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BY 4.0 license Open Access Published by De Gruyter Mouton February 14, 2022

Journalistic Practices on Twitter: A Comparative Visual Study on the Personalization of Conflict Reporting on Social Media

Shahira S. Fahmy, Basma Mostafa Taha and Hasan Karademir

Abstract

Purpose

Using a mixed-method approach, this comparative study unpacks the way journalists personalized the controversial Yemen Civil War by examining the patterns of visual framing on Twitter. It further explores the influence of the individual level factor (home country or foreign identity of the journalist) and organizational level factor (countries affiliated with news organizations directly or indirectly involved in the conflict), on images shared on the Twitter platform.

Design/methodology/approach

A content analysis and a semiotic analysis of 2880 image tweets were used to investigate the different visual narratives related to the conflict and the extent of personalized journalism on Twitter.

Findings

The content analysis showed that while journalists offered some personalized reporting, by and large, they preferred to adopt a neutral stance when reporting the conflict. The semiotic analysis complemented the findings and identified more broadly that the image tweets analyzed emphasized the classic war-as-a-tragedy narrative, while at the same time shedding some light on the political conflict.

Practical implications

Researchers are given guidance into journalistic practices on social media and a deeper understanding of the extent and role of personalized journalism of conflict on Twitter.

Social implications

This study captured the fluctuating role of journalists on Twitter. Journalists occasionally fluctuated in their visual roles between being neutral observers and moral agents. These fluctuations were likely influenced by an array of factors, including the journalist’s home country or foreign identity and the country affiliation of news organizations they were working for.

Originality/value

This is the first study to show that journalists from different backgrounds have remained somehow obliged to carry on with their journalistic roles on Twitter. It also sheds light on different levels of influences on personalized war coverage on social media and extend the hierarchy of influence model (Shoemaker, Pamela & Stephen Reese. 1996. Mediating the Message; Theories of influence on mass media content. New York: Longman) in the context of personalized reporting on Twitter. It thus adds to the growing body of knowledge on how this model plays out in an online-first era, especially in non-western contexts.

1 Introduction

Since Yemen’s civil war broke out in 2015, the world has witnessed one of the worst humanitarian crises of the 21st century. In October 2018, the United Nations reported more than 13 million people facing starvation, making it the worst global famine in recent history (Guerin 2018). By 2019, the conflict had killed over 100,000 people, including more than 12,000 civilians (see Magdy 2019).

The Yemen conflict has been described as a civil local conflict that turned into a proxy war between two broad coalitions led by Saudi Arabia and Iran (Al Iriani et al. 2021). The beginning of Yemen’s civil war can be traced back to 2014 when Houthi rebels (a group of Shia rebels supported by Iran) took hold of Sanaa, Yemen’s capital. Alarmed by rising Shiite power in Yemen, Saudi Arabia and several other Gulf states sent airstrikes with the aim of attacking the Houthis and resisting the Iranian influence in Yemen (Yemen crisis 2020). They supported the ousted Sunni president and the Iranians supported the Shiite Houthis (Salisbury 2015). The United States supported the Saudi-led coalition against the Houthis and, consequently, against Iranian influence in Yemen (Mclaughlin and Martinez 2016). It provided the Saudi-led coalition with weapons sales, intelligence, and air-refueling support (Mclaughlin and Martinez 2016).[1] Qatar was also part of the Saudi-led coalition at the beginning of the Yemen conflict in 2014; however in June 2017, a diplomatic dispute broke out between Qatar and several other Arab countries (Baabood and Baabood 2020). Qatar was consequently excluded from the coalition and later shifted its position from being actively involved in military operations to supporting a peaceful settlement of the conflict.

Meanwhile, journalists worldwide actively used Twitter to report on the conflict. Unlike traditional journalism, journalistic practices on social media are said to be less formal and more personal (e.g., Lasorsa et al. 2012; Pantti 2019). A rather unexplored area of research deals with the different visual narratives and personalized reporting that journalists from diverse backgrounds offer on social media. Past literature demonstrates that journalistic content is affected by a hierarchy of influences, including individual, social, political, and cultural climates (Shoemaker and Reese 1996). In this comparative study, we analyze the visual tweets in the personal accounts of journalists to explore the extent of personalization that has occurred in visual reporting of the conflict on the Twitter platform and to explore influential factors that might have influenced the visual coverage on social media. The term personalized reporting has been adopted from Pantti’s study (2019), who described it as a form of reporting that allows “for more opinion and displays of emotion” (p. 126). Traditionally, the expression of emotion and opinion has been considered a deviation from journalistic standards. On platforms such as Twitter, however, Pantti explains that sharing personalized content reveals the journalist’s human side and can thus increase audience engagement.

Visuals play a critical role in shaping public opinion, specifically, during military operations (Fahmy et al. 2014). In recent years social media has continuously provided an incredible amount of visual information about the conflict and daily life in Yemen (Noman et al. 2018). Using a mixed-method approach, we unpack the way journalists personalized the conflict on Twitter by examining the patterns of visual framing. We further explore influencing factors, including the individual level factor (home country or foreign identity of the journalist) and organizational level factor (countries affiliated with news organizations directly or indirectly involved in the conflict), on images shared on Twitter.

Specifically, we analyze the visual tweets of 13 journalists from different countries, who work with news organizations associated with four countries involved in the conflict: Saudi Arabia, Iran, the United States, and Qatar. Our analysis of twitter images shared by journalists from different nationalities and organizational backgrounds is critical for several reasons. First, image tweets play a fast-growing part in overall tweets (Chen et al. 2013). Second, the literature illustrates the critical role of Twitter for news organizations and journalists in reporting, analyzing, commenting, and creating personal brands (Brems et al. 2016; Bruns 2012; García de Torres and Hermida 2016; Hedman 2017). Clearly, the influence of journalists and their personal and emotional perspectives on social media has been gradually increasing. Visual tweets are one of the primary means of reporting a conflict and in eliciting certain ideas about it (see Pantti 2019). The value of our study lies in examining micro-and macro-level factors on the types of visual content journalists share on Twitter. We do not look at the news organizations’ official pages, but rather the personal accounts of journalists, and hence we incorporate the concept of personalized reporting in light of the hierarchy of influence model. We, therefore, add to the growing body of knowledge on how this model plays out in an online-first era, especially in non-western contexts.

2 Background: The Yemen Civil War

Following the Arab Spring uprising in Yemen in 2011, then-authoritarian president Ali Abdullah Saleh was forced to hand over power to Abdrabbuh Mansour Hadi (Yemen crisis 2020). As the new president struggled with several problems in his country, the Houthi movement – one that belongs to Yemen’s Shia community – took advantage of the political turbulence. The Houthis led a series of rebellions and gained control over some parts of Yemen, and by March 2015, the newly appointed President Hadi had fled the country (Sharp 2019).

Concerns regarding the Houthis’ Shia background – which was believed to be financially and militarily backed by Iran – propelled Saudi Arabia and other Sunni Arab states to form a Saudi-led coalition to militarily intervene against the Houthis, put an end to Iran’s influence in Yemen, and restore President Hadi’s control (Wintour 2019). This Saudi-led coalition received support from Western countries, including the United States.[2] Western and Yemeni officials accused Iran of providing financial, logistical, and military support to the Houthis (Salisbury 2015).

The current conflict in Yemen therefore, can be described in terms of two sides: the Houthis (backed by Iran) and anti-Houthi forces (backed by Saudi Arabia, other Arab states, and the West) (International Crisis Group 2018). At the onset of the conflict, Qatar was also part of the Saudi-led coalition until a diplomatic disagreement between Doha, on one hand, and Riyadh and Abu Dhabi, on the other hand, ended Qatar’s intervention in Yemen (Gasim 2018; Perlo-Freeman 2018). Qatar’s position then shifted from actively participating in the Saudi-led military intervention in Yemen to a neutral mediator, seeking a peaceful settlement of the Yemen conflict while providing humanitarian support (Baabood and Baabood 2020). The United States supported Saudi Arabia’s military intervention in Yemen since the onset of the conflict, providing the Saudis with weapons as well as intelligence and air-refueling support (Mclaughlin and Martinez 2016). A longtime ally of Saudi Arabia, the U.S. government was alarmed by both growing Iranian influence in the region and the susceptibility of the conflict-torn region to turn into a hotbed of terrorist activities (Salisbury 2015).[3] Nevertheless, the US involvement in the conflict was not unanimously supported by all political actors. In 2019, the congress passed a resolution to end US involvement in the war in Yemen. President Donald Trump, however, vetoed the resolution, describing it as an “unnecessary, dangerous attempt” that could possibly endanger the lives of “American citizens and … service members” (Trump Vetoes Congressional Resolution to End U.S. Involvement in Yemen War 2019, para. 2).

In Yemen, reporting on the ongoing civil war represented a challenge for journalists (Sayed 2019). Several organizations such as the Freedom House (2019) and the Media Freedom Observatory in Yemen (The report of violation against 2018 2018) recorded violations against journalists, including murder, kidnapping, torture, and assault. Under these circumstances, several international news bureaus were forced to downsize and consequently fewer international correspondents reported the conflict from Yemen. Most international journalists and news organizations felt obliged to rely on local journalists, including freelancers, local news organizations, and citizen journalists in Yemen (Sinjab 2017), making Twitter a key source for journalists to get news and information regarding the conflict on the ground.

Twitter has been an invaluable source of news about conflicts, for both journalists and audiences (Bennett 2011). The practice of relying on citizen journalists, has become widely popularized following the proliferation of image-capturing technologies (Ferrucci et al. 2020). Social media platforms have proven to be equally useful in the protests against the tight control of authoritarian regimes in Ukraine (Ronzhyn 2014), Turkey (Tüfekçi 2017), as well as during the Arab Spring (Bossio 2014). In Yemen, the warring parties blocked websites that framed the conflict in ways contradictory to their own (see Noman et al. 2018). Online filters, however, could not block social media platforms, on which users capitalized to post and reshare banned and/or restricted content. Local journalists and activists in Yemen resorted to Twitter to share their opinions as well as images and videos of the conflict on the platform’s more open ecosystem, thus bypassing local filters and gatekeeping (Noman et al. 2018).

3 Personalized Journalism on Twitter

Social media platforms have enabled users to blend their professional and personal experiences, as well as their public and private selves (Papacharissi 2012). Traditionally, news reporting focused on facts and objective representations of reality, but reporting on social media, such as Twitter, has allowed for a personalized style of reporting (Pantti 2019).

Producing and distributing content on Twitter has been known to be driven by social media logic (Hedman 2016); one that stresses subjectivity and the expression of emotion to generate user engagement. Individual journalists can gain more visibility on Twitter by displaying their personalities and emotional stances rather than their institutional roles (Bruns 2012). Several scholars previously referred to the role of Twitter in shifting journalistic norms and practices with different terms, such as ambient journalism (Hermida 2010), Twitter-journalists (i.e., Barnard 2014), personalized tweeting (i.e., Canter 2015), and personalized reporting (i.e., Pantti 2019). Further, research focusing on personalized journalism examined journalists’ activities on Twitter by mainly focusing on textual content (i.e., Lasorsa 2012). Scant literature exists on how personalized journalism is implemented through visuals on the digital platform (i.e., Pantti 2019).

In examining the personalization of visual journalism on Twitter, Pantti (2019) analyzed the Twitter images shared by journalists reporting on the Ukraine conflict and explored whether the digital platform enabled them to use a more personal voice in comparison to traditional media practices. Following a qualitative analysis, the researcher identified several key themes in the image tweets (armed conflict, international politics, information warfare, the violence of conflict, everyday life, and journalistic work) and several emotional domains (neutral, tragic, critical, ironic, and comical). Results showed that while journalists attempted to maintain a level of professionalism, they often resorted to irony, which has traditionally been a way of expressing a subjective voice. Critical visual tweets were often shared by the journalists to express the revulsion they felt at the humanitarian cost of the conflict. The journalists did post their own photos on Twitter, that is, pictures that they themselves captured, wherein they demonstrated reactions and provided interpretations to newsworthy events. Pantti observed they refrained from sharing images that include death or injury and have themselves become visual gatekeepers. Unlike traditional war reporting, they chose not to share gory images and instead resorted to including links to the images and providing textual descriptions. Pantti maintained that the decision made by the journalists not to post graphic images contributed to the demonstration of the journalist’s self and the personalized style of reporting on Twitter.

Overall then, recent developments focusing on social media’s impact on contemporary journalism suggests journalistic practices on Twitter have generally been less bound by traditional news values, as journalists have the chance to report from a more personal or emotional standpoint. To a certain extent, Twitter has enabled each individual journalist to exercise their personal judgment when selecting images in a way that differs from what is traditionally considered purely professional.

4 Influences on News

Journalists do not operate in a vacuum, but rather they base their decisions on a myriad of internal and external factors. Shoemaker and Reese (1996) developed a five-level model that suggests the influence of both macro- and micro-level forces on news content. These levels include the individual level, media routines level, organizational level, extra-media level, and ideological level forces. Their model is hierarchical and suggests that each level has its own range of influence but is also influenced by higher-level factors. For example, the journalists’ professional roles or norms (individual level) stems from newsroom socialization (media routines level) that operate within organizational needs (organizational level) (see Shoemaker and Reese 1996, 2014). News values and journalistic norms are therefore, often the result of an array of influences that are heavily reliant on the local context, including social, political, and cultural climates (Fahmy and Johnson 2005; Pintak 2013).

More recently, Reese and Shoemaker (2016) have argued that the Internet has facilitated the existence and growth of news and social media platforms, yet individual newsmakers continue to make decisions about the inclusion/exclusion of specific news—just in a different sequence. Journalists are expected to produce content at a more rapid pace—given the fast-flow nature of online environments—and are generally required to multitask. They can also now have an online presence that is independent of their employers, such as creating a personal brand on their social media accounts. The authors explain that the routines level of influence in news media has also been influenced by the rules of the digital culture. Journalists today can monitor the process of news consumption in real time, allowing them to understand the exact type of content that is popular among their audiences, that is, the type of content that is more likely to be shared and thus become a trend. While previously “news values and occupational norms” have been considered part of the routines level of influence, technology has indirectly introduced new values (p. 400). In that sense, it has become imperative to include content that allows greater user participation and drives audience traffic. As for the organizational level, the authors mentioned that news production has become more diffused, as more journalists choose to work and communicate remotely. So instead of focusing on a single location for a specific news organization, understanding the organizational level of influence mandates selecting the most critical actors in the news production process, even if they are dispersed across small organizations “loosely aligned with a larger parent company” (p. 401). The fourth level of influence—previously called extra-media—has come to be known as the social institutions level of influence. This includes all organizational/institutional sources of influence apart from the media organization itself, including, but not limited to audiences, powerful sources, or public relations. Media organizations operate within a larger system with other significant players including the state and advertisers. Finally, the most macro-level—the social system level of analysis—examines how the media operate within a larger national system. Despite the fact that this model is arranged hierarchically, the authors explain, this does not mean that power flows in a single direction, as decisions are often made in an interactive and multidirectional manner.

What we also know is that journalists operating in different parts of the world exhibit several differences regarding how they perform their jobs, what ethical practices they consider acceptable, and how they view their professional roles, with the majority of such differences reflecting societal influences (Weaver and Willnat 2012; Willnat et al. 2013). While previous scholars have argued that journalists’ adherence to the truth is a universal value that can be found in newsrooms all over the world (Callahan 2003), a growing body of literature has provided a counterargument, which posits that a global, borderless culture of journalism is an elusive concept (Pintak 2013).

Journalism scholars identified certain overarching objectives in the practice of journalism that have transcended borders (Hanitzsch et al. 2010), but more recent evidence highlighted strong nation-dependent differences among international journalists (Weaver and Willnat 2012; Willnat et al. 2013). It has also been suggested that journalistic values and norms are often interpreted in light of local social, political, and cultural contexts (Deuze 2005; Jiang et al. 2021). Moreover, even within countries that share a plethora of similarities—such as Western countries—scholars have reported substantial diversity in how journalists perceive their professional roles (Patterson and Donsbach 1996; Weaver 1998), their understanding of well-established news values, such as objectivity (Donsbach and Klett 1993), and how they view the role of social media in affecting gatekeeping decisions (Chattopadhyay 2018; Tenenboim 2017).

Generally, the media are supposed to objectively reflect the different sides of a specific story; however, they are also expected to respect the values and sensibilities of their target audiences (El-Nawawy and Iskandar 2002). In this sense, the media assign importance to events and people through framing news, while such framing is also shaped by public views. In the context of war reporting, Hoxha and Hanitzsch’s (2018) study concludes that journalists are not merely reporting factual accounts of what happened, but often adopt different narratives to share their own versions of the stories about these conflicts. The media can choose to rally behind the country’s national flag in times of crises, even in democratic states where the press is expected—and often encouraged—to adopt complete impartiality (Gasim 2018).

In sum, there has been a considerable amount of studies published on the external and internal factors that influence news judgments and ethical decisions in war coverage (i.e., Fahmy and Johnson 2005). Most recently, research has also suggested a personalized style of visual reporting on social media during conflict (Pantti 2019). Some scholars have also found that sharing merely factual tweets on Twitter was less likely to result in high audience engagement in comparison to tweets that include journalists’ opinions (Chattopadhyay and Chattopadhyay 2021).

The Yemen Civil War has been perceived as a proxy war waged among multiple powers competing for geopolitical, economic, and sectarian power. Here we specifically examine the impact of the individual level and thee organizational level influences on personalizing the visual narrative of the conflict on Twitter. For the individual level, we specifically look at the home country or foreign identity of the journalist (Yemeni vs. non-Yemeni). We concluded that differentiating between domestic and foreign journalists was important as Yemenis had the most emotional investment in the conflict; it was—after all—their home country that was being torn apart. For the organizational level, we examine the journalist’s organization’s affiliation with countries directly or indirectly involved with the conflict. We apply Pantti’s (2019) approach by focusing on the displays of emotions and key themes represented in image tweets and propose the following two research questions:

RQ1:

In covering the Yemen War, did the home country or foreign identity of the journalist (Yemeni vs. non-Yemeni) influence a) the emotional expressions and b) the themes of the images shared on Twitter?

RQ2:

In covering the Yemen War, did the journalist’s organization (their affiliation with countries directly or indirectly involved with the conflict) affect a) the emotional expressions and b) the themes of the images shared on Twitter?

5 Visual Framing and Conflict Reporting

Visual framing refers to the selection of some aspects of the perceived reality and their accentuation by visual stimuli (Brantner et al. 2011). Journalists and reporters frame the news through selecting and highlighting certain snapshots of reality, while disregarding others, which promotes a certain understanding of the world and leads audiences to arrive at frame-specific conclusions (Entman 1993).

It has been well documented that the selection of images bringing certain aspects of the conflict into focus at the expense of other aspects results in the creation of visual frames. Fahmy (2007), for example, examined the visual coverage of the toppling of the Saddam Hussein statue in 2003 and found that newspapers in different countries adopted varying visual frames. The majority of the U.S. newspapers refrained from publishing images that portrayed the event as an instance of invasion or occupation (negative) and instead only published images that showed a victory/liberation frame (favorable), suggesting that Iraqis viewed the Americans as liberators rather than occupiers. Newspapers from other countries depicted the event differently. French newspapers, for instance, favored the invasion/occupation frame in visually portraying the toppling event. In another study, Fahmy (2010) examined the visual frames employed by English- and Arabic-language transnational press in covering the 9/11 attack and the Afghan War. The English-language newspaper (International Herald Tribune) published images that focused on the human suffering of 9/11 and on the complex military operations rather than the humanitarian costs of the Afghan war. The Arabic-language newspaper (Al-Hayat) employed visual frames that emphasized the material destruction of 9/11 rather than the victims and visual frames that focused on the human suffering of the Afghan War. The author argued that although both newspapers are based in Western European countries, they both have different cultural and political perspectives. This and other work on visual framing and conflict reporting suggest that an array of factors influence visual coverage and during conflicts the news media favor certain visual frames over others.

In the literature there is an agreement that visuals facilitate the understanding of conflicts in far-away zones (i.e., see Zelizer 2017). They are highly effective tools for enunciating ideological messages (Messaris and Abraham 2001) and shaping public opinion (Fahmy et al. 2014). In reporting conflict, past studies have shown that images have stronger effects on public opinion and behavioral intentions (Powell et al. 2015). Based on their real-life qualities, images depicting extreme human suffering in war-torn territories play a critical role in the formation of public opinion and in creating collective public memories (Hellmueller and Zhang 2019). These images have more power to influence viewers than words alone (Zelizer 2005).

For visual framing researchers, differentiating between themes and frames offers a useful lens. Bowe et al. (2019) for example, first examined the themes about the visual representation of the burkini (full body swimsuit) and then analyzed how these themes were framed to unravel the visual representation of a complex cross-cultural debate. As Kuypers (2009) noted, “a theme is the subject of discussion, or that which is the subject of the thought expressed. The frame … is suggesting a particular interpretation of the theme” (p. 187). It is therefore necessary to differentiate between these two concepts to understand the denotative and connotative meanings embedded in the visual representation of intricate events.

In the visual communication field, framing research has focused on the analysis of all types of visuals. For example, scholars have analyzed a variety of visuals, including images (i.e., Bowe et al. 2019), cartoons (i.e., Berkowitz 2017), memes (i.e., Fahmy and Ibrahim 2021), and social media content (i.e., Makhortykh and Sydorova 2017). Most recently, as journalists have relied heavily on digital platforms to report on global crises, there has been an increasing interest in visual tweets (Pantti 2019; Zelizer 2002). Pantti (2019) explains that visuals shared on Twitter allow for enhanced articulation, engagement, and shareability and thus are more often used by journalists to increase user engagement and interest in their tweets.

Based on the above, in our last research question we explore the visual representation of the Yemen Civil War. Following our analysis of themes, we then examine how these themes are framed (see Kuypers 2009). We analyze the broad spectrum of frames present in the image tweets surrounding the conflict to uncover the different patterns of visual framing and personalized reporting on Twitter.

RQ3:

How did the journalists visually frame the Yemen Civil war on Twitter?

6 Method

6.1 Data Collection

The Yemen War began in 2014 when rebel Houthis procured extensive control of northern Yemen, including the capital of Sana’a. Each warring party in the conflict took political steps to justify its authority and military operation, hence portraying the situation in a way that legitimized its actions and position. To investigate the different visual narratives related to the conflict and explore patterns of visual framing and personalized journalism on Twitter, we used Twitter’s advance search using keywords related to the war. We purposively selected a sample of 13 journalists who work for different news organizations that are affiliated with either the United States, Saudi Arabia, Qatar or Iran. From 3 to 4 journalists were chosen from the different news organizations affiliated with the four countries directly or indirectly involved with the conflict, based on the amount of war coverage (number of shared tweeted images related to the Yemen Conflict) and their influence (number of followers on Twitter) to ensure the selected journalists were among the most prominent compared to their peers.[4] We chose the journalists who tweeted the most images about the war and who also had a large number of followers. The selection of the journalists was also based on the volume of visual tweets they shared; that is, we selected journalists who were more likely to share images rather than text. Table 1 details a complete list of the selected journalists, along with their Twitter accounts, job description, nationality, and country affiliation of the news organization they are working for.

Table 1:

A list of the selected journalists covering the Yemen Civil War on Twitter (N = 13).

Name Twitter account Job description Country affiliation of News organization Home country or. foreign identity of the journalist
Maad Alzekri @MaadAlzekri Freelance video journalist at AP (Twitter Profile & The Pulitzer Center) US Yemeni
Shuaib M. Almosawa @Shuaibalmosawa Freelance journalist who wrote for The New York Times, The Intercept, and Foreign Policy (Columbia Journalism Review) US Yemeni
Maggie Michael @mokhbersahafi Journalist at AP (Twitter Profile & The Pulitzer Center) US Non-Yemeni (Egyptian)
Giles Clarke @gcwingman Freelance photojournalist at CNN, Arizona Daily Star, etc. (Twitter Profile and Muck Rack) US Non-Yemeni (American)
Fatima Alasrar @YemeniFatima Columnist/Contributor at Arab News, Foreign Policy, and Al-Arabiya Saudi Arabian Yemeni
Badr Alqahtani @BadrAlQahtani Journalist at Aawsat News Saudi Arabian Non-Yemeni (Saudi)
Mohammed Al-Arab @malarab1 Journalist at Al-Arabiya Saudi Arabian Non-Yemeni (Bahraini)
Abas Aslani @AbasAslani Editor at Iran Front Page (Iran Front Page) Iranian Non-Yemeni (Iranian)
Akram Sharifi @akramsharifi Journalist affiliated with Iran news organization Iranian Non-Yemeni (Iranian)
Fereshteh Sadegni @fresh_sadegh Freelance Journalist, Producer affiliated with Iran news organization Iranian Non-Yemeni (Iranian)
Sara Massoumi @SaraMassoumi Journalist (Iranian Diplomacy) Iranian Non-Yemeni (Iranian)
Abdulaziz Al-Sabri @abdulazizasabri Photographer at Al Jazeera. Qatari Yemeni
Afrah Nasser @Afrahnasser Contributor to Al Jazeera Qatari Yemeni

For the first step, we collected all of their tweets related to the conflict from January 1, 2014 to November 11, 2019. This collection process started with the beginning of the war in 2014 and continued for an extended period of time. This extended time frame provided a variety of visuals of the conflict and everyday life in Yemen. All of the images from the 13 journalists’ Twitter accounts during the study period were downloaded using a Google Chrome extension for bulk image downloads, thus allowing us to capture 8926 image tweets. Keywords related to the conflict were identified in English, Arabic, and Persian to filter out relevant images. These keywords were Yemen, Yemeni, Houthi, Houthis, Aden, Sana’a, Taiz, and Amran and were used to search through the captions and hashtags of the downloaded images.

Thereafter, we filtered out any tweet that did not contain an image. Following the recent work of Fahmy and Ibrahim (2021), we removed retweets and/or identical tweets to avoid repetition. Only original tweeted images were included in the data set; retweets were not included. Original tweets provided a more precise data set regarding journalists’ judgments and standpoints related to Yemen. In the case of multi-image tweets that included more than one image, each image was coded separately. And only images that included one or more keywords in either the caption or the accompanying hashtags were included. This process yielded 2880 image tweets related to the conflict. These images tweets were then retained for further analysis.

6.2 The Coding Process

All of the 2880 images tweets were coded, with the unit of analysis being a single image tweet. For the quantitative analysis a detailed set of categories was developed based on previous literature and the current context. The coding was based on the following five variables:

  1. Type of image: This variable identified the type of visual. Image tweets were coded as: picture only, picture-text (including memes), map, and caricature. To be coded as a map, the image tweet needed to show maps of Yemen. Images that were accompanied by any type of text were coded in the picture-text category, including memes. In this category, the meme was defined as a picture with a formatted text meant to provide commentary on current events or cultural ideas (Gil 2020). To be coded as a caricature, the image had to communicate the message with an exaggerated drawing (Sarigül 2009).

  2. Emotional expressions: Following the codebook constructed by Pantti (2019), each image was coded based on the following categories: tragic, ironic/comical, critical, and neutral. One additional category happiness was added to code for images with a positive emotional tone (i.e., people smiling as shown in Figure 1). Images coded as neutral provided reflections of the conflict and carried no emotional connotation, such as images of maps and intact buildings. To be coded as Tragic, the image included depictions of human suffering or loss and destruction of property or belongings. Ironic/comical image tweets (Figure 2) are meant to evoke humor or explicitly make a negative evaluation of their subject matter. Finally, images coded as Critical expressed angry disapproval of the humanitarian costs of the war and/or criticized policies or officials (Figure 3).

  3. Key theme: For this variable, we again used Pantti’s approach (2019) to identify the key themes. The images tweets were coded for the following categories: armed conflict, international politics, conflict violence, everyday life, and journalistic work. Upon coding, an additional theme emerged: demonstrations and was added to the list of categories. Examples of images coded for armed conflict, included images of soldiers in combat or those carrying weapons. Images of state officials or international organization officials were coded in the international politics category. For the conflict violence category, it included images that depicted the aftermath of the war, such as destroyed property, and humanitarian suffering (i.e., dire living conditions, including poverty, starvation, grief, and images of injured individuals). To be coded in the everyday life category, the image captured any sense of normalcy in the lives of Yemenis (i.e., children playing, photos of food and/or nature). Images that portrayed media personnel covering the war were coded as journalistic work. An additional category entitled “Other” was added to include memes with textual information only and maps.

  4. Country affiliation of news organization: We examined the Twitter profiles of journalists’ who work for different news organizations affiliated with four countries directly or indirectly involved with the conflict. As detailed in Table 1, the categories were: US, Saudi Arabian, Iranian, and Qatari.

  5. Home country or foreign identity of the journalist: For this variable, we examined the personal bios of journalists shared on their Twitter profiles. We then coded them as: Yemeni and non-Yemeni as shown in Table 1. In case the journalist’s nationality was not evident from their Twitter profile, we checked their profile on the website of the news organizations they worked for. If the journalist held a dual nationality, one of which was Yemeni, the journalist was coded as Yemeni.

Figure 1: 
An example of an image tweet with a happy emotional tone.
Fatima Alasrar, Twitter: @YemeniFatima. April 8, 2016.
In the image, Yemeni artists pose for photos in front of paintings.

https://twitter.com/YemeniFatima/status/718552680122183680.

Figure 1:

An example of an image tweet with a happy emotional tone.

Fatima Alasrar, Twitter: @YemeniFatima. April 8, 2016.

In the image, Yemeni artists pose for photos in front of paintings.

https://twitter.com/YemeniFatima/status/718552680122183680.

Figure 2: 
An example of an ironic/comical image tweet.
Abdulaziz Al-Sabri, Twitter: @abdulazizasabri. August 25, 2018.
A cartoon by Yemeni cartoonist Rashad Alsamei (رشاد السامعي), shows a doctor who operates on himself.

https://twitter.com/abdulazizasabri/status/1033454621732360192.

Figure 2:

An example of an ironic/comical image tweet.

Abdulaziz Al-Sabri, Twitter: @abdulazizasabri. August 25, 2018.

A cartoon by Yemeni cartoonist Rashad Alsamei (رشاد السامعي), shows a doctor who operates on himself.

https://twitter.com/abdulazizasabri/status/1033454621732360192.

Figure 3: 
An example of a critical image tweet.
Fatima Alasrar, Twitter: @YemeniFatima. December 27, 2018.
A cartoon by Yemeni cartoonist Rashad Alsamei (رشاد السامعي). The cartoon shows the gap between the poor society and rich officials.

https://twitter.com/YemeniFatima/status/1078318612388237313.

Figure 3:

An example of a critical image tweet.

Fatima Alasrar, Twitter: @YemeniFatima. December 27, 2018.

A cartoon by Yemeni cartoonist Rashad Alsamei (رشاد السامعي). The cartoon shows the gap between the poor society and rich officials.

https://twitter.com/YemeniFatima/status/1078318612388237313.

One of the authors who is proficient in English, Arabic, and Persian, completed the coding of the 2880 image tweets. To assess intercoder reliability, a second person randomly coded a selected subset of 12.5% of the entire sample (360 images). For all variables, the rate of agreement by chance was acceptable using Scott’s Pi (see Scott 1955). Specifically, for Type of image, the rate of agreement was 0.85. For Emotional domain, the agreement was 0.93. For the Key theme, the agreement was 0.75. For the Country affiliated Organization, the agreement was one. Finally, for home country or foreign identity of the journalist, the agreement was one.

Following the quantitative analysis and to answer the third research question, we examined patterns of visual framing and holistically explored the entire corpus of image tweets. When analyzing visuals, it is not only significant to look at manifest messages but to explore latent, below-the-surface meanings (Bowe et al. 2019). Image subjects (including persons and objects) do not only represent their individual selves, but also denote a range of ideas or concepts (see Rodriguez and Dimitrova 2011; Rose 2016). In addition to analyzing the manifest meanings, we therefore also embarked on a qualitative semiotic analysis to explore the connotative and latent meanings associated with the visual content. This analysis allowed for a better understanding of the signs used and how they related to each other and to the ideology articulated within them (Rose 2016). It combined both denotative and connotative explorations of visuals, as recommended by a variety of scholars (i.e., Bowe et al. 2019; Rose 2016).

7 Results

Because an image tweet usually contains pictures, it made sense that out of the 2880 image tweets analyzed, almost 70% were in the pictures only category (68.8%). A quarter were coded as picture-text tweets (25.6%) and the remaining percentage of tweets analyzed were maps (2.1%) and caricatures (3.6%).

Looking at the overall corpus, there were more tweets by Yemeni than non-Yemeni journalists (60.5 vs. 39.5%). Further, journalists affiliated with the Saudi news organizations shared almost half of image tweets in our dataset (48%), while journalists affiliated with Iranian news organizations shared the least proportion of image tweets at 3.4%. Regarding emotional domains, almost two-thirds of the tweets fell in the neutral category (64.7%) and one-quarter of the tweets were tragic (23.2%). The remaining 12% were coded in the happiness, critical and ironic/comical categories. These emotional domains applied to the entire dataset of journalists—regardless of their home country or foreign identity and the country affiliation of the news organization they are working for—and could suggest that journalists generally preferred to adopt a neutral stance when reporting conflicts on Twitter. Regarding themes, the most common theme was international politics at 22.5%, followed closely by violence at 20.5%. The least identified theme was journalistic work, at 5.9%.

RQ1 investigated the impact of home country or foreign identity of the journalist on the emotional expressions and themes of the tweeted images shared on Twitter. Overall, our data shows similarities between Yemenis and non-Yemenis in visually depicting emotional expressions on Twitter (see Figure 4). Results of a chi-square did not yield significant differences (χ2 = 8.38, p > 0.05). As illustrated in Table 2, both Yemeni and non-Yemeni journalists were more likely to post images with no emotional connotation (65.2% and 64% respectively), followed by visuals of tragedy. The remaining visual tweets that were coded in the happiness, critical and ironic/comical categories, were minimal.

Figure 4: 
Emotional expressions in the tweeted images of the Yemen Civil War based on journalists’ home country or foreign identity (N = 2880).

Figure 4:

Emotional expressions in the tweeted images of the Yemen Civil War based on journalists’ home country or foreign identity (N = 2880).

Table 2:

Frequency and percentages of themes and emotional expressions in the tweeted images of the Yemen Civil War based on the journalists’ home country or foreign identity (N = 2880).

Yemeni Non-Yemeni Total Chi-square
Emotional domain 8.38
 Neutral 1136 (65.2%) 728 (64.0%) 1864 (64.7%)
 Tragic 411 (23.6%) 258 (22.7%) 669 (23.2%)
 Happiness 96 (5.5%) 90 (7.9%) 186 (6.5%)
 Critical 50 (2.9%) 38 (3.3%) 88 (3.1%)
 Ironic and comical 49 (2.8%) 24 (2.1%) 73 (2.5%)
Total 1742 (100%) 1138 (100%) 2880 (100%)
Key theme 375.08a
 International politics 311 (17.9%) 337 (29.6%) 648 (22.5%)
 Violence of war 376 (21.6%) 215 (18.9%) 591 (20.5%)
 Armed conflict 142 (8.1%) 293 (25.8%) 435 (15.1%)
 Everyday life 305 (17.5%) 93 (8.2%) 398 (13.8%)
 Demonstrations 186 (10.7%) 7 (0.2%) 193 (6.7%)
 Journalistic work 89 (5.1%) 80 (2.8%) 169 (5.9%)
 Others 333 (19.1%) 113 (3.9%) 446 (15.5%)
Total 1742 (100%) 1138 (39.5%) 2880 (100%)

  1. a p < 0.001.

Regarding themes, however, our data painted a different picture (see Figure 5). Yemeni journalists tweeted the most about violence at 21.6%, followed by visual tweets on international politics at 17.9% and everyday life in Yemen at 17.5%. Non-Yemeni journalists, on the other hand, tweeted the most about international politics at 29.6%, followed closely by armed conflict at 25.8% (Table 2). These differences were statistically significant (χ2 = 375.08, p < 0.001).

Figure 5: 
Themes in the tweeted images of the Yemen Civil War based on journalists’ home country or foreign identity (N = 2880).

Figure 5:

Themes in the tweeted images of the Yemen Civil War based on journalists’ home country or foreign identity (N = 2880).

RQ2 explored the impact of country affiliation of the news organizations journalists are working for on the emotional expressions and themes visually identified on Twitter. Overall, our data analysis indicated significant differences[5] in both emotions (χ2 = 297.65, p < 0.001) and themes (χ2 = 898.73, p < 0.001).

In displaying emotional expressions as shown in Table 3, journalists affiliated with US news organizations, tweeted their largest proportion of visuals (61.1%) communicating tragedy, while journalists affiliated with the Saudi Arabian, Iranian, and Qatari news organizations tweeted their largest proportion of visuals with a neutral tone. Overall, a small proportion of the images were coded with a happy emotional tone (6.4%), which would only be appropriate given the conflict’s tragic nature. Only a minority of the image tweets (3.1%) were coded in the critical category (Figure 6), suggesting that journalists by and large rarely resorted to other emotional styles. Journalists mostly refrained from overtly criticizing or making judgments even on Twitter, an environment where they were free to do so.

Table 3:

Frequency and percentages of themes and emotional expressions in the tweeted images of the Yemen Civil War based on country affiliation of news organization journalists are working for (N = 2880).

U.S. Saudi Arabia Iran Qatar Total Chi-square
Emotional domain 297.65 a
 Neutral 84 (31.5%) 1014 (73.4%) 71 (72.5%) 695 (61.4%) 1864 (64.7%)
 Tragic 163 (61.1%) 218 (15.8%) 10 (10.2%) 278 (24.5%) 669 (23.2%)
 Happiness 11 (4.1%) 85 (6.1%) 14 (14.3%) 76 (6.7%) 186 (6.4%)
 Critical 7 (2.6%) 39 (2.8%) 1 (1.0%) 41 (3.6%) 88 (3.1%)
 Ironic and comical 2 (0.7%) 26 (1.9%) 2 (2.0%) 43 (3.8%) 73 (2.6%)
Total 267 (100%) 1382 (100%) 98 (100%) 1133 (100%) 2880 (100%)
Key theme 898.73a
 International politics 20 (7.5%) 352 (25.5%) 76 (77.6%) 200 (17.7%) 648 (22.5%)
 Violence of war 159 (59.6%) 172 (12.4%) 9 (9.2%) 251 (22.2%) 591 (20.5%)
 Armed conflict 10 (3.7%) 346 (25.0%) 6 (6.1%) 73 (6.4%) 435 (15.1%)
 Everyday life 58 (21.7%) 106 (7.7%) 0 (0%) 234 (20.7%) 398 (13.8%)
 Demonstrations 13 (4.9%) 34 (2.5%) 1 (1%) 145 (12.8%) 193 (6.7%)
 Journalistic work 1 (0.4%) 82 (5.9%) 3 (3.1%) 83 (7.3%) 169 (5.9%)
 Others 6 (2.2%) 290 (21.0%) 3 (3.1%) 147 (13.0%) 446 (15.5%)
Total 267 (100%) 1382 (100%) 98 (100%) 1133 (100%) 2880 (100%)

  1. a p < 0.001.

Figure 6: 
Emotional expressions of the tweeted images covering the Yemen Civil War based on country affiliation of news organization journalists are working for (N = 2880).

Figure 6:

Emotional expressions of the tweeted images covering the Yemen Civil War based on country affiliation of news organization journalists are working for (N = 2880).

In terms of themes, our data once again illustrates differences (see Figure 7). The violence theme dominated the image tweets of journalists who work for US news organizations (59.6%), followed by one-fifth (21.7%) of the visuals showing everyday life in Yemen. The armed conflict and international politics themes were equally present at 25%, in the image tweets of journalists working for Saudi news organizations. These journalists were less likely to tweet extensively about violence and everyday life. The international politics theme dominated the image tweets of journalists who belong to the Iranian news affiliation, with 77.6% of the images shared. Oddly, these journalists did not tweet a single image focusing on everyday life in Yemen. Finally, Al-Jazeera journalists working for the Qatari news organization tweeted the most about violence (22.2%), followed closely by everyday life (20.7%) and international politics (17.7%). These journalists also tweeted the most about demonstrations (12.8%) in comparison to the other journalists working for US, Saudi Arabian, and Iranian news organizations.

Figure 7: 
Themes of the tweeted images covering the Yemen Civil War based on country affiliation of news organization journalists are working for (N = 2880).

Figure 7:

Themes of the tweeted images covering the Yemen Civil War based on country affiliation of news organization journalists are working for (N = 2880).

To address our last research question, we embarked on a semiotic analysis to examine how journalists visually framed the Yemen Civil War on Twitter. We combined both denotative and connotative analyses to identify the broad range of photographs and their role in manufacturing the representation of the conflict. We built on previous literature and the themes and narratives suggested by our quantitative content analysis, and used the semiotic analysis to explore the connotative and latent meanings to identify specific patterns (or frames) and provide an understanding of the signs included within the visuals (see Bowe et al. 2019; Rose 2016).

Based on this process of analysis and interpretation, four overarching frames emerged: The Official frame (N = 648) included images of state officials and/or representatives of international organizations; the Tragic-violent frame (N = 591) included images that focused on the humanitarian consequences of the war; the Armed Conflict frame (N = 435) included images in which the actual fighting, soldiers, weapons, and war zones were evident; the anti-war frame (N = 193) included images of demonstrations and citizens voicing their indignation over the war. Below we explain the four frames and list them from most prominent to least prominent.

7.1 The Official Frame

This frame showed the official viewpoints, including the coverage of peace talks, negotiations, and official meetings. For example, in Figure 8 the Minister of Foreign Affairs of Iran is shown with Ibrahim Mohammed Al-Dailami, who was appointed by the Houthi Movement as the ambassador of Yemen to Iran. This frame was the most prominent frame, and so the tendency toward the official perspective by journalists on Twitter is worth mentioning. It was specifically prominent in the image tweets shared among journalists affiliated with the Iranian and Saudi news organizations. The entire Yemen conflict can be traced back to the dispute between both Iran (who supports the Shiite Houthis) and Saudi Arabia (who was alarmed by rising Shiite influence in the region). Consequently, it was foreseeable that these journalists were most likely to adopt this visual frame when covering the war on Twitter.

Figure 8: 
An example of an official frame.
Akram Sharifi, Twitter: @akramsharifi. September 1, 2019.
The Minister of Foreign Affairs of Iran is shown meeting with Ibrahim Mohammed Al-Dailami, who was appointed by the Houthi Movement as the ambassador of Yemen to Iran.

https://twitter.com/akramsharifi/status/1168095585167187970.

Figure 8:

An example of an official frame.

Akram Sharifi, Twitter: @akramsharifi. September 1, 2019.

The Minister of Foreign Affairs of Iran is shown meeting with Ibrahim Mohammed Al-Dailami, who was appointed by the Houthi Movement as the ambassador of Yemen to Iran.

https://twitter.com/akramsharifi/status/1168095585167187970.

7.2 The Tragic-Violent Frame

A high priority for the journalists was to cover the day’s violent events. The tragic-violent frame focused mainly on the Yemeni population and portrayed the violent consequences of the war and everyday life in Yemen (Figure 9). This visual frame was mostly evident in the tweets of Yemeni journalists and journalists affiliated with US and Qatari news organizations. These journalists tweeted profusely about the violent aftermath of the war, including images of dire living conditions and injured individuals. Semiotically, using this frame, the journalists personalized the conflict and focused on the plight of the Yemenis living through a prolonged humanitarian crisis. The sign produced in these tweets conveyed a tragic emotional tone that would have prompted a high level of engagement between journalists and their audiences. Among the common Tweets in this frame were a group of visuals highlighting the rampant starvation among children, the destruction of belongings and property, and the grief over lost ones.

Figure 9: 
An example of a tragic-violent frame.
Account for the image tweet. @MaadAlzekri. November 19, 2017.
This multi-image tweet shows suffering Yemeni children.

https://twitter.com/MaadAlzekri/status/932366452966948864.

Figure 9:

An example of a tragic-violent frame.

Account for the image tweet. @MaadAlzekri. November 19, 2017.

This multi-image tweet shows suffering Yemeni children.

https://twitter.com/MaadAlzekri/status/932366452966948864.

7.3 The Armed Conflict Frame

This frame featured combat in action. Among the most common images in this frame were snapshots of the actual fighting, including military operations, armed forces, soldiers in combat, and military tools. These photos represented a relatively smaller portion of the overall coverage analyzed on Twitter, which is noteworthy because combat is the main event during war. This frame was most prominent in the tweets of journalists affiliated with Saudi news organizations, who often shared images of child soldiers fighting within the ranks of the Houthi army (Figure 10). Here, in a semiotic sense such visual tweets possibly attempted to highlight the atrocities committed by the Houthis. The sign created carried a sense of personalizing the coverage in a way that delegitimize the Houthis’ position in the conflict.

Figure 10: 
An example of an armed conflict frame.
Fatima Alasrar, Twitter: @YemeniFatima. July 3, 2018.
Child soldiers in the Houthi militia army are shown holding rifles.

https://twitter.com/YemeniFatima/status/1014175311435530241/photo/1.

Figure 10:

An example of an armed conflict frame.

Fatima Alasrar, Twitter: @YemeniFatima. July 3, 2018.

Child soldiers in the Houthi militia army are shown holding rifles.

https://twitter.com/YemeniFatima/status/1014175311435530241/photo/1.

7.4 The Anti-War Frame

This frame featured citizens (Yemeni or otherwise) protesting against the ongoing war. For example, Figure 11 shows mass demonstrations against the local government to demand basic necessities. These image tweets featured people expressing frustrations and/or indignation. Among the most common images in this frame were individuals holding signs in protest. One image showed a young boy carrying a sign that read, “the smell of gunpowder suffocates me.” Other tweets showed masses of people holding the Yemeni flag. Semiotically, these photos signified the anti-war perspective. While this frame represented a relatively small portion of the overall visuals analyzed (6.7%), most of these anti-war visuals circulated the most among journalists affiliated with the Qatari organization, and thus personalized the coverage to reinforce Qatar’s perspective towards the conflict as a neutral mediator.

Figure 11: 
An example of an anti-war frame.
Account for the image tweet. @abdulazizasabr. October 26, 2019.
Mass protests at Taiz and demands for basic necessities, such as medicine and fair wages.

https://twitter.com/abdulazizasabri/status/1188076319256350720.

Figure 11:

An example of an anti-war frame.

Account for the image tweet. @abdulazizasabr. October 26, 2019.

Mass protests at Taiz and demands for basic necessities, such as medicine and fair wages.

https://twitter.com/abdulazizasabri/status/1188076319256350720.

8 Discussion

This comparative study examined how journalists from different nationalities and organizational backgrounds shared images to give meaning to the controversial Yemen Civil War on Twitter. So far, limited research exists on the different visual narratives and personalized reporting presented by journalists on social media. Guided by previous literature, our content analysis showed that while journalists offered some personalized reporting, by and large journalists preferred to adopt a neutral stance when reporting the conflict, similar to what is typically expected in traditional news reporting. Our semiotic analysis complemented our findings and showed more broadly that the image tweets emphasized the classic war-as-a-tragedy narrative, while at the same time shedding some light on the political conflict.

Content analysis showed how both Yemeni and non-Yemeni journalists posted neutral images more often, which suggests journalists by and large prioritize fact-based neutral reporting, even when the topic under question holds a highly personal value. The majority of the image tweets analyzed communicated a neutral emotional tone, which supports current research (Pantti 2019). Despite the fact that journalists on the Twitter platform are relatively free from traditional editorial constraints, this does not mean they perpetually engage in personalizing narratives on social media. Journalists still generally adhere to their professional roles as information disseminators on social media. Our quantitative analysis served as a useful starting point to understand that journalists overall refrained from sharing a large proportion of image tweets that were ironic or critical and thus, distanced their opinions and personal stories from their reporting.

Our next level of analysis, however, revealed a slightly more subjective pattern, a finding in line with recent findings that illustrates personalized reporting on social media is scarce, yet detectable (see Pantti 2019). Yemeni journalists were more likely to share image tweets about violence and everyday life in Yemen and non-Yemeni journalists were more likely to share image tweets about international politics and armed conflict. Here, the individual level factor (home country or foreign identity of the journalist) was influential. Yemeni journalists naturally were more invested in their country’s well-being and thus more likely to believe that the humanitarian costs of the war are most important. Non-Yemeni—being distant from the war—were more likely to focus on the political aspects of the conflict, by sharing images, for example, depicting negotiations between officials and soldiers in combat.

The local conflict in Yemen quickly shifted to a proxy war, in which Yemen became the theater where superpowers and regional actors got involved to achieve their strategic objectives. It was in this context that the organizational level factor appeared influential. Journalists affiliated with both the US and Qatari news organizations were more likely to share images about violence of war and everyday life in Yemen, thus emphasizing the humanitarian cost of the conflict through sharing images of grieving people, poor living conditions, and the persistence of life despite the proliferation of death and destruction. On the other hand, journalists affiliated with the Saudi and Iranian news organizations, tweeted the most about international politics, thus shifting the focus away from the conflict’s human consequences and highlighting its political dimensions. The organizational level influence was further crystalized by looking at the emotional expressions within the image tweets analyzed here. Journalists affiliated with the US organizations shared the largest proportion of images illustrating powerful tragic connotations. Meanwhile, journalists affiliated with Saudi, Iranian, and Qatari news organizations prioritized the sharing of neutral tweets, thus assuming the role of visual gatekeepers themselves and the practice of traditional journalism. While we understand that a universally agreed upon definition of what constitutes traditional journalism does not exist, keeping one’s own emotions in check and attempting to provide coverage that is as neutral as possible can be considered a good starting point.

Overall, our findings captured the fluctuating role of journalists on Twitter. Journalists occasionally fluctuated in their visual roles between being neutral observers and moral agents and these fluctuations were likely influenced by an array of factors, including the journalist’s home country or foreign identity and the country affiliation of news organizations they were working for. Our findings here, thus, extend the hierarchy of influence model (Shoemaker and Reese 1996) in the context of personalized reporting on Twitter. Similar to traditional media, lower individual level factors, such as the journalist’s home country or foreign identity, seem less influential than higher-level factors, such as country affiliation of organizations that journalists need to operate within.

Our semiotic analysis further contextualized the visuals qualitatively and helped develop an in-depth understanding of the visual narrative surrounding the war. By and large, the journalists examined overwhelmingly framed the war as an official/tragic issue. The biggest portion of featured images were not about the conflict itself but were about politicians and government officials from different countries amid negotiations, as well as images of human suffering, including images of mourning citizens.

As noted, the official frame was the most dominant frame and it was most evident in the Twitter images posted by journalists affiliated with the Iranian news organizations, followed by journalists who work for the Saudi news organizations. These journalists rarely used the tragic-violent frame; that is, they shared a small number of images that depicted the suffering of civilians. Perhaps for them, the casualties of war did not come at the forefront of their framing decisions on Twitter, but rather Iran and Saudi motivations to maintain power and influence in the region were. In fact, our results showed the armed conflict frame was most evident in the tweets of journalists affiliated with Saudi news organizations. As previously noted, Saudi Arabia led a coalition of Arab countries that supported military involvement in Yemen against the Iran-backed Houthis. Such a frame de-emphasized visual messages that focused on the suffering of the victims and prioritized instead a more technical frame that featured images of men in uniform carrying their weapons and mugshots of soldiers. Such focus on military preparations clearly de-emphasized the humanitarian cost of the conflict and may have led to a specific interpretation of the conflict in which the human suffering was shoved to the background. And it was no surprise that this was the visual narrative favored by the journalists working for Saudi news organizations. While many media outlets strive to be objective, in conflict reporting many choose to rally around the flag and support their country’s official viewpoints, even in democratic societies (Gasim 2018; Novais 2007).

By contrast, the tragic-violent frame was more dominant in the image tweets posted by Yemeni journalists. By and large, our study revealed more tweets by Yemeni than non-Yemeni journalists. As documented above, Yemeni journalists had the most emotional investment in the conflict, as it was their home country being torn apart. The tragic-violent frame was also more prominent in the image tweets posted by journalists who work for both the US and Qatari news organizations.

Although the United States backed the Saudi involvement in the war in hopes of resisting Iranian influence in the region, journalists who worked for U.S. news organizations found no qualms in exposing the ugly truth about the conflict, through prioritizing a tragic-violent frame. Through sharing images of mourning families, starving children, and citizens surviving in dire conditions (see Figure 9), these journalists unmistakably favored a specific interpretation of the conflict, suggesting that the humanitarian costs of the war were far too high and that it was, at the end, the average Yemeni citizen who bore the brunt of the conflict. Unlike traditional media, these journalists focused on the violent consequences of the war – an aspect they deemed important. It is through the relative freedom afforded by Twitter that these journalists were able to personalize their reporting.

The position of Qatar shifted throughout the conflict. While at the beginning, Qatar supported the Saudi-led coalition, it was later ostracized by Saudi Arabia and other Gulf countries and stepped away from active military involvement to a more neutral stance, supporting peaceful settlement. Journalists who worked for the Qatari news organization Al-Jazeera also focused on the tragic-violent frame, perhaps in an attempt to shed light on the humanitarian costs of a war that Qatar was pushed away from. These journalists were Yemini and prioritized an interpretation of the conflict and the sign created by their images conveyed a message that coincided with Qatar’s perspective: the cost of the military involvement had become too high and a more peaceful approach would be more fitting. Similarly, the anti-war frame was mostly employed by Qatari-affiliated journalists. Images published in this frame included demonstrations, citizens expressing their anger over the war, and children holding signs describing the horrors of the conflict. Qatar’s position in the conflict had shifted from active military participation to more of a dislodged supporter of peaceful resolution. It stands to reason that these journalists’ focus on an anti-war frame coincided once again with Qatar’s overall vision of rejecting military intervention and adopting strategies that support the peaceful settlement of the war. By focusing on how the Yemenis themselves have had enough with the ongoing conflict, these journalists may in a way garner support for their cause: there has to be some other way to resolve the conflict other than military violence. A plausible explanation for the variations in the dominant frame adopted by each organizational side is the journalistic culture within which journalists operate. The focus on images of official meetings (the official frame) that was common in the Iranian and Saudi tweets is probably common in the media of these two countries in general, across many areas of content. It may be the result of the media’s tendencies in these two countries to cater to political elites, and perhaps the official frame was limited in both Al Jazeera and US news organizations because of their more audience-driven nature.

9 Conclusion

Previous work illustrates journalists do not operate in a vacuum. Instead, their reporting is influenced by a whole host of internal and external factors (Shoemaker and Reese 1996). Initially, we noted the large portion of neutral visuals, but a closer inspection has led us to conclude that journalists also to some extent personalized their visual narratives through sharing some bitingly ironic and deeply critical images and these tweets were of subjective nature. One notable example is a caricature of an injured man connected to an IV drip, lying on a hospital bed and operating on himself with an open wound across his stomach (Figure 2). The man was identified in the image as Taiz, one of Yemen’s war-torn cities. The message suggests that no one has come to the city’s rescue, even in its most desperate state. However, given the small number of such emotionally laden images, this type of visual represented only a fraction of the tweets analyzed. By and large journalists in this study hardly allowed themselves room to share subjective content. Similarly, unlike other research that suggests journalists are likely to resort to irony on the social media platform (Holton and Lewis 2011; Lasorsa et al. 2012), we noted the use of irony and humor was been kept to a minimum and therefore, it was not an integral part of covering the conflict and communicating the journalist’s subjective voice, personal perspective, and/or critical evaluation. Journalists in this study, also, were least likely to share images about their journalistic work, although such a theme would have represented a ripe ground for displaying the journalists’ personal perspective and therefore allow Twitter users to see them for who they were, regular human beings working in a highly challenging environment.

Further, one important point should be made about our sample. We did not look at whether each individual journalist was operating on the ground, that is, tweeting images they have captured themselves, or whether they were simply selecting images to share from their respective organization’s database. This would have made a difference in understanding to what extent each journalist was actively framing the conflict. Capturing a live image and tweeting it because this is where the journalist is at a specific point in time has different framing implications than going through an already existing pool of photographs and selecting one to share. The former implies less control—as journalists cannot possibly predict the type of incidents that will occur—and consequently a less conscious attempt to favor a specific visual frame.

In conclusion, our study opens an exciting new avenue of study and contributes to the developing area of journalistic practices on social media. It allows for a deeper understanding of the extent and role of personalized journalism of conflict on Twitter. It also sheds light on different levels of influences on war coverage on social media, specifically in a non-Western context. The way the media visually portray a conflict contributes to how the mindsets and judgments of audiences are shaped (Fahmy et al. 2014). Although many scholars have previously discussed Twitter’s liberating potential for self-expression, this does not mean that journalists have resorted to overwhelmingly personalized styles of reporting. This study has demonstrated that journalists from different backgrounds have remained somehow obliged to carry on with their journalistic roles on the social media platform. We found that home country or foreign identity of the journalist, as an individual level factor, did play a minor role in determining the emotional tone and the visual themes of the images posted on Twitter. In other words, Yemenis seemed more likely to shed light on the humanitarian cost of the war in comparison to non-Yemenis. However, a stronger predictor of emotional expressions and themes in the tweeted visuals was at the organizational level, that is, journalists working for news organizations affiliated with countries that were directly or indirectly involved in the conflict, influenced the personalization of the conflict on Twitter.

Finally, we are aware our research may have limitations. In this study we did not look at whether each individual journalist was operating on the ground, that is, sharing images they have captured themselves, or whether they were simply selecting images to tweet from their respective organization’s database. This would have made a difference in understanding to what extent each journalist was actively framing the conflict. Capturing a live image and sharing it because this is where the journalist was at a specific point in time has different framing implications than going through an already existing pool of photographs and selecting one to share. The former implies less control—as journalists cannot possibly predict the type of incidents that will occur—and consequently a less conscious attempt to favor a specific visual frame. Finally, there are large variations in the sample size for each country affiliation. For instance, there are 1382 image tweets from the Saudi Arabian-affiliated organizations and only 98 image tweets from the Iranian side, an observation which should be kept in mind when interpreting the results of this study. This study analyzed the visuals shared by journalists who work for news organizations affiliated with four countries that were directly or indirectly involved with the conflict. Future studies should include journalists from other news organizations and explore other conflicts. Future research should also make use of other research methods, such as surveys and in-depth interviews with news professionals who are actively engaged on Twitter. This study also categorized the individual level factor, in this case, home country or foreign identity of the journalist, to two camps only (Yemeni and non-Yemeni). Future research should make a more precise distinction among non-Yemeni journalists. Differences and/or similarities in visual coverage of journalists of different nationalities should be studied. This study also did not look at the level of association with the parent organization as a variable. Future research should examine if there are differences in visuals of freelance journalists and contributors versus full-time journalists on Twitter. Lastly, this study explored the impact of individual level and organizational level factors and scholars should continue to explore more internal and external factors that may influence personalized journalism on social media.


Corresponding author: Shahira S. Fahmy, The American University in Cairo, New Cairo, Egypt, E-mail:

Article Note: This article underwent single-blind peer review.


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Received: 2021-07-07
Accepted: 2021-10-21
Published Online: 2022-02-14

© 2022 Shahira S. Fahmy et al., published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.