative actions1 are determined by the level of situational motivation on the issues or problems. If people perceive that the issue is a problem (problem recognition) which violates the expectation, is personally relevant (involvement recognition), and has low obstacles to solve (constraint recognition), they are more motivated to solve their situational problems through communicative actions. Communicative actions have two dimensions: passive (reactive) and active (proactive). Those who are highly motivated to solve communicative problems will engage in both types of communicative actions. In this theory, communicative actions are the outcome variables of the intrapersonal problem-solving process. Communicative actions can promote or repress attitudes, beliefs, and behaviors. The current study raises a research question regarding the effects of active communicative actions on individuals’ ability to distinguish falsehoods from facts.
Many concerned voices have expressed the hazard of political polarization cracking the foundation of democracy (e.g., Hetherington et al. 2009; Layman et al. 2006). Partisan bias has been researched as a major factor in the deteriorating of perceived news media reports’ tones (e.g., Gunther and Schmidt 2004; Perloff 2015) and the majority of social opinions on the issues (e.g., Christen and Gunther 2003). However, increased digital selectivity in the last decades has posed an increasing threat to the common ground of knowledge. Widespread conspiracy theories are a major epistemological crisis today. The danger of misinformation at the societal level calls for more systemic, collaborative, and restrictive actions to combat it (Mitchell and Mason 2021).
Given this background, the current study examines the relationship between individuals’ trust toward two different governments (the Republican government led by President Donald Trump and the Democrat government led by President Joe Biden) and the extent to which they believe in conspiracy theories. The study used three major socio-political issues which created a large volume of conspiracy theories (i.e., Afghanistan, the Black Lives Matter movement, and Voter Fraud issues). More specifically, we test the relationship between trust levels toward two politically different administrations (Trump vs. Biden), active communicative actions, and the level of conspiratorial beliefs about the given political issues. The study also examines whether conspiracy beliefs flourish more when high trust toward a certain government meets active communicative actions.
2 Literature review
2.1 Beliefs in conspiracy theories and political stance
Douglas and Sutton (2008) defined conspiracy theories as “attempts to explain the ultimate cause of an event (usually one that is political or social) as a secret plot by a covert alliance of powerful individuals or organizations, rather than an overt activity or natural occurrence” (p. 211). In journalism studies, Konkes and Lester (2017) define conspiracy theory as “a speculative explanation for an event that involves elite individuals secretly colluding for their interests, rather than the public interest” (p. 827). Kim and Cao (2016) differentiate conspiracy theories from misinformation and rumors, noting that unlike misinformation, not all conspiracy theories are false, and that unlike rumors, they are not used to seek control or closure in uncertain situations. The core element of a conspiracy theory in definition is that “a group, or coalition, of powerful and evil-minded individuals” is involved in causing malevolent events in order to achieve a hidden goal (van et al. 2017, p. 324).
Therefore, conspiracy theories are often associated with political stance and political information consumption. People prefer to consume media outlets closer to their political beliefs and political ideology (i.e., selective exposure) (e.g., Stroud 2010). Political ideology determines how individuals identify issues and how political perceptions and attitudes resonate with them (Rathje 2018). Political ideology functions as an information filter for individuals’ beliefs (Pasek et al. 2015). It is closely related to the cognitive tendency to accept information that confirms one’s own ideas (i.e., confirmation bias) (e.g., Knobloch-Westerwick et al. 2015; Lerman and Daniel 2020) and to reject contradictory information unless the issue is closed to one’s political ideology (Lewandowsky et al. 2012; Pasek et al. 2015). In other words, confirmation bias with regards to political ideology makes people more likely to believe misinformation that supports what they want to believe and less likely to believe things that are true but opposed to their political ideology. The power of political ideology could have stronger repercussions when taking into account belief in conspiracy theories. Hollander (2018) found that political stance can affect belief in conspiracy theories, leading to substantial changes in attitudes towards health and safety policies that confirm political ideology. In terms of political ideology, Nyhan and Reifler (2010) concluded that partisanship presents barriers to correcting misinformation for this reason.
According to Pasek et al. (2015) study, partisanship and liberal/conservative self-identification were significantly associated with conspiracy beliefs about President Barack Obama’s birthplace, and they further found that conservatives had a stronger tendency to suspect the previous president’s origins. Pasek et al. (2015) work highlights that this relationship could also happen in the opposite direction, with liberals supporting conspiracies about conservative politicians. Moreover, Enders and Uscinski (2021b) further discussed that ideological extremity predicted belief in conspiracies when such conspiracies aligned with people’s partisan ideology, and the same people rejected nonpartisan conspiracy beliefs.
Scholars who study beliefs in political conspiratorial claims (e.g., Hollander 2018; Jardina and Traugott, 2019) show that they can be explained by both predisposition (e.g., personality) (e.g., Dagnall et al. 2015; Darwin et al. 2011; Douglas et al. 2016) and situational belief in conspiracy theories (Kim & Lee; Kim et al 2021). The dispositional element of belief in conspiracy theories might matter, but as anyone can be a victim of conspiracy theories, it is worth concentrating on situational belief in conspiracy theories. A political bias sometimes could be a stronger predictor of belief in political fake news and conspiracies than the predispositional tendency to believe in conspiracy theories (Faragó et al. 2019). Partisans easily, quickly, and consistently accuse groups in the opposition, or at least groups with ideas opposing the partisan ideology, of engaging in conspiracies (Smallpage et al. 2017).
Belief in conspiracy theories is often tightly linked to politics and targeted institutions (e.g., administrations, government agencies) because conspiracy theories often attack institutional power and knowledge. This can be worsened when there is a lack of trust in institutions and when there is fear and hatred toward minorities (Tam and Hyelim 2022). The COVID-19 pandemic provides a good example. In a recent study about COVID-19 and conspiracy beliefs, Republicans and conservatives, more than Democrats and liberals, tended to think the virus was spread deliberately. We believe this is due to fewer Democrat and liberal elites endorsing conspiracy theories on COVID-19 (Uscinski et al. 2020). Regarding the pandemic conspiracy, many studies maintain the importance of the public’s trust in public health institutions and governments as the main factor necessitating alleviation of belief in conspiracy theories on the COVID-19 virus and vaccines (e.g., Karić and Međedović 2021; Wirawan et al. 2021).
2.2 Politicized conspiracy theories
Belief in conspiracy theories can proliferate with more political polarization as conspiracy theories can be intentionally weaponized by political activists and politicians (Shahrezaye et al. 2021). Conflict among opposing groups provokes the spread and support of conspiracy theories being started or utilized by a partisan group (Smallpage et al. 2017). Political parties use conspiracy theories to undermine their political opposition and find support for their interests, smoothing their way to power (Hollander 2018; Moore 2018).
Politicians are more trusted than scientists in politically charged and polarized environments (Zaller 1992), enabling wider support of a conspiracy theory. When a party uses conspiracy theories, these theories tend to become more widespread and end up being a factor in decision-making and influencing policies. Since politicians promote accusations against their opponents, they contribute to boosting conspiracy theories and their followers’ support of such beliefs (Smallpage et al. 2017). These notions suggest that those who trust a political candidate or party will be more prone to believing conspiracy theories about their opponents.
President Donald Trump often used the frame of ‘fake news’ in his political rhetoric. He had publicly labeled media outlets, such as CNN, as ‘fake news media’ on his Twitter account (Silva 2017). He uploaded a wrestling video which depicted him attacking CNN on his Twitter account with the hashtag “#FraudNewsCNN.” As this example suggests, the fierce rivalry of political rhetoric between the liberal and conservative sides makes fake news a more legitimized form of communication simply by keeping the conversation alive. The scope of misinformation and fake news production extends to mainstream sources who are in many cases forced to contest them on air, which gives the false conspiracies legitimacy simply by virtue of being on the news. This degrades the credibility of the established institutions, which have been regarded as producing reliable information for a long time.
Since the Trump era, these trends of disregarding mainstream sources and giving more legitimacy to alternative sources have prevailed among right-wing conspiracists such as with QAnon (e.g., Roose 2021). As this conspiracy grew exponentially, cognitive polarization between the two political alignments was exacerbated, resulting in political protests such as the Capitol Attack and the Black Lives Matter movement. For example, the Capitol Attack broke out mainly because of distrust in the 2021 presidential election process. The attackers increased their doubts about the fairness or transparency of elections because Donald Trump persisted in attacking the legitimacy of the election process. This induced many conspiracy theories, including the so-called “voter fraud issue” in the language of conservatives, or the “Big Lie” according to liberals. Those who endorse the voter fraud conspiracy theories asserted without evidence that the election was manipulated in Joe Biden’s favor.
Given this background, 2021 was a time of extremely high uncertainty and instability. The pandemic was prolonged more than expected, and the country went through a political transition in a climate of extreme polarization. In this situation, the conspiracy theories spread through social media were a political weapon, especially among right-wing supporters. Hence, we suggest research to test whether people’s trust in two different governments enhances or mitigates belief in conspiracy theories on some major social issues. As the conspiracy theories attacking the liberal side were more popular in the time of the transition era between the Trump and Biden governments, the study only focused on anti-Biden conspiracy theories. The Republicans’ and conservatives’ dominance in conspiracy theories (so called “ideological asymmetry in conspiracy theories”) was considered among the main reasons to choose the anti-Biden conspiracy theories. Enders et al. (2022) recently found that the long-lasting belief in ideological asymmetry (e.g., Van der Linden et al. 2021), originated from Richard Hofstadter’s The Paranoid Style (1964), cannot be confirmed. However, as pointed out previously, the Trump administration is unique when it comes to amplifying conspiracy theories. Donald Trump actively used ‘conspiracies’ and ‘fake news’ for his campaigns, like any other populist leader making full use of anti-establishment sentiments, which is a core element of conspiracy theories (Enders and Uscinski 2021a). The period in which we conducted the survey was right after the Joe Biden won the election with a close result. The Trump regime’s populist and conspiracy-minded movement prevail still among half of American citizens, which is the main reason we selected anti-Biden conspiracy theories only.
Also, studies about conspiracy theories constantly maintain that people are vulnerable to conspiracy theories when there is a lack of information and authority (e.g., Kim et al. 2021), and institutional trust plays a pivotal role in lowering conspiracy belief (e.g., Miller et al. 2016; Saunders 2017). Tam and Lee also found that institutional trust determines a person’s belief regarding recent South Korean conspiracy theories. The study found that institutional trust showed more powerful effects than STEM education. The COVID-19 pandemic is also a great example as to why institutional trust is critical. The latest research regarding belief in COVID-19-related conspiracy theories show that when people have a high trust level of institutions, including government and health agencies, their conspiracy beliefs regarding the coronavirus were significantly lower (e.g., Jennings et al. 2021; Van der Linden et al. 2021). Given this background, the first hypotheses are as follows:
Those who trust the Trump government will believe more in anti-Biden conspiracy theories about political issues.
Those who trust the Biden government will believe less in anti-Biden conspiracy theories about political issues.
2.3 Active communicative actions and belief in conspiracy theories
In this study, we adopt STOPS (Kim et al. 2011) as a framework to understand information behaviors. According to STOPS, there are three levels of communicative action: acquisition, selection, and transmission. These three levels of communicative action can either be passive or active. Passive communicative actions corresponding to the three levels are: information attending (acquisition), information permitting (selection), and information sharing (transmission). On the other hand, active communicative actions are: information seeking (acquisition), information forefending (selection), and information forwarding (transmission). In STOPS, people are inclined to communicate to solve problems. Our question is, what is the effect of these communicative actions afterward? Does more communicative action produce more problematic consequences?
Recently, Kim et al. (2021) updated explanations about the current issue of conspiracy theories’ dispersion based on STOPS. There are two routes in the cognitive process mechanism: cognitive progression (forwarding reasoning) and cognitive retrogression (backward reasoning). Cognitive progression is based on evaluating evidence to reach a reasonable conclusion. In contrast, cognitive retrogression starts with the conclusion and looks for evidence to support it. The former has a “best solution” purpose and is open to “informed choice.” The latter has a “best justification (or fit)” purpose and is not flexible about “information choice.” Studies reveal that cognitive retrogression is a much risker method which can have the effect of building hard-shelled closed-mindedness or dogmatism.
The authors suggest that the worst cases of cognitive retrogression led to cognitive incapability. If people use their previous referent criterion to purposely select information, they end up with cognitive arrest where they do not feel it necessary to look for alternatives or counter facts to their own points of view. The status of cognitive arrest will increase epistemic conviction, which creates a causal looping chain and can lead to epistemic inertia.
The authors explained the model by suggesting ‘conspiratorial thinking’ as an example (in this paper, it is ‘belief in conspiracy theories’). When (1) there is a poor relationship of trust between the public and the organization, (2) someone has a conspiracy mindset and a situational belief in conspiracy theories, and (3) he/she has a relevant emotional experience about the issue (affective referent criterion), belief in conspiracy theories can follow the model of epistemic inertia. As the person launches their communicative process from their belief, information that they take (acquire), give (transmit), or select could be more biased. When people pursue cognitive retrogression, they are unable to get out of their own loops of information intake such as ‘deliberative enclaves’, ‘filter bubbles’, or ‘eco-chambers’ (e.g., Sunstein 2007). Thus, active communicative actions could increase individuals’ belief in conspiracy theories on a certain issue.
Also, belief in a conspiracy theory is related to distinctive ways of communicating values, morals, and feelings (Douglas et al. 2019). Communicative actions are a motivation to take part in conspiratorial discussions on social media (Shahrezaye et al. 2021). Because of the engagement with issues, people are more likely to seek information, participate in the conversation, be exposed to more conspiratorial information, and argue with other people. Social media facilitates the free spread of conspiracy theories, providing space and options for sharing fake news and misinformation (Zeng and Schafer 2021). Mahl et al. (2021) noted that “de-platformed” extremist accounts are behind the first fabrications of conspiracies. There are also new dark platforms (e.g., 8kun, Gab) in which like-minded extremist users gather and share misinformation, fostering the growth of false conspiracies (Zeng and Schager 2021). The other publics who engage in active communicative actions spread this wrongful information to others, making conspiracies spread.
There are several motivations for people to start and spread rumors in a world of uncertainty and anxiety, such as the need for self-esteem, which people fulfil online by trying to belong to a group, or to feel the power of a secret truth; yet in the case of conspiracy theories, fact-finding seems a low priority (DiFonzo 2018). In today’s digital world, we often find ourselves stuck in communicative echo chambers, where we are only communicating with other people who agree with us. If people lack trust in other sources or lack exposure to counter-arguments, or if there are elevated levels of uncertainty about issues, then information-seeking behaviors occur, albeit not in an accurate way (DiFonzo 2018). Therefore, ordinary people with active communicative actions regarding conspiracy issues sometimes enhance their conspiracy beliefs in a digital media setting.
Lastly, there is a fundamental mechanism in one’s belief in conspiracy theories. A belief in a conspiracy is determined by ‘motivated reasoning.’ Miller et al. (2016) argued that conspiracy endorsement should be considered as a motivated reasoning issue. The authors indicated that politically endorsing conspiracy theories can involve more motivation than any other context. Their explanation exactly echoes the rationale from STOPS. According to STOPS, people who recognize a problem more and perceive personal involvement will have more situational motivation about the problem. Situational motivation in STOPS predicts increased communication actions, which elevate active communication. Put another way, active communication behaviors imply that people already have a high level of situational motivation about an issue. Hence, the active communicator would be more likely to promote conspiracy beliefs as the outcome of a motivated reasoning process. For this reason, we postulate that:
H2. More active communicative actions lead to more belief in anti-Biden conspiracy theories regardless of preference in government.
The study further questions how active communicative actions could influence conspiracy beliefs if there are two different kinds of trust in governments. We built the research question to ask whether trust toward two governments will be moderated by active communicative actions in levels of belief in conspiracy theories.
RQ1. Is trust in the Trump and Biden governments moderated by active communicative actions in belief in anti-Biden conspiracy theories?
This study used recent debatable issues in the United States: The Black Lives Matter issue, the Voter Fraud issue, and the Afghanistan issue (in chronological order). These three issues increased partisan conflicts and are closely associated with conflicts between the two political ideology alignments. The Black Live Matters movement started in 2014, but reached a nationwide level of protest after video of George Floyd’s killing went viral in 2020. The Floyd case exacerbated race issues, especially regarding police violence. Support for BLM was more pronounced because the government leader at the time, Donald Trump, was perceived to have openly supported right-wing positions up to and including white supremacy. This claim is supported by Trump’s unsubstantiated attacks on Barrack Obama’s citizenship, his obsession with building a wall at the Mexican border, and his comment that all African leaders are in charge of shithole countries, implying that is what was in store for us with Obama as President.
The Voter Fraud issue is connected with the Capitol Attack of January 2021. Trump had been lying about the pervasiveness of voter fraud since the 2016 election, claiming Hillary Clinton’s vote count was inflated by voter fraud. Many people believe this was the beginning of Trump’s campaign to shake confidence in the election process. The pandemic led to increased mail-in voting, which Donald Trump falsely characterized as unreliable. And Trump invented stories or plucked anecdotes from social media describing all kinds of voter fraud, but no evidence has ever been found that the level of voter fraud was enough to change the results of the election. Those who firmly believed that the election was manipulated could legitimize their violent attacks on the Capitol, which caused the loss of several lives.
The Afghanistan issue is different from the first two issues. When the U.S. government withdrew troops after losing the war with the Taliban, the downward trend of the Biden approval rate was reinforced. Although many experts and Democrat pundits accused the previous administration’s diplomatic and security policy of failing, the public perception of Biden’s leadership was damaged by the Taliban insurgency, which gave ammunition for conservative supporters’ or Trump supporters’ conspiratorial accusations on the issue.
To examine the hypotheses, we collected Amazon Mechanical Turk (MTurk) data during July and August 2021 about three political issues inviting conspiratorial claims – the Afghanistan issue, the Black Lives Matter issue, and the Voter Fraud issue. The survey only collected information from respondents who are older than 18 years old, use English, and reside in the United States. We also recruited respondents whose HIT approval rate is higher than 97%, and the total approval count is over 1000. The respondents received $1.70 as a compensation. The total N was 1355. Of the participants, 47% were female (N = 638), and 53% were male (N = 717). The average age was about 41 years old, and more than 70% of respondents were white (N = 1039). More than a half of the participants answered that their highest level of education was higher than a Bachelor’s degree (77.1%, N = 1051).
All measures are administered with 5-Likert scales (1 = Strongly Disagree, 5 = Strongly Agree). Please find the descriptive statistics in Appendix 1 and the specific items used for variables in Appendix 2.
Trust Toward Two Different Governments. The study measured levels of trust in two different governments by modifying the items from Huang’s (2001) Organization-Public Relationship Assessment (OPRA) measures: Trust in the Trump Administration ( = 0.97) and Trust in the Biden Administration ( = 0.96), with six similar items. For example, Trump government trust was measured by the question “Sound principles guided the Trump administration’s behavior,” while Biden government trust was measured by the same question changing only the name: “Sound principles guided the Biden administration’s behavior.”
Belief in Conspiracy Theories. As mentioned earlier, there are more conspiracy theories against the Biden government and Democrats. Therefore, we only use conspiratorial arguments against the Biden government. Belief in conspiracy theories was measured by asking how much the respondents believed in the suggested conspiracy theories for three issues: the Afghanistan Issue used two items (r = 0.76) (e.g., I think President Joe Biden intentionally let Afghanistan fall to the Taliban as part of a scheme to bring in more refugees, to change the U.S. population and give Democrats permanent political control). The BLM Issue used three items ( = 0.93) (e.g., I think Black Lives Matter (BLM) vandalized businesses downtown, especially targeting white communities). The Voter Fraud issue used five items ( = 0.89) (e.g., I think Dominion voting machines changed or deleted votes for Trump). Those conspiracy theories were collected based on the list from snopes.com, one of the independent fact-checking organizations which debunk misinformation/fake news.
Active Communicative Actions. We adopted STOPS (Kim et al. 2011) to measure the active communicative actions. We operationalized the composite index for active communicative actions ( = 0.93) of the public (i.e., information seeking (four items, = 0.95), information forwarding (four items, = 0.96), and information forefending (four items, = 0.95)) based on the theory.
Control Variables. We controlled gender (female = 1, male = 0), race (white = 1, non-white = 0), education level, and age.
To examine two hypotheses and one research question, we conducted a multiple regression analysis using STATA 16.1. We created two separate models testing Trump government trust and Biden government trust. Unlike partisanship (party identification), trust toward government includes many factors such as capability, integrity, and credibility. Therefore, the test was conducted using two different models, including one of government trust.
Proposed that the level of trust in two different governments has a profound impact on conspiracy thinking about political issues. H1a predicted that higher Trump government trust increases belief in anti-Biden conspiracy theories. As H1a suggested, all three social issues showed that those who held more trust in the Trump government had a higher level of belief in conspiracy theories ( = 0.719 (Afghanistan), = 0.755 (BLM), = 0.786 (Voter fraud), ps < 0.001) (see Table 1). H1b predicted, in contrast, that higher Biden government trust will have a negative relationship with belief in conspiracy theories ( = −0.057, p < 0.05 (Afghanistan), = −0.268 (BLM), = −0.243 (Voter fraud), ps < 0.001) (see Table 2).
|Trump Gov. Trust||0.719b||(39.32)||0.755b||(41.05)||0.786b||(46.06)|
|Active communicative actions (ACA)||0.104b||(5.56)||0.064b||(3.40)||0.075b||(4.33)|
|Trump Gov. Trust x ACA||0.072b||(4.20)||0.039a||(2.28)||0.057b||(3.57)|
|Female = 1||−0.013||(−0.75)||−0.025||(−1.46)||−0.010||(−0.59)|
|White = 1||−0.009||(-0.52)||0.020||(1.15)||0.001||(0.07)|
Standardized beta coefficients; t-value in parentheses; ap < 0.05 ,bp < 0.001.
|Biden Gov. Trust||−0.057a||(−2.19)||−0.268c||(−9.43)||−0.243c||(−10.64)|
|Active communicative actions (ACA)||0.398c||(15.49)||0.382c||(13.77)||0.577c||(25.65)|
|Biden Gov. Trust x ACA||0.174c||(6.96)||0.216c||(8.51)||0.134c||(6.14)|
|Female = 1||−0.065b||(−2.59)||−0.106c||(−4.24)||−0.045a||(−2.03)|
|White = 1||0.044||(1.76)||0.042||(1.65)||0.028||(1.22)|
Standardized Beta Coefficients; t-value in parentheses; ap < 0.05 bp < 0.01 cp < 0.001.
Predicted that active communicative actions regarding the issues would enhance anti-Biden conspiracy thinking. This hypothesis did not particularize a partisan group in anticipating effects. The results show that the active communicative actions increased participants’ belief in conspiracy theories concerning the three issues. In the first model, including Trump government trust only, all the issues showed significant effects ( = 0.104 (Afghanistan), = 0.064 (BLM), and = 0.075 (Voter fraud), ps < 0.001) (see Table 1). The second model included Biden government trust only, and all three issues showed significant effects ( = 0.398 (Afghanistan), = 0.382 (BLM), and = 0.577 (Voter fraud), ps < 0.001) (see Table 2). Compared with the second model, the first model’s coefficients of active communicative actions were smaller, which means Trump government trust explains more variance of belief in conspiracy theories. On the other hand, the second model controlling Biden government trust supports the theory that active communicative actions regarding conspiracy issues can still increase belief in conspiracy theories.
The research question asked whether there is any interaction effect of government trust and active communicative actions on belief in conspiracy theories. Both models showed significant effects of interaction terms. In the first model, all three issues had significant coefficients ( = 0.072, p < 0.001 (Afghanistan), = 0.039 (BLM) p < 0.05, and = 0.057 (Voter fraud), p < 0.001). In addition, these patterns were similarly found in every issue ( = 0.174 (Afghanistan), = 0.216 (BLM), and = 0.134 (Voter fraud), ps < 0.001). However, the interpretation of this interaction should be substantially different.
The first model’s moderation effects explained that low Trump government trust was barely affected by changes in the level of active communicative actions. The noticeable effects were only found in the high trust groups. As the active communicative actions increased, the high Trump trust group increased their beliefs in conspiracy theories (see Figure 1). As the study only deals with conspiracy theories against the Biden government, Trump government support has more powerful effects on belief in conspiracy theories.
The second model’s significant interaction portrayed dissimilar cases. Unlike the first model, the active communicative actions’ effects were larger and differed based on the issues. The high Biden trust group started at the lowest point of belief in conspiracy theories, but as the level of active communicative actions grew, their belief in conspiracy theories quickly increased. The slope is much steeper as compared with the first model. Also, in the case of the Voter Fraud issue, the low and high trust group both increased their beliefs in conspiracy theories as active communicative actions increased. The first model did not show this pattern, where the low Trump trust group did not have any effects from active communicative actions for all three issues. However, the second model showed that the low Biden trust group increased their beliefs in conspiracy theories about the Voter Fraud issue while the high Trump trust group did (see Figure 2).
The study tried to illustrate the relationship between trust toward two different governments (Trump vs. Biden), active communicative actions, and belief in conspiracy theories. It found that trust in governments and active communicative actions play a significant role. Belief in conspiracy theories against the Biden government was associated with high Trump government trust and low Biden government trust. Additionally, if people were more engaged with active communicative actions, including information-seeking, -forefending, and -forwarding about these issues, they were more likely to believe the conspiracy scenarios. This pattern would seem too obvious, but interaction effect results depict a more intriguing picture.
The Trump supporters elevated their conspiracy thinking through active communication concerning the issues. As we mirror this trend to the opposite side, more support for the Biden government correlates with repression of belief in conspiracy theories. However, contrary to the common expectation, people who have a high support level for the Biden government increased their beliefs in conspiracy theories and anti-Biden arguments if they were communicatively active.
We think that those two types of supporters would operate with different mechanisms. As for the Trump supporters, they strengthened their belief in their preexisting conclusion on the issue through communicative actions. This case can be well explained by Kim et al. (2021) epistemic inertia model. Contrastingly, the reason Biden supporters increased their conspiracy thinking is more complicated. First, we can think about the Biden supporters’ practice of reasonable skepticism. In the past, some conspiracy theories turned out to be true after a while (e.g., Project MKUltra, Tuskegee syphilis experiment, Iran-Contra Affair). These conspiracy theories help people to critically think about situations and prevent them from having blind faith in their leaders. Second, we could also think of the possibility that a high-level supporter could accept two dimensions of belief in conspiracy theories. By actively seeking information related to the conspiratorial accusation, they believe that there could be some truth behind the theory.
We also found that there is a similar pattern although there are some differences in the nature of the issue: the Afghanistan issue is an international issue, but the other two issues (BLM and Voter Fraud) are domestic issues. Many political communication studies assert that American citizens are ignorant of foreign affairs (Thrall 2018) mainly due to the media eco-system. News organizations cover international affairs less than domestic affairs (Kohut and Robert 1995). The reasons can be demonstrated mainly in a twofold manner: First, foreign affairs are hard to cover for their high news-making cost (e.g., Utley 1997). News organizations and journalists must rely on more foreign resources like correspondent networks, or they are burdened with extra expenditures to send people out of the country for in-depth research. Second, news market consumers are not interested in foreign affairs (The Pew Research Center 2012; Reuter Institute 2012) because people believe that international events are ‘their’ issues rather than “our’ issues. Ownership of such issues essentially, therefore, is not given to ordinary people but to the states’ elites (Kohut and Robert 1995). On top of this, as already maintained in a series of studies, especially in America, governmental debates about foreign crises actually have much more impact on decisions than the movements of public opinions (Benett 1990; Groeling and Baum 2008). In sum, the smaller supplies and demands of foreign news inside the country makes the public less influential over the government’s decisions. These are common arguments in the TV news era as to why people are more ignorant of foreign affairs and policy concerning news media factors. This situation has been further aggravated with the introduction of the Internet. Some scholars indicate that online news users have shown less interest in international news (Reuter Institute 2012), and provision of international news on the internet is highly concentrated with a small number of global news agencies (Paterson 2007), so the Internet does not bring any groundbreaking alternation in producing and consuming foreign news at all.
It is also necessary to discuss whether this tendency will be ‘accelerated’ in this Internet-dominant time while news gets rapidly softened. This tendency is paralleled with the universal commercialization trend of news media (Hallin & Mancini 2004) regardless of its type. Today, as soft news prevails and hard news shrinks, the international coverage is a perfect target for cuts attempting to increase the efficiency of news production in business by eliminating time-consuming and expensive elements. As we previously observed in the TV news age, as people are more surrounded by a less deliberating communication environment, much smaller portions of the audience or only political elites would have steady interests in international news.
As discussed, digital communication could boost propagation of conspiracy theories about foreign affairs issues. However, this study did not show any substantial difference in terms of belief in conspiracy theories. This could be explained by two scenarios. First, the public’s indifference and selective consumption about the political-social issues are universal. Thus, effects do not differ by the type of issue. Second, the Afghanistan issue can be considered as a domestic issue because it impacts American politics and society directly. The American government does not have any control over the Afghanistan government and the country accepts refuges from Afghanistan wars. As prior studies have argued (Benett 1990; Groeling and Baum 2008), if an international issue has a domestic effect, people would have more motivation to selectively consume information about the issue.
5.1 Limitations and future studies
The study has several limitations. First, the data used in the present study cannot demonstrate exactly what motivated the high Biden trust group to develop higher belief in conspiracy theories through active communicative actions. In future research, it is necessary to employ anti-Trump conspiracy theories and test various issues. It also may be that only Trump affects the test cases in this way, which would result in a lower relevance to the Trump government in predicting future outcomes.
In addition, future work can include measurements referring to media literacy. When publics are knowledgeable about sources of information, specific formats that news sites utilize to provide stories, and aspects such as the inclusion of contrasting arguments, they can distinguish the professionalism behind the source of the information and be more skeptical in believing information provided by non-traditional news outlets and potential conspiracies (Craft et al. 2017). It would be interesting to compare the levels of media literacy of partisan publics in addition to their previous conspiratorial belief, and to segment publics based on their literacy level to test differences in conspiracy belief and communicative actions.
Second, this study only used one dataset obtained from Amazon MTurk. To increase the reliability of the findings, several studies using representative data or other methodologies would be necessary. As mentioned before, the dataset was collected in a climate of high uncertainty, political tensions, and polarization, with the recent Capitol Attack and consequent distrust. It would be interesting to re-conduct the study including recent issues which publics are familiar with, but in a less politically tense climate. While trust may not have returned to the levels prior to the Capitol Attack, the tension prevailing in the American society at the time the data was collected has diminished considerably. The reduction of tension may prime different communicative actions, which is worthy of study in order to understand publics and better predict their behaviors, given that political tension happens in a cyclical fashion (Rudolph and Evans 2005).
The current study could provide a better understanding of how ordinary people can situationally fall into belief in conspiracy theories when they are highly engaged with communicative actions. By integrating preexisting efforts tackling conspiracy theories, this study calls for the necessity to educate the people with the knowledge that anyone could fall into conspiracy beliefs if they do not carefully diagnose their information behaviors.
Additionally, many studies have paid attention to dispositional factors such as partisanship, but this study highlights the importance of situational conspiracy thinking (situational belief in conspiracy theories) and communicative factors to contribute to people’s conspiracy belief. It contributes theoretically to grasping the essential mechanism of conspiracy belief. In particular, the political conspiracy belief has been approached more through the lens of partisanship. This paper suggests that conspiracy belief can be explained by communicative factors, not only by partisanship. For those who are not partisan or politically sophisticated, belief in politico-social issues can be developed if they are situationally motivated and undertake active communication. Hence, to better understand belief in conspiracy theories, further discussion is required about how communicative actions induce or alleviate conspiracy thinking.
Efforts in reducing conspiracy thinking are critical for people to think more deeply about the different situations they face and prevent them from blindly following political leaders. Bringing the situational theory of problem solving (STOPS) and communicative actions together with conspiratorial thinking enables better understanding of the processes of conspiracy belief; moreover, it provides solutions to prevent such beliefs. Understanding different communicative actions and diagnosing behaviors enacted by publics, taking into account dispositional factors, are crucial elements for understanding the different steps that publics face when seeking information, sharing conspiracy-related information, and contributing to the expansion of conspiracies and blind faith in leaders.
|1. CT: Afghanistan||1|
|2. CT: BLM||0.770a||1|
|3. CT: Voter fraud||0.787a||0.795a||1|
|4. Trump trust||0.769a||0.782a||0.813a||1|
|5. Biden trust||0.081a||−0.131a||−0.120a||−0.148a||1|
|6. ACA: Afghanistan||0.384a||0.348a||0.366a||0.381a||0.230a||1|
|7. ACA: BLM||0.409a||0.249a||0.331a||0.305a||0.435a||0.705a||1|
|8. ACA: Vote||0.571a||0.483a||0.545a||0.540a||0.193a||0.696a||0.690a||1|
CT = Belief in conspiracy theories, ACA, active communicative actions; a p < 0.05.
Trust in the Trump Administration ( = 0.97).
Sound principles guided the Trump administration’s behavior
When the Trump administration made an important decision, people knew the government would consider the decision’s impact on members.
The Trump administration treated its publics fairly.
I feel positive about the direction in which the Trump administration was heading.
The Trump administration had the ability to accomplish what it said it will do.
The Trump administration could keep its promises to its publics.
Trust in the Biden Administration ( = 0.96).
Sound principles guides the Biden administration’s behavior.
When the Biden administration makes an important decision, people know the government will consider the decision’s impact on members.
The Biden administration treats its publics fairly.
I feel positive about the direction in which the Biden administration is heading.
The Biden administration has the ability to accomplish what it will do.
The Biden administration can keep its promises to its publics.
Belief in Conspiracy Theories about Afghanistan Issue (r = 0.76).
I think President Joe Biden intentionally let Afghanistan fall to the Taliban as part of a scheme to bring in more refugees, change the U.S. population and give Democrats permanent political control.
I think President Joe Biden when he was a vice president had SEAL Team 6 killed as part of a cover-up after a purportedly failed assassination of Osama bin Laden.
Belief in Conspiracy Theories about BLM Issue ( = 0.93).
I think Black Lives Matter (BLM) vandalized businesses in downtown, especially targeting white communities.
I think Black Lives Matter (BLM) movement and the left-wing anti-fascist movement Antifa are closely linked.
I think George Soros funded Black Lives Matter (BLM) movement to destroy the U.S.
Belief in Conspiracy Theories about Voter fraud Issue ( = 0.89).
I think Dominion voting machines changed or deleted votes for Trump.
I think Sharpie markers did not invalidate Trump votes in Arizona.
I think mail-in voting was rife with fraud.
I think poll watchers were blocked from observing.
I think there were thousands of votes by dead people or people voting multiple times.
Active Communicative Actions.
Note: The same items were measured separately for three different issues (i.e., Afghanistan, BLM, Voter Fraud).
Information Seeking ( = 0.95).
I often search for more information about this issue (Afghanistan/BLM/Voter Fraud Issue) on Internet.
I have searched for more information about this issue (Afghanistan/BLM/Voter Fraud Issue) on the websites or experts in the related industry.
I often search for news articles or blog postings related to this issue (Afghanistan/BLM/Voter Fraud Issue).
I have spent some time and effort to find information related to this issue (Afghanistan/BLM/Voter Fraud Issue).
Information Forwarding ( = 0.96).
I am willing to spare my time to discuss this issue (Afghanistan/BLM/Voter Fraud Issue) with someone I do not know well.
When there are opportunities, I explain this issue (Afghanistan/BLM/Voter Fraud Issue) to my family members and/or friends.
I (often) have conversations with people around me about this issue (Afghanistan/BLM/Voter Fraud Issue).
I look for chances to share my knowledge and thoughts about this issue (Afghanistan/BLM/Voter Fraud Issue).
Information Forefending ( = 0.95).
I have invested enough time and energy to understand this issue (Afghanistan/BLM/Voter Fraud Issue) so I can classify information quickly.
I can easily judge the value of information about this issue (Afghanistan/BLM/Voter Fraud Issue).
I know where to go when I need updated information regarding this issue (Afghanistan/BLM/Voter Fraud Issue).
I have a selection of trusted sources that I check for updates on this issue (Afghanistan/BLM/Voter Fraud Issue).
Ball, Philip & Maxmen Amy. 2020. The epic battle against coronavirus misinformation and conspiracy theories. Nature 581(7809). 371–375. https://doi.org/10.1038/d41586-020-01452-z.Search in Google Scholar
Bennett, W. Lance. 1990. Toward a theory of press-state relations in the United States. Journal of Communication 40(2). 103–125. https://doi.org/10.1111/j.1460-2466.1990.tb02265.x.Search in Google Scholar
Chaiken, Shelly, Roger Giner-Sorolla & Serena Chen. 1996. Beyond accuracy: Defense and impression motives in heuristic and systematic information processing. In Peter M. Gollwitzer, A. John Bargh (eds.), The psychology of action: Linking cognition and motivation to behavior, 553–578. New York City: The Guilford Press.Search in Google Scholar
Christen, Cindy T & Albert C. Gunther. 2003. The influence of mass media and other culprits on the projection of personal opinion. Communication Research 30(4). 414–431. https://doi.org/10.1177/0093650203253366.Search in Google Scholar
Craft, Stephanie, Seth Ashley & Maksl Adam. 2017. News media literacy and conspiracy theory endorsement. Communication and the Public 2(4). 388–401. https://doi.org/10.1177/2057047317725539.Search in Google Scholar
Dagnall, Neil, Kenneth Drinkwater, Andrew Parker, Andrew Denovan & Megan Parton. 2015. Conspiracy theory and cognitive style: A worldview. Frontiers in Psychology 6(FEB). 1–9. https://doi.org/10.3389/fpsyg.2015.00206.Search in Google Scholar
Darwin, Hannah, Nick Neave & Joni Holmes. 2011. Belief in conspiracy theories. The role of paranormal belief, paranoid ideation and schizotypy. Personality and Individual Differences 50(8). 1289–1293. https://doi.org/10.1016/j.paid.2011.02.027.Search in Google Scholar
Difonzo, Nicholas. 2018. Conspiracy rumor psychology. In Joseph E. Uscinski (ed.), Conspiracy theories and the people who believe them. Oxford: Oxford University Press.10.1093/oso/9780190844073.003.0017Search in Google Scholar
Douglas, Karen M. & Robbie M. Sutton. 2008. The hidden impact of conspiracy theories: Perceived and actual influence of theories surrounding the death of Princess Diana. The Journal of social psychology 148(2). 210–222.10.3200/SOCP.148.2.210-222Search in Google Scholar
Douglas, Karen M., Robbie M. Sutton, Mitchell J. Callan, Rael J. Dawtry & Annelie J. Harvey. 2016. Someone is pulling the strings: Hypersensitive agency detection and belief in conspiracy theories. Thinking & Reasoning 22(1). 57–77. https://doi.org/10.1080/13546783.2015.1051586.Search in Google Scholar
Douglas, Karen M., Joseph E. Uscinski, Aleksandra Cichocka, Turkay Nefes, Siang Ang Chee & Farzin Deravi. 2019. Understanding conspiracy theories. Political Psychology 40. 3–35. https://doi.org/10.1111/pops.12568.Search in Google Scholar
Enders, Adam, C. Farhart, J. Miller, J. Uscinski, K. Saunders & H. Drochon. 2022. Are Republicans and conservatives more likely to believe conspiracy theories? Political Behavior. 1–24. https://doi.org/10.1007/s11109-022-09812-3.Search in Google Scholar
Enders, Adam M. & Joseph E. Uscinski. 2021a. The role of anti-establishment orientations during the trump presidency. In The forum, Vol. 19, 47–76: De Gruyter.10.1515/for-2021-0003Search in Google Scholar
Enders, Adam M. & Joseph E. Uscinski. 2021b. Are misinformation, antiscientific claims, and conspiracy theories for political extremists? Group Processes & Intergroup Relations 24(4). 583–605. https://doi.org/10.1177/1368430220960805.Search in Google Scholar
Groeling, Tim & Matthew A. Baum. 2008. Crossing the water’s edge: Elite rhetoric, media coverage, and the rally-round-the-flag phenomenon. The Journal of Politics 70(4). 1065–1085. https://doi.org/10.1017/s0022381608081061.Search in Google Scholar
Gunther, Albert C. & Kathleen Schmitt. 2004. Mapping boundaries of the hostile media effect. Journal of Communication 54(1). 55–70. https://doi.org/10.1111/j.1460-2466.2004.tb02613.x.Search in Google Scholar
Hetherington, Marc J., Jonathan D. Weiler & Jonathan D. Weiler. 2009. Authoritarianism and polarization in American politics. Cambridge: Cambridge University Press.10.1017/CBO9780511802331Search in Google Scholar
Hofstadter, Richard. 1964. The paranoid style in American politics, 77–86. Newyork: Harper’s Magazine.Search in Google Scholar
Hollander, Barry A. 2018. Partisanship, individual differences, and news media exposure as predictors of conspiracy beliefs. Journalism & Mass Communication Quarterly 95(3). 691–713. https://doi.org/10.1177/1077699017728919.Search in Google Scholar
Huang, Yi-Hui. 2001. Opra: A cross-cultural, multiple-item scale for measuring organization-public relationships. Journal of Public Relations Research 13(1). 61–90. https://doi.org/10.1207/s1532754xjprr1301_4.Search in Google Scholar
Jardina, Ashley & Michael Traugott. 2019. The genesis of the birther rumor: Partisanship, racial attitudes, and political knowledge. Journal of Race, Ethnicity, and Politics 4(1). 60–80. https://doi.org/10.1017/rep.2018.25.Search in Google Scholar
Jennings, Will, Gerry Stoker, Hannah Bunting, Viktor Orri Valgarðsson, Jennifer Gaskell, Daniel Devin, Lawrence McKay & Melinda C. Mills. 2021. Lack of trust, conspiracy beliefs, and social media use predict COVID-19 vaccine hesitancy. Vaccines 9(6). 593.10.3390/vaccines9060593Search in Google Scholar
Karić, Tijana & Janko Međedović. 2021. Covid-19 conspiracy beliefs and containment-related behaviour: The role of political trust. Personality and Individual Differences 175. 110697. https://doi.org/10.1016/j.paid.2021.110697.Search in Google Scholar
Kim, Jeong-Nam & James E. Grunig. 2011. Problem solving and communicative action: A situational theory of problem solving. Journal of Communication 61(1). 120–149. https://doi.org/10.1111/j.1460-2466.2010.01529.x.Search in Google Scholar
Kim, Jeong-Nam & James E. Grunig. 2021. Lost in informational paradise: Cognitive arrest to epistemic inertia in problem solving. American Behavioral Scientist 65(2). 213–242. https://doi.org/10.1177/0002764219878237.Search in Google Scholar
Kim, Jeong-Nam, James E. Grunig & Lan Ni. 2010. Reconceptualizing the communicative action of publics: Acquisition, selection, and transmission of information in problematic situations. International Journal of Strategic Communication 4(2). 126–154.https://doi.org/10.1080/15531181003701913.Search in Google Scholar
Kim, Jeong-Nam & Seungyoon Lee. Conceptualizing conspiratorial thinking: An anatomy of public conspiracism for effective debiasing strategy. American Behavioral Scientist, in press.Search in Google Scholar
Kim, Minchul & Xiaoxia Cao. 2016. The impact of exposure to media messages promoting government conspiracy theories on distrust in the government : Evidence from a two-stage randomized experiment. International Journal of Communication 10. 3808–3827.Search in Google Scholar
Knobloch-Westerwick, Benjamin K. Johnson Silvia & Axel Westerwick. 2015. Confirmation bias in online searches: Impacts of selective exposure before an election on political attitude strength and shifts. Journal of Computer-Mediated Communication 20(2). 171–187. https://doi.org/10.1111/jcc4.12105.Search in Google Scholar
Kohut, Andrew & C. Toth Robert. 1995. A content analysis: International news coverage fits public’s ameri-centric mood. Pew Research Center for the People and the Press.Search in Google Scholar
Konkes, Claire & Libby Lester. 2017. Incomplete knowledge, rumour and truth seeking: When conspiracy theories become news. Journalism Studies 18(7). 826–844. https://doi.org/10.1080/1461670x.2015.1089182.Search in Google Scholar
Layman, Geoffrey C., Thomas M. Carsey & Juliana Horowitz. 2006. Party polarization in American politics: Characteristics, causes, and consequences. Annual Review of Political Science 9. 83–110. https://doi.org/10.1146/annurev.polisci.9.070204.105138.Search in Google Scholar
Lau, Richard R. & David P. Redlawsk. 2001. Advantages and disadvantages of cognitive heuristics in political decision making. American Journal of Political Science 45(4). 951–971. https://doi.org/10.2307/2669334.Search in Google Scholar
Lerman, Amy E. & Acland. Daniel. 2020. United in States of dissatisfaction: Confirmation bias across the partisan divide. American Politics Research 48(2). 227–237. https://doi.org/10.1177/1532673x18799274.Search in Google Scholar
Lewandowsky, Stephan, Ullrich K. H. Ecker, Colleen M. Seifert, Norbert Schwarz & John Cook. 2012. Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest 13(3). 106–131. https://doi.org/10.1177/1529100612451018.Search in Google Scholar
Mahl, Daniela, Jing Zeng & Mike S. Schäfer. 2021. From “Nasa Lies” to “Reptilian Eyes”: Mapping communication about 10 conspiracy theories, their communities, and main propagators on Twitter. Social Media+ Society 7(2). 20563051211017482. https://doi.org/10.1177/20563051211017482.Search in Google Scholar
Mantzarlis, Alexios. 2018. Fact-checking 101. In Cherilyn Ireton & Julie Posetti (eds.), Journalism, fake news & disinformation: Handbook for journalism Education and training, 81–95. Paris: UNESCO.Search in Google Scholar
Manzoor, Syed Ishfaq & Jimmy Singla. 2019. Fake news detection using machine learning approaches: A systematic review. In 2019 3rd international conference on trends in electronics and informatics (ICOEI), 230–234. Tirunelveli: IEEE.10.1109/ICOEI.2019.8862770Search in Google Scholar
Mitchell, Amy & Walker Mason. 2021. More Americans now say government should take steps to restrict false information online than in 2018. Washington, D.C.: The Pew Research Center.Search in Google Scholar
Miller, Joanne M., Kyle L. Saunders & Christina E. Farhart. 2016. Conspiracy endorsement as motivated reasoning: The moderating roles of political knowledge and trust. American Journal of Political Science 60(4). 824–844. https://doi.org/10.1111/ajps.12234.Search in Google Scholar
Nyhan, Brendan & Jason Reifler. 2010. When corrections fail: The persistence of political misperceptions. Political Behavior 32(2). 303–330. https://doi.org/10.1007/s11109-010-9112-2.Search in Google Scholar
Pasek, Josh, Tobias H. Stark, Jon A. Krosnick & Trevor Tompson. 2015. What motivates a conspiracy theory? Birther beliefs, partisanship, liberal-conservative ideology, and anti-black attitudes. Electoral Studies 40. 482–489. https://doi.org/10.1016/j.electstud.2014.09.009.Search in Google Scholar
Paterson, Chris. 2007. International news on the internet: Why more is less. Ethical space: The. International Journal of Communication Ethics 4(1/2). 57–66.Search in Google Scholar
Rathje, Steve. 2018. Why people ignore facts. Psychology Today. Available at: https://www.psychologytoday.com/us/blog/words-matter/201810/why-people-ignore-facts.Search in Google Scholar
Ransack, Brian. 2017. The science behind why fake news is so hard to wipe out. VOX. Available at: https://www.vox.com/science-and-health/2017/10/5/16410912/illusory-truth-fake-news-las-vegas-google-facebook.Search in Google Scholar
Roose, Kevin. 2021. What is QAnon, the viral pro-trump conspiracy theory? The New York times. Available at: https://www.nytimes.com/article/what-is-qanon.html.Search in Google Scholar
Rudolph, Thomas J. & Jillian Evans. 2005. Political trust, ideology, and public support for government spending. American Journal of Political Science 49(3). 660–671. https://doi.org/10.1111/j.1540-5907.2005.00148.x.Search in Google Scholar
Saunders, Kyle L. 2017. The impact of elite frames and motivated reasoning on beliefs in a global warming conspiracy: The promise and limits of trust. Research & Politics 4(3). 2053168017717602. https://doi.org/10.1177/2053168017717602.Search in Google Scholar
Shahrezaye, Morteza, Miriam Meckel, Léa Steinacker & Viktor Suter. 2021. COVID-19’s (mis) information ecosystem on Twitter: How partisanship boosts the spread of conspiracy narratives on German speaking Twitter. In Future of Information and communication conference, p. 1060–1073. Cham: Springer.10.1007/978-3-030-73100-7_73Search in Google Scholar
Shu, Kai, Sliva Amy, Suhang Wang, Jiliang Tang & Huan Liu. 2017. Fake news detection on social media: A data mining perspective. ACM SIGKDD explorations newsletter 19(1). 22–36. https://doi.org/10.1145/3137597.3137600.Search in Google Scholar
Shu, Kai, Suhang Wang & Huan Liu. 2019. Beyond news contents: The role of social context for fake news detection. In Proceedings of the twelfth ACM international conference on web search and data mining, p. 312–320.10.1145/3289600.3290994Search in Google Scholar
Silva, Daniella. 2017. President Trump tweets wrestling Video of himself attacking ’CNN’. NBC News. Available at: https://www.nbcnews.com/politics/donald-trump/president-trump-tweets-wwe-video-himself-attacking-cnn-n779031.Search in Google Scholar
Smallpage, Steven M., Adam M. Enders & Joseph E. Uscinski. 2017. The partisan contours of conspiracy theory beliefs. Research & Politics 4(4). 2053168017746554. https://doi.org/10.1177/2053168017746554.Search in Google Scholar
Sunstein, Cass. R. 2007. Republic.com 2.0. Princeton: Princeton University Press.Search in Google Scholar
Tam, Lisa & Hyelim Lee. 2022. From conspiracy orientation to conspiracy attribution: The effects of institutional Trust and demographic differences. American Behavioral Scientist, in press.Search in Google Scholar
The Pew Research Center. 2012. Interest in foreign news declines. Available at: https://www.pewresearch.org/politics/2012/06/06/interest-in-foreign-news-declines/.Search in Google Scholar
Thrall, Trevor. 2018. America’s foreign policy attention deficit. CATO Institute. Available at: https://www.cato.org/blog/americas-foreign-policy-attention-deficit.Search in Google Scholar
Uscinski, Joseph E., Adam M. Enders, Casey Klofstad, Michelle Seelig, John Funchion, Caleb Everett, Stefan Wuchty, Kamal Premaratne & Manohar Murthi. 2020. Why do people believe COVID-19 conspiracy theories? Harvard Kennedy School Misinformation Review 1(3).10.37016/mr-2020-015Search in Google Scholar
Van der Linden, Sander, Costas Panagopoulos, Flávio Azevedo & John T. Jost. 2021. The paranoid style in American politics revisited: An ideological asymmetry in conspiratorial thinking. Political Psychology 42(1). 23–51. https://doi.org/10.1111/pops.12681.Search in Google Scholar
Van, Prooijen & Jan Willem, M. Karen Douglas. 2017. Conspiracy theories as part of history: The role of societal crisis situations. Memory Studies 10(3). 323–333. https://doi.org/10.1177/1750698017701615.Search in Google Scholar
Wirawan, Gede Benny Setia, Putu Nandika Tungga Yudanti Mahardani, Made Ratna Komala Cahyani, Ni Luh Prema Shantika Putri Laksmi & Pande Putu Januraga. 2021. Conspiracy beliefs and trust as determinants of COVID-19 vaccine acceptance in Bali, Indonesia: Cross-sectional study. Personality and Individual Differences 180. 110995. https://doi.org/10.1016/j.paid.2021.110995.Search in Google Scholar
Zeng, Jing & Mike S. Schäfer. 2021. Conceptualizing “dark platforms”. Covid-19-Related conspiracy theories on 8kun and gab. Digital Journalism 9(9). 1321–1343. https://doi.org/10.1080/21670811.2021.1938165.Search in Google Scholar
© 2022 the author(s), published by De Gruyter, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.