First Monday

Hashtag publics, networked framing and the July 2016 coup in Turkey by Semra Demirdis, Stefania Vicari, and Paul Reilly



Abstract
On 15 July 2016, Turkey faced a military coup attempt against the government. Most Turkish citizens learned about the coup attempt from President Recep Tayyip Erdoğan, who contacted a television channel using FaceTime and urged citizens to go into the streets to resist it. Social media platforms, such as Twitter, were used heavily by Turkish citizens, with hashtags such as #TurkeyCoupAttempt, #darbeyehayir, #NoCoupInTurkey and #TurkeyCoup all trending during this period. This paper focuses on one of the most important anti-coup hashtags, #darbeyehayir (NoCoup), to examine how it was used during the anti-coup protests. By applying a mixed methods approach for Twitter content under the hashtag, the aim of the study is to unveil motivational frames used to call for action and provide a rationale for those participating in anti-coup protests. Results demonstrate that the framing dynamics emerging in the hashtags publics in which pro-Erdoğan supporters were dominant and used this process to provide support to the government during the ‘coup’. The hashtag was mainly used as a tool for government propaganda rather than encouraging civic discussions and participation, and ultimately democratic acts in authoritarian countries.

Contents

Introduction
The emergence of publics with the use of Twitter hashtags
Framing as discursive practice
Networked framing on Twitter
Hashtag activism in Turkey
15 July ‘coup’ attempt and anti-coup protests
Data and methods
Results
Conclusion

 


 

Introduction

On 15 July 2016, there was an attempted ‘coup’ against President Recep Tayyip Erdoğan’s government in Turkey, led by units of the national army. Erdoğan’s Justice and Development Party (Adalet ve Kalkınma Partisi or AK Party) used both traditional and social media to mobilise citizens against the ‘coup’ (Yavuz and Koc, 2016; Esen and Gumuscu, 2017). This article focuses on one of the most important anti-coup hashtags, #darbeyehayir, translated into English as ‘no coup’ (Mis, et al., 2016), to examine how it was used to encourage the anti-coup protests.

Previous research suggests that online platforms like Twitter provide unprecedented opportunities for non-elite users to shape news agendas and gain visibility (Chadwick, 2017). This often happens through the emergence of publics that form around hashtags. These dynamics can generate and promote so-called ‘counterpublics’ around contentious political issues (Jackson and Foucault Welles, 2016, 2015; Choi and Cho, 2017), that is, alternative and often activist collective voices that aim to challenge the status quo. This paper adds to the literature on hashtag publics by exploring the framing dynamics of these formations when they mobilise in favour of governments rather than against them. In other words, it seeks to explore how Twitter and, more specifically, its hashtags, may enhance the coming to prominence of reactionary discourses.

This article begins by reviewing literature on hashtag publics and counterpublics. It then discusses theorisations of activist discourses practices through the lens of ‘frame theory’ (e.g., Goffman, 1975; Benford and Snow, 2000) and progresses with a reflection on studies of ‘networked framing’ on Twitter (Dahlberg-Grundberg and Lindgren, 2014; Papacharissi, 2016; Hon, 2016; Xiong, et al., 2019). It then moves on to provide background on the role of social media during the anti-coup protests in July 2015, before presenting the findings of a mixed methods study of 10,953 #darbeyehayir tweets posted between 15 July and 19 July 2016. The remainder of the paper discusses the empirical findings, shedding light into how hashtag publics can become a means to support, rather than challenge, governments.

 

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The emergence of publics with the use of Twitter hashtags

Hashtag defined as the “prefixing of a keyword or phrase with the # symbol” [1]. Hashtags are used to indicate an event, subject or association on Twitter (Murthy, 2018). They were first created by San Francisco technologist Chris Messina (2007) in order to improve “contextualization, content filtering and exploratory serendipity within Twitter”, allowing individuals to follow and become a part of conversations on specific topics without needing to ask permission or send friendship requests to view the feeds of others (Chaudhry, 2014).

The connection and disconnection of publics through the use of social media constitute an ongoing transformation for public spaces (Poell and van Dijck, 2015). In fact, there is a need to reconsider the structures of the publics and positions of public figures in public spaces (Poell and van Dijck, 2015). Scholars have suggested such terms as ‘networked publics’, ‘counterpublics’ and ‘hashtag publics’ to understand the structures of communication and participation through digital media (e.g., boyd, 2010; Poell and van Dijck, 2015). According to boyd (2010), networked publics are “publics that are restructured by networked technologies; they are simultaneously a space and a collection of people” [2]. Hashtags have been linked to the emergence of networked publics. These are coordinated and shaped by the dynamics of communication networks and by the ways in which online platforms in particular are used relative to significant events or issues.

Jackson, et al. (2020) highlighted that hashtags can be used strategically to mobilise counterpublics and to hold political debates about identity politics that advocate for identity redefinition, social change and political inclusion. For example, #BlackLivesMatter and #Ferguson were used to criticise police brutality and increase the visibility of the BLM movement (Freelon, et al., 2016; Gallagher, et al., 2018). Hashtags were used by tweeters to express solidarity with the movement and their anger at police violence towards people of colour in the U.S. and overseas (Bonilla and Rosa, 2015; Carney, 2016; Ince, et al., 2017).

Hashtag publics emerge on Twitter in response to political events and crises. For instance, #Tahrir, #Jan25, #Tunisia, #Spill and #Egypt brought users together during the ‘Arab Spring’ (Rambukkana, 2015). During the ‘Arab Spring,’ individuals and organisations used Arabic- and English-language hashtags to inform each other about the actions of state actors, to plan and report protest activities, and to connect with the world to report events happening in the region (Howard, et al., 2011; Wilson and Dunn, 2011; Bruns, Highfield and Burgess, 2013). Lotan and colleagues (2011) found that the information flows through hashtags, such as #sidibouzid and #Jan25, were heavily influenced by journalists during the ‘Arab Spring’ movement. Journalists and activists served as key information sources; bloggers and activists were more likely to retweet content (key information routers), and news on Twitter was co-constructed by bloggers and activists alongside journalists (Lotan, et al., 2011). However, it needs to be acknowledged that hashtag activism has not in and of itself led to democratic reform in many of these countries. There was some evidence that these regimes used social media to round up and arrest its critics as well (Howard, et al., 2011). Therefore, hashtag activism should be seen as a double-edged sword, given that it exposes activists to potential harm.

 

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Framing as discursive practice

“Framing” can be defined as:

to frame is to select some aspects of a perceived reality and make them more salient in a communicating text, in such a way as to promote a particular problem definition, causal interpretation, moral evaluation, and/or treatment recommendation for the item described [3]

Framing works through the selection, interpretation, exclusion, emphasis, and retention of persistent patterns that are communicated symbolically (Gitlin, 2003). Frame analysis has been used, for instance, to examine the diffusion and functionality of mobilising ideas and meanings in social movements (e.g., Benford and Snow, 2000). Social movement frames are created and spread to achieve a particular purpose, such as recruiting new members, mobilising adherents and acquiring resources (Benford and Snow, 2000).

Social media often become platforms for elite and non-elite actors to frame events, news and values for mobilisation purposes. Individuals can use these platforms to interpret and propagate news content that has already been reported and distributed on several platforms (Singer, 2014). Thus, by publishing and endorsing news content, social media users can become gatekeepers (Wallace, 2018). The ‘gatewatching’ process describes how active audience members amplify, evaluate and share relevant materials posted by other sources to develop a comprehensive understanding (Bruns, 2005). The interactions between gatekeepers help foreground certain frames over others, indicating participation in the production and maintenance of meanings (Meraz and Papacharissi, 2013).

Seminal frame research has identified three core framing tasks played by textual content that is meant to mobilise publics: the diagnostic task helps identify and single out the problem(s) to be addressed; the prognostic task concerns solutions for these problems, and the motivational one provides a rationale for engaging in collective action (Benford and Snow, 2000). These framing dynamics can be seen as functional to signpost broader value systems that define justice (i.e., what is right and wrong), identity (i.e., us versus them) and agency (i.e., what can be done to produce social change) (Gamson, 1995; Vicari, 2010). Drawing from Vicari [4], this study uses a textual analysis “to capture the multilayered relations among frames, concepts, and words”. Specifically, it identifies the motivational frames developed through #darbeyehayir, which may have played a role in convincing citizens to participate in anti-coup protests.

 

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Networked framing on Twitter

According to Meraz and Papacharissi (2013), framing differs on Twitter from traditional media due to the 280-character limit. For example, tweeters create hashtags linked to breaking news stories and events, engaging with the construction of a shared sense of meaning and creating common political discourses, structures and aims (Dahlberg-Grundberg and Lindgren, 2014). Papacharissi (2016) found that crowds generated interpretative frames through the use of words like ‘Egyptian’, ‘Egypt’ and ‘Mubarak’. Networked publics framed the movement in Egypt as ‘a revolution’ through retweeting processes. In a similar vein, the U.S. Million Hoodies Movement used social media to frame issues relating to the racial injustice experienced by African Americans, with a view to mobilising supporters in the aftermath of the murder of Trayvon Martin in February 2012 (Hon, 2016).

Xiong, et al. (2019) applied framing theory to explore how Twitter was used for mobilisation purposes by the #MeToo movement. They found that feminist issues became more salient through online discussions revolving around terms such as ‘sexual harassment’, ‘women’, ‘story’ and ‘survivor’ (Xiong, et al., 2019). This illustrates how hashtags capture the attention of tweeters in such a way as that aids the mobilisation of support for social movements and advocacy campaigns (Xiong, et al., 2019). Research indicates that hashtags can be extremely effective in presencing specific narratives, which are often curated by non-elite actors (Meraz and Papacharissi, 2013; Jackson and Foucault Welles, 2016; Vicari, 2017; Reilly and Vicari, 2021).

 

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Hashtag activism in Turkey

This study adds to the literature on hashtag publics by exploring how Twitter was used during contentious public events in Turkey. The most recently available data shows that there are 54 million active Turkish social media users, constituting 64 percent of the total population (Kemp, 2020). A survey of weekly news consumption in 2020 showed that Turkish citizens prefer to access news via online sources (including social media), which had a reach of 85 percent of those sampled in the study (Newman, et al., 2020). This was followed by television, which had a reach of 68 percent, social media only (58 percent), and print media (42 percent). In this context, hashtag activism has proven increasingly popular among those seeking to publicise political causes in Turkey.

Probably the most well-known examples to date were #OccupyGezi and #Direngeziparki, which were used to mobilise opposition campaign against plans to turn Gezi Park into a shopping centre in 2013 (Mercea, et al., 2018). Environmental activists used the microblogging site to share information about the unfolding events and to call citizens to participate in the protests (Ozturkcan, et al., 2017). Scholars such as Tufekci (2017) argued that the speed with which the Gezi Park movement was built online and the millions of people who participated in the protests, demonstrated the transformative power of these ‘digital tools’. Similarly, Mercea, et al. (2018) found that Twitter was used to document and memorialise the mass demonstrations across Turkey in support of this movement. Twitter activists built momentum for the Gezi Park campaign through online discussions with their peers and encouraging others to ascribe to a shared social identity around the movement. The use of Twitter to memorialise the Gezi demonstrations helped sustain the symbolic legacy of the protests, as well as highlight their ongoing relevance to modern Turkish society.

 

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15 July ‘coup’ attempt and anti-coup protest

Twitter was once again used by activists to encourage public participation in street protests during the ‘coup’ attempt in July 2016, albeit for very different ideological reasons to #OccupyGezi. On 15 July 2016, units of the Turkish army tried to take control of the Turkish government, state institutions, key communication points and national media (Haugom, 2019; Iseri, et al., 2019). In response, President Recep Tayyip Erdoğan and the AK Party leadership used social media to mobilise citizens against the ‘coup’ attempt (Esen and Gumuscu, 2017; Karagöz and Kandemı, 2016). The opposition parties supported these efforts to mobilise citizens to engage in street protests against the ‘coup plotters’. The Republican People’s Party (or Cumhuriyet Halk Partisi [CHP], the main opposition party), released a public statement condemning the ‘coup’, with its lawmakers articulating this position in the Turkish Parliament (Esen and Gumuscu, 2017). During this period, online platforms such as Facebook and Twitter played an important role in coordinating and publicising street protests (Karagöz and Kandemır, 2016). Both pro and anti-government TV news networks disseminated information about anti-‘coup’ demonstrations, providing a platform for politicians from both AK and the other parties to articulate their opposition to these events (Akin, 2017). Supporters of President Erdoğan played a key role in the street protests, preventing the ‘coup’ organisers from gaining access to areas of strategic importance such as the Parliament building and the National Intelligence Agency (Esen and Gumuscu, 2017).

Social media users appeared to have played a key role in sharing information which mobilised the anti-coup protesters (Esen and Gumuscu, 2017). Networked publics coalescing around several protest-related hashtags (Yildiz and Smets, 2019). Users living in Ankara (where the ‘coup’ started) shared pictures and videos of ‘pro-coup’ soldiers and F-16 fighter jets flying over residential areas (Karagöz and Kandemır, 2016). Between 15 and 19 July 2016, an estimated 51 million tweets were posted about the ‘coup’, peaking on 16 July (Mis, et al., 2016). Following President Erdoğan’s appearance on CNN Turk television network, where he urged Turkish citizens to take to the streets via FaceTime, an estimated 20 million tweets were posted on 16 July (Mis, et al., 2016; Yanardagoglu, 2017). Twitter was used to share logistical information (date, location, and time) for the anti-coup protests. As a result, Twitter traffic was 35 times higher than normal for Turkey, with tweeters shared half a million tweets through anti-coup hashtags such as #NoCoupinTurkey, #darbeyehayir (#NoCoup), #nedarbenediktatörlük (#neitherblownordictatorship) and #UyumuyoruzÇünkü (#wedidnotsleepbecause) on the night of the ‘coup’ attempt (Esen and Gumuscu, 2017).

To provide insight into the way hashtags promote reactionary discourses during times of social contention, this study addresses the following research question: How were motivational discourses developed through the use of pro-Erdoğan Twitter hashtag #darbeyehayir during the 2016 attempted ‘coup’ in Turkey?

 

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Data and methods

This study builds on previous research which used networked framing theory to explore how hashtag publics operate during contentious political events and campaigns (Meraz and Papacharissi, 2013; Vicari, 2017; Molina, 2019; Pöyhtäri, et al., 2021). However, these studies did not examine the use of protest-related hashtags to mobilise popular support for governments during civil unrest. This study used a mixed methods approach to explore networked framing processes through the hashtag #darbeyehayir (nocoup), specifically focusing on motivational frames, namely, frames used to call for action and provide a rationale for those participating in the anti-coup protests.

A historical search was launched via Sifter [5], a programme which relied on the Gnip application for firehouse access to Twitter data and allowed researchers to search and retrieve every undeleted tweet in the history of the platform (Hernandez-Suarez, et al., 2018). A total of 277,964 #darbeyehayir tweets, posted between 15 and 19 July 2016 were collected for this study. These data were transferred into text-mining software DiscoverText which is an application that allows users to code and mine social media content (Shulman, 2011) [6]. The process of data cleansing was implemented to improve data quality. Tweets written in languages other than English and Turkish, such as German, Arabic, and Dutch, were excluded from the final dataset. The study also removed deleted and suspended accounts’ tweets, as well as broken media URL connections. This resulted in 27,742 tweets being removed, leaving a final dataset of 250,222 tweets. ‘Duplicate groups’ were created in order to identify those tweets that were retweeted or duplicated at least once (e.g., copy-pasting the exact tweet content). This resulted in a corpus of 10,953 original tweets [7], allowing us to carry out an analysis of tweets that received attention from more than one user.

The motivational frames in #darbeyehayir were identified by identifying the most frequently used words in the corpus and analysing tweets containing them. This approach was based on the idea that frames were created via the strategic use or omission of specific words and phrases (Entman, 1993). The top ten most used words under the hashtag were identified as ‘coup’, ‘country’, ‘nation’, ‘God’, ‘democracy’, ‘Turkey’, ‘public’, ‘Turkish’, ‘protection’, and ‘unity’. Table 1 shows their frequency of use.

 

Table 1: Top 10 most used words in #DarbeyeHayir tweets.
WordFrequency
Darbe (Coup)1,129
Vatan (Country)621
Millet (Nation)485
Allah (God)441
Demokrasi (democracy)408
Türkiye (Turkey)377
Halk (Public)294
Türk (Turkish)285
Korusun (Protection)224
Birlik (Unity)216

 

In order to identify motivational frames, this study examined the meaning and use of those words to understand how they were encouraging citizens to join the anti-coup protest: we repeatedly read the tweets containing these words and grouped them according to broad emerging frames [8]. For example, it was observed that words such as ‘God’ and ‘nation’ were often used together to encourage citizens in the protests. Studies focusing on nationalist discourses in Turkey have highlighted that these discourses often incorporate religious elements to gain consensus from the Muslim population in the country (Copeaux, 2002). Therefore, based on our reading of the tweets and the existing literature, we grouped tweets building motivational discourses through the combination of nationalist and religious rhetoric under a broad motivational frame, which we labelled as ‘love for the nation’. In the end, we identified three broad frames playing a motivational task: ‘love for the nation’ (primarily built through the use of the words ‘God’, ‘nation’, ‘Turkey’ (or ‘Turkish’), and ‘protection’); ‘unity and solidarity’ (primarily built through the use of the words ‘Turkey’, ‘unity’, ‘public’, ‘nation’, and ‘country’); and ‘democracy’ (primarily built through the use of the words ‘democracy’ and ‘protection’).

The study received ethics approval from the host institution prior to data collection. Our ethical stance was informed by the most recent iteration of the AoIR guidelines (franzke, et al., 2019), Since the study was based on textual analysis, anonymising Twitter usernames and other personal information would not affect the results. Therefore, personal data such as usernames, identification numbers, location data, online identifiers, and tweet identification numbers were not shared and the study used pseudonyms, removing identifying information and paraphrasing quotations in a way that retained meaning for anonymisation and confidentiality (Reilly and Trevisan, 2016). The usernames of public figures (e.g., Galatasaray FC) were however used throughout the study.

 

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Results

#darbeyehayir, 15–19 July 2016

The majority of the 250,222 posts in the corpus were retweets or modified tweets (N=180,001), followed by original tweets (N=70,221) (see Figure 1).

 

User participation by number of tweets and retweets
 
Figure 1: User participation by number of tweets and retweets.

 

The retweet function is frequently used to indicate support for, or agreement with, the original post during political events (Giglietto and Lee, 2017; LeFebvre and Armstrong, 2018). This was probably the case during the anti-coup protests, when tweeters shared posts encouraging others to participate in the street protests in support of Erdoğan and his government. This finding also suggests that most contributors to the hashtag did not share their own personal perspectives on the protests.

The five most retweeted posts accounted for 10.66 percent of the entire dataset. The accounts responsible for these posts tended to have millions of followers and included a number of well-known sporting and political institutions from Turkey (see Table 2).

 

Table 2: Most retweeted #darbeyehayir tweets.
UsernameUser categoryUser bioEnglish translation of tweetsFollow countRetweet count
GalatasaraySKInstitutional actorA Turkish professional football clubWe stand by democracy.9.6M8,603
tcbestepeInstitutional actorPresidency of the Republic of TurkeyThe children of the nation, who exhibited a domestic and national stance, protected the TRT and the General Staff.8.2M7,727
AtillaTasNetCelebrityTurkish singer, actor, TV presenter and columnistCould it be that Turkish soldiers bombed the Grand National Assembly of Turkey? Could it be such nonsense?2M3,644
aylak_adamSocial media influencerA highly visible media figure on TwitterThere is no political opinion today, there is only the state and the nation.493.4K3,495
yenisafakwriterJournalistProfessor, writer, and columnist for a conservative Turkish daily newspaperThis is independence and a future war! Turkey resists sleep! And Lord! The traitors are wretched! 469K3,221

 

These tweets frequently contained emotive words such as ‘nation’, ‘independence’, and ‘democracy’; it is reasonable to presume that these actors were using their Twitter accounts to encourage citizens to participate in the protests. For example, the institutional actor tcbestepe (Turkey government organization) and the celebrity AtillaTasNet tweeted information about the bombing of the Grand National Assembly of Turkey on 16 July, using emotive terms like ‘national stance’ to characterise this as an attack on the Turkish nation. The Grand National Assembly of Turkey (Türkiye Büyük Millet Meclisi or TBMM) and other state buildings were bombed by ‘coup plotters’.

By sharing information about this event, tweeters shared messages about ‘independence’ and ‘democracy’, the core principles of TBMM, in order to call on Turkish citizens to participate in the anti-coup protests. Given that tcbestepe was an official government account, it is perhaps not surprising to learn that it tweeted nationalistic messages urging citizens to take to the streets to oppose the ‘plotters’. In the remainder of the paper, we will discuss how the discursive elements emerging in these top retweeted messages resurfaced across the entire #darbeyehayir Twitter stream through what we have identified as three broad motivational frames: ‘love for the nation’, ‘unity and solidarity’, and ‘democracy’. The analysis below focuses on the entire corpus of 10,953 original tweets that were retweeted or duplicated at least once between 15 and 19 July 2016.

Networked framing dynamics for #darbeyehayir

As mentioned earlier, tweeters frequently used at least one of three frames to mobilise others to act against the ‘coup’ attempt, which we label here as ‘love for the nation’, ‘unity and solidarity’, and ‘democracy’. These motivational frames selected different aspects of the events and made them more notable by foregrounding specific information related to those aspects during the protest (see Figure 2).

 

Frames used to encourage citizen participation in anti-coup protests
 
Figure 2: Frames used to encourage citizen participation in anti-coup protests.

 

Love for the nation

The most prominent frame in the corpus built on the idea of patriotism, urging Turkish citizens to demonstrate their national identity by participating in anti-coup protests. In effect, love for the ‘Turkish nation’ was conflated with the patriotic duty to mobilise against the coup plotters and to support Erdoğan. It was found that the love for the nation frame was the most mentioned of tweets (67 percent) showing a motivational task. For example:

Anyone who loves their country, their state, and feels a sense of belonging to this nation should stand upright against the coup #darbeyehayir (User1, 11.19am, 6 July 2016).

Anyone who loves their country, whether pro-government or not, should not provide support for the coup attempt and stand against the coup! #darbeyehayir (User2, 10.11pm, 15 July 2016).

The example tweets were evidence of orchestration by pro-Erdoğan tweeters who used the same opening phrase “anyone who loves their country” to mobilise others to participate in the protests. Pro-Erdoğan tweeters were also claimed that if the ‘coup’ was successful, the Turkish nation would be destroyed. By posting messages like ‘if you love your nation, come to the streets’, pro-Erdoğan tweeters created an emotional pull encourage citizens to participate in anti-coup protests. Some tweeters went further in conflating love of the Turkish nation with support for Erdoğan and the AK Party:

Tonight, is the day of the conflict between truth and lies! Victory belongs to the believers. People who love their country and the AK Party should stand up against the coup! #darbeyehayir (User3, 8.54pm, 15 July 2016).

The implication was that Turkish citizens who didn’t mobilise in support of the Erdoğan government were unpatriotic. Many of these pro-Erdoğan tweeters shared images of national symbols such as the Turkish flag, as well as pictures of people protesting in the streets holding these flags. This illustrated how images of national symbols were being used to provoke emotional responses among social media users, a trend noted in the literature on how protest imagery is circulated by activists via online platforms in order to mobilise supporters (Reilly, 2015; Veneti, 2017). Tweeters were also urged to change their profile pictures to images such as the Turkish flag and President Erdoğan to demonstrate their patriotism:

This is the only picture that suits profiles today. Change it. You will not be able to separate these hands. You will not break this nation #darbeyehayir [alongside a picture of the Turkish flag and connecting hands] (User4, 2.03am, 16 July 2016).

Let’s make profiles a picture of Erdoğan and Turkish Flag #darbeyehayir [alongside a picture of Erdogan and the Turkish flag] (User5, 6.30am, 16 July 2016).

Love for the nation was likely invoked to manufacture a sense of solidarity around the nationalist emblems and symbols such as the images of Turkish flags. President Erdoğan was in effect considered synonymous with the nation in these tweets. Hence, Turkish citizens had a moral obligation to protect the nation from the threat posed by the coup plotters. Pro-Erdoğan tweeters used this hashtag as part of their efforts to create a distinction between ‘the nation’ and its enemies. Erdoğan supporters framed the people who they thought were involved in the ‘coup’ attempt as enemies of the nation, calling them ‘traitors’ and ‘terrorists’. This resonates with previous research which suggested that a narrative differentiating ‘the nation’ from ‘its enemies’ was deployed to support the Erdoğan government during this period (Bulut and Yörük, 2017).

Unity and solidarity

twenty-three percent of the tweets within the dataset invoked unity and solidarity in an effort to mobilise citizens to join the ‘anti-coup’ protests. These tweets highlighted the moral imperative to protect the Erdoğan government from the plotters through emotive phrases like ‘today is the day of solidarity and day of unity’ and ‘whatever our ideas, opinions, and ethnicity, we should protect our country as all of Turkey’. Tweeters were urged to support the anti-coup demonstrations as an act of patriotism in defence of ‘the Turkish nation’. These tweets tried to motivate people to participate in the protests by emphasising the importance of unity and solidarity against the coup. For instance:

Today is the day of solidarity and day of unity!!! Whatever our ideas, opinions, and ethnicity, we should protect our country as all of Turkey #darbeyehayir (User6, 11.38pm, 15 July 2016).

Today is the day of unity and solidarity for all of us #darbeyehayir (User7, 9.17pm, 16 July 2016).

Frequent references to ‘citizens of Turkey’ underpinned posts which called for unity and solidarity among Turks opposing the coup. The emphasis on Turkish identity might have linked individuals or groups, enhancing citizen participation in the protests (Benford and Snow, 2000). Tweeters often shared images of protesting people across Turkey to demonstrate the unity and solidarity among citizens. The text accompanying these images typically noted the location of protests and the unity and solidarity among protesters, for example: ‘As of the moment of Turkish unity in Sivas, Turkey’, ‘Fifth day of citizens’ solidarity in Çorum’, and ‘Turkish solidarity continues on the 4th day in Çanakkale Pier Square, Turkey’. This suggests that these images played a role in the demonstration of public resistance and the unity and solidarity among citizens during the coup. Sharing images of the protesters had the most likely aim of motivating citizens to participate in the protests. In addition, politicians used this hashtag to call for national unity in the face of the coup and to urge citizens to join anti-coup protests. These included both pro- and anti-Erdoğan political figures, such as Kemal Kilicdaroglu, leader of the opposition Republican People’s Party; Devlet Bahceli, leader of the Nationalist Movement Party (an opposition party in an electoral alliance with the ruling Justice and Development Party); and Erdoğan.

Democracy as an essential model

While the threat to the Turkish nation was highlighted, there was also an existential ‘threat to democracy’ cited in these tweets, which were asking citizens to support the anti-coup protest. The findings indicate that 10 percent of the tweets in the dataset emphasised how the coup threatened ‘Turkish democracy’. For instance:

The only solution against any military or civilian coup is democracy #darbeyehayir (User8, 3.55am, 16 July 2016).

I urge our nation to stand by democracy, to have its will, and go out into the streets in order to reject the coup attempt #darbeyehayir (User9, 9.44 pm, 15 July 2016).

Members of the Republican People’s Party (Cumhuriyet Halk Partisi or CHP, the main opposition party in Turkey) also framed the coup as a genuine threat to ‘Turkish democracy’ on Twitter. Pro-CHP tweeters engaged in the discussion about the ‘coup’ as a ‘threat to democracy’ and called for citizens to become involved in the protests to ‘sustain democracy’ in Turkey. Pro-CHP tweeters frequently shared images showing the damaged parts of the parliament building after the attack of the ‘coup plotters’. Those images conveyed emotionally arousing content; the sole body of the Turkish Constitution was ruined, windows were broken, most of the building were destroyed — this might have motivated other users. These images posted by highlighting the necessity of participation in the protests to protect democracy, which is the core principle of TBMM.

Previous military coups were also often mentioned in posts encouraging others to take to the streets in support of Erdoğan:

If you don’t go out on the street, you are allowing democracy to disappear, as in the days previous coups (User10, 11.00 pm, 16 July 2016).

These tweets often compared the results of past coups with the possible effects of the latest ‘coup’ attempt on people’s lives, especially on ‘Turkish democracy’. They were leveraging collective memories of these coups in order to convince Turkish citizens in 2016 that they were likely to face a similar fate unless they took action now.

 

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Conclusion

This study examined the most popular frames used by the #darbeyehayir public in encouraging participation in the 2016 anti-coup protests in Turkey. While much previous research has focused on how non-elites benefit from the affordances of online platforms, this research demonstrates how political elites can mobilise hashtag publics for their own political purposes and benefits. More specifically, this article illustrated the framing dynamics emerging in hashtags publics in which pro-Erdoğan supporters were dominant and used this process to provide support to the government during the ‘coup’. Pro-Erdoğan tweeters invoked ‘love for the nation’, ‘unity and solidarity’, and ‘democracy’ in tweets designed to elicit emotional responses from citizens.

The rhetoric of ‘love for the nation’ was more frequently highlighted than other frames by tweeters in order to motivate others to participate in protests. Turkish citizens were being told that Erdoğan was synonymous with the nation, and therefore they needed to take to the streets to protect him from coup plotters. In Turkish politics, nationalism has been a powerful force since the foundation of the Republic (Cagaptay and Aktas, 2017). Nationalism is placed at the centre of the ideological orientation of the AK Party (Erdoğan’s party) and is a critical element of its hegemonic strategy (Saraçoğlu and Demirkol, 2015). Therefore, during the protests, nationalism was frequently highlighted by pro-Erdoğan supporters; it was inevitable that these tweeters would use nationalist sentiments due to it being part of AK Party’s ideology.

The frame of ‘unity and solidarity’ was also frequently used to encourage citizens to participate in anti-coup protests. Tweeters highlighted the threat to a shared Turkish identity, to which both supporters and opponents of Erdoğan could (and should) subscribe to. The emphasis on Turkish identity might have linked individuals or groups, enhancing citizen participation in protests (Benford and Snow, 2000). In collective actions, people categorise themselves as being part of different social groups, such as along national and religious lines (Tajfel and Turner, 2001). Therefore, one interpretation of this finding is that pro-Erdoğan tweeters were asking Turkish citizens to decide whether they would support Erdoğan and Turkish democracy or side with the enemies of the nation. It seems that this ‘collective sense of self’ defined who the protesters were and what they stood for, during the events following the attempted ‘coup’ (Gerbaudo and Treré, 2015). As highlighted by Gamson (1995), in collective action frames the identity component is concerned with the process of defining ‘we’ as opposed to ‘them’, who typically have different values or interests. Movements negotiate and elaborate on this meaning over time, and perhaps even make the question of ‘who we are’ a significant part of their discourse (Gamson, 1995). This study also demonstrated how people using the hashtag were able to promote the identity of being part of Turkish society by applying the frame of ‘unity and solidarity’ during the protests.

The findings indicate that most tweeters framed the ‘coup’ as a threat to democracy. They posted tweets with the emphasis on ‘democracy’ as an essential model and rejected the military coup. Tweeters who were in favour of the opposition Republican Peoples’ Party (CHP) frequently posted tweets to demand the protection of democracy during the ‘coup’ attempt. The CHP describes itself as ‘a modern social democratic party’, and members of this party always highlighted the importance of the continuity of democracy in Turkey. For example, the CHP defended the rights of minorities and women in Turkey ‘to deepen democracy’ (Heper, 2002).

During the protests, pro-CHP supporters also framed the idea that the only solution to the ‘coup’ attempt was ‘democracy’, to protect the elected parliament in Turkey. The opposition party and its supporters reinforced the mobilisation of citizens against the ‘coup’. This is not because the opposition suddenly decided to support Erdoğan (Cagaptay, 2018) but possibly because they believed that if the ‘coup’ was successful, Turkey would become a country ruled by generals (Cagaptay and Jeffrey, 2016). In sum, the study demonstrated that the hashtag was reactive and often reactionary and used as a tool for government propaganda. The examination of #darbeyehayir showed that hashtag activism research specifically focusing on progressive protests is insufficient to provide a comprehensive picture of the type of ‘activism’ that is often observed during moments of heightened social contention, like the anti-coup protests examined here. In doing so, it draws attention to the need to further develop research into hashtag activism that is not necessarily progressive or ‘left leaning’, as recently suggested by Freelon, et al. (2020).

This study has some limitations. First, the social media data analysed were limited to posts tagged #darbeyehayir. However, social media users created and used different hashtags during the coup period; therefore, the examination of the hashtag is not representative of all the social media activity of the Turkish population during this period. Secondly, our data collection method only provided tweets including the specific hashtag, hence ‘replies’ to hashtagged tweets were not collected unless they themselves contained the hashtag. It is certain that more private social platforms like Facebook and WhatsApp were used during the coup and subsequent protests.

It is neither offered nor claimed that this study is a complete overview of everything that tweeters shared on Twitter during the coup period. The focus of future studies should be on the examination of other Twitter hashtags created and used during the coup to give a better understanding of the content shared more widely on the platform. Besides, it needs to be acknowledged that the method of textual analysis was limited in terms of understanding responses to social media content. Therefore, future studies should focus on audiences to explore why people participated in protests and whether Twitter or other online platforms played any role in the mobilisation. End of article

 

About the authors

Semra Demirdis is a lecturer at Cankiri Karatekin University in Cankiri, Turkey.
Direct comments to: semrademirdis [at] karatekin [dot] edu [dot] tr

Stefania Vicari is a senior lecturer in digital sociology in the Department of Sociological Studies at the University of Sheffield (United Kingdom).
E-mail: s [dot] vicari [at] sheffield [dot] ac [dot] uk

Paul Reilly is a senior lecturer in communications, media & democracy in the School of Social and Political Sciences at University of Glasgow (Scotland).
E-mail: Paul [dot] Reilly [at] glasgow [dot] ac [dot] uk

 

Notes

1. O’Reilly and Milstein, 2012, p. 43.

2. boyd, 2010, p. 41.

3. Entman, 1993, p. 52.

4. Vicari, 2010, p. 505.

5. Sifter is no longer available due to changes in Twitter’s terms and conditions.

6. DiscoverText no longer has access to the full API.

7. The original tweets included @replies.

8. These frames were not mutually exclusive; a tweet could be coded with more than one frame.

 

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Editorial history

Received 19 November 2022; accepted 11 January 2023.


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Hashtag publics, networked framing and the July 2016 ‘coup’ in Turkey
by Semra Demirdis, Stefania Vicari, and Paul Reilly.
First Monday, Volume 28, Number 3 - 6 March 2023
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