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On December 28, 2017, protests erupted throughout several cities in Iran. Initially, protesters showed their dissatisfaction toward rising prices, unemployment, and economic discrimination. They blamed the economic policies of President Hassan Rouhani’s government. However, after spreading dissent throughout the country, public discontent grew beyond economic issues to include political dissatisfaction as well. Social media such as Twitter played a key role in coordinating the protests and disseminating news to the world. Using content analysis, this exploratory study examines the visual content of Twitter posts (photos and videos) published during the 2017 Iranian protests. The theoretical framework of this study is driven from “dynamic dual path way model of approach coping” that categorizes responses of collective action in emotion-focused and problem-focused coping. Our findings reveal that visual content with efficacy-eliciting characteristics were posted more than emotional arousing contents. Furthermore, visual content with more protest activity are more likely to be retweeted. The implications of this research will be discussed later.
On December 28, 2017, many protests occurred in several cities in Iran. Mashhad, the second most populous city in Iran, was the starting point of these protests. Initially, protesters showed their dissatisfaction toward rising prices, unemployment, and economic discrimination. They attributed these problems to the economic policies of President Hassan Rouhani’s government. However, after spreading dissent throughout the country, public discontent went beyond economic issues to include political problems as well. It should be noted that the occurrence of such protests in Iran has not been unprecedented. In fact, recent protests in Iran could be considered the largest national protests after the 2009 post-election protests, which is known as the Green Movement. However, December 2017 dissents in Iran is different from 2009 post-election protests. First of all, recent protests, unlike the past, did not have a particular leader. Historically, the two major cases of public dissent in Iran, which occurred in 2009 and 1999, were led by the reformists, who did not play a significant role in the recent protests. More importantly, due to this lack of leadership, the recent protests lacked a specific goal. Furthermore, they lacked the participation of intellectuals and the urban middle class. In fact, compared to previous rallies in Iran, most of the protests occurred in small cities and were predominately sustained by young unemployed citizens. The December 2017 protests were also unique in terms of dispersion. The protests took place in more than 100 cities of Iran, particularly in small towns without significant protest history. Despite all these differences, social media like Twitter highly effected both the 2017 and 2009 post-election protests.
According to Encyclopedia Britannica, “Collective action occurs when a number of people work together to achieve some common objective”. In the field of new media studies, many scholars have studied the relationship between social media, especially pertaining to the role of Twitter in collective action. Nevertheless, most of the literature focused on the textual aspect of tweets rather than the visual aspects. To address this gap, this exploratory research investigates visual content shared on Twitter during the December 2017 protests in Iran. This study categories visual content posted on Twitter into two categories: emotionally arousing and efficacy-eliciting. Previous research shows that emotionally arousing content, like violence, can influence behaviour that leads to collective action. A number of researchers have examined the role of Twitter during protests, specifically the content of Arabic text tweets, or the content of images during the 2011 Egyptian revolution. However, no research has been done specifically on the visual content of Twitter posts in Iranian protests. The main objective of this paper is to understand how Iranian protests are portrayed through visual content on Twitter. Particularly, the main emphasis of this research is on emotional arousing and efficacy-eliciting aspects of photos and videos shared on Twitter in the December 2017 protests in Iran.
Activism in The Age of Social Media In the past two decades, the advantages of social networks sites (SNSs) have been applauded by many media specialists. In addition to becoming a regular part of everyday life, SNSs are an effective tool for collective action, particularly for dissidents and protests in different countries. Individuals use their mobile phones not only to take photos or videos, but also to distribute information about what is happening around them. In fact, SNSs change the way people interact with political systems. As Malcolm Gladwell (2010) argues, social media has created an arena for individuals to express their worries and difficulties to politicians more easily than before. In our new cyber space, many social networks like Facebook and Twitter are used as an efficient tool for organizing protests. In this way, SNSs have reshaped civic movements to a new form. Modern communication technologies enable protestors to discuss and share news about their “protest message” with other people around the world. From another perspective, Bennett & Segerberg (2012) introduce the term “connective action, ” which refers to a kind of action based on sharing personalized content through social media. Traditionally, collective action emphasized a collective identity, “community organizing” and “broadcast media campaigning”. However, Bennett & Segerberg argue that today social movements are more personalized and are tailored based on people’s opinions and lifestyles. Changes in media use and the personalization of lifestyles has redefined the way people communicate about politics. This is the concept of “connective action” that explains this change.
The Tunisian uprising in 2011 and the following series of protests known as the “Arab Spring”, can be considered as a milestone in research on the relationship between digital media use and collective action. On one hand, some scholars are skeptical about the role of social media in political activities and do not consider activities such as blogging and tweeting as real political action. On the other hand, many scholars have argued and proved the relationship between media use and collective action. For instance, Zeynep Tufekci and Christopher Wilson’s (2012) study about the Arab Spring in Egypt has verified that people who use social media are more likely to attend the protest. In another study supporting this finding, Gil de Zúñiga, Jung, & Valenzuela found “that social media users are 11 times more likely to participate in demonstrations than non-users”. Additionally, user-generated networks are essential for breaking news. In particular, they are a good environment for citizen journalists to coverage protests and share them in a real-time environment when mainstream media and journalists cannot fully cover the events. Tufekci & Wilson (2012) discovered that approximately half of their respondents were “citizen journalists” who regularly “documented” and shared images of the protests on social media.
Presidential Election results in 2009 led to massive protests in the capital of Iran. On June 13, the day after election, Mahmoud Ahmadinejad was announced as the winner for the second term of his presidency. However, Mir Hossein Mousavi, another election candidate, and his supporters disapproved of the results. They believed that the results were fraudulent and soon the motto “Where is my vote?” circulated among Moussavi’s supporters to demonstrate their dissatisfaction toward the election results. At first, green was used as Mousavi’s campaign symbol after Mohammad Khatami (the former president of Iran) gave a green sash to him. Later, this color became the symbol of the 2009 protests, which are collectively known as the Green Movement Of Iran. Days after the protests, there was still no news coverage about demonstration in formal media in Iran. However, because of the internet, Iranian protesters were able to communicate, organise, and cover the protests themselves. People used the #iranelection hashtag to share the latest news in the 2009 protests. This online activity is also known as “Twitter Revolution”. The government quickly blocked SNSs and restricted access to the Internet. Nevertheless, people continued to use social media such as Facebook and Twitter not only to organize events but also to create their own “narratives”. Despite the differences of protests in 2009 and 2017, social media like Twitter played a significant role in both protests. Over the course of the protests in 2017, protesters used Twitter and Telegram to organize the events. According to Internet Word State, there were over 56 million internet users in 2017 in Iran (69. 1% of the population). It means that more people could participate in content creation and distribution process. However, the government prevented people from internet access either by shutting down internet providers completely and by temporarily shutting down VPN providers or specific social network services (such as Instagram or Telegram).
Moreover, Twitter, Telegram and Instagram in Iran should be considered as alternative media that broke the monopoly of official media in a time of crisis and enabled users to present their message in a local and global environment. However, many social media sites like Twitter, YouTube and Facebook were blocked in Iran after the 2009 post-election protests (Telegram was also banned in Iran at the time of writing this paper). Still, although these sites are blocked, many people, including politicians, continue to use them in order to share information. For instance, President Hassan Rouhani and many parliament members have an official account on Twitter despite the fact that it is blocked within the country. This contradictory behavior shows that the importance of SNSs is undeniable for political activists, citizen journalists, and even politicians. In Iran, images and citizen photojournalism has played an important role in coverage of Iranian protests since 2009 when telephone footage of an Iranian woman killed during a demonstration made its way online and subsequently, into major media outlets. As Mortensen (2011) points out, photojournalism challenges ethical standards of conventional journalism from several perspectives. The format is usually fragmentary and subjective, and both the author and origin of the content is often impossible to track down and verify. Combined with the viral potential of visual content shared on social media, this can create a problematic environment where misinformation, disinformation and biased content can influence and shape public discussion and public opinion. Non-professional images and footage are the only type of user-generated content that is interpreted in a similar fashion to professional content. As a result, many media houses encourage their audiences to send and share such content so it can be incorporated into their stories. In this way, the boundaries between formal and informal crisis reporting are being contested. This only speaks to how important and influential visual content shared by internet users has become. Vvisual social media contente and motivationImages are more easily processed by the human brain than textual or verbal content. One study found that heavy viewers of television not only overestimated the amount of actual violence in the real world but were also more likely to see the world as fearful and to mistrust people in it. Since social networks are heavily image-saturated environments and images have the potential to create negative emotions, they have the potential to contribute to protests. Kharroub & Bas’s (2016) study shows that social media images can sometimes function as inspiration for political activism. Another study demonstrates that videos evoking negative emotions are also more likely to be forwarded than non-emotional videos. Although the viral potential depends on specific circumstances, like the contributor or a group structure, emotional content seems to have the biggest potential of gaining the most attention.
Many theories such intergroup theory, social identity theory, relative deprivation theory, and Klanderman’s resource mobilization model have studied collective action. While each of these theories focuses on different aspects of collective action, Van Zomeren, Spears, Fischer, & Leach (2004) combined different elements of collective action theories into a dual pathway model that explains two types of behavior that lead toward collective action. They considered theories of collective action not as competitors but as complementary to one another. According to their dual pathway model, anger and efficacy are two paths to collective action. Group-based anger refers to an emotion-focused approach. Specifically, relative deprivation and social injustice create anger that leads to emotional responses in collective action. Group-efficacy as a problem-based approach, deals with the efficacy of collective action that can bring social changes. As a matter of fact, emotions like anger do not always lead to collective action. People might also evaluate the efficacy of their actions.
Taken together, previous studies support the notion that social media have a significant impact on collective action and that this role will be increased in the future. Although many studies have studied Twitter’s role in social change and collective action, few have looked at the role of emotional images on collective action. This paper contributes to the existing research by analyzing photos and videos shared on Twitter to examine what themes and discover which type of visual media has the broadest reach. By determining that, we will learn more about the trends and strategies of Twitter users involved in covering the Iranian protests and about the role of Twitter as a medium during the protests.
To understand how Twitter is utilized in the December 2017 protests in Iran, a content analysis of images and photos shared on Twitter was conducted. Berelson (1952) defined content analysis as “a research technique for the objective, systematic, and quantitative description of the manifest content of communication”. Content analysis is also one of the most well-known and suitable tools for e-research. We used this method to analyze images posted on Twitter during the Iranian protests in 2017. Twitter is a free micro blog established in 2004 in which users can share photos, videos and information within 140 characters.
Sample Data collection started from the first day of protests, December 28, 2017, to January 2, 2018. Although the protests continued for almost two weeks, the first seven days were more noticeable in terms of volume of protests. Though convenience sampling, 221 non-repetitive photos and videos were collected. Each visual content needed to meet two conditions in order to be included in the study. First, it needed to show people who were protesting or the presence of any violent element like the army or an injured person. Second, the tweet should be posted within our seven day time frame. The unit of analysis in this study is a single photo or video shared on Twitter. Data was gathered from Twitter’s advanced search system by searching trending hashtags during the one week of protests. Hashtags ‘organize discussion around specific topics or events’. Hashtags in both Persian and English (e. g, #Iranprotests, #Mashhad) were used to gather related photos and videos. Coding schemaThe variables of this study is based on a research conducted by Kharroub and Bas in 2016. However, we modified them according to the different situation of Iran.
According to users’ bio or photo in their twitter profile, we coded three categories of users’ gender (male, female, not mentioned), user’s role (journalist, activists, ordinary user, news agency/organization) and user’s location (Iran, outside of Iran, not mentioned).
Tweet Popularity. Number of retweets were collected in order to define the popularity of shared photos. In Twitter, retweets are commonly accepted as measures of the attention a message receives and the popularity of a tweet.
Time. This indicates on which day of protests the photo or video was published (e. g, first day:12/28, second day: 12/29 etc. ).
Emotionally-arousing. This indicates violence in images. The presence of the police, army, military vehicles, weaponry, fighting and confrontation between protestors and police/army, blood and injured persons were used to create an index of 0 (no violent content) to 6 (presence of all eight items). These six items were adopted from Kharroub and Bas’s (2016) study.
Efficacy-eliciting. This pertains to crowd and protestor activity. Crowd is defined as not containing crowd (presence of 10 or less people), small crowd (presence of 10 to 100 people) and large crowd (presence of 100 people or more). Protestors activity is an indicator for participating in a protest. In this study it consists of the presence of people holding signs, raising their fists, marching, chanting and also the burning or damaging of property. These items were categorized using an index range from 0 (no activities) to 5 (presence of all five activities).
In order to analyze this study’s research questions, frequency distributions, chi-square tests and Spearman correlation tests were conducted. For RQ1, the frequency distribution identifies that efficacy-eliciting contents were prevalent in photos and videos during Iran 2017 protests. Data revealed that efficacy-eliciting contents including crowds and protest activities were shared more than emotionally arousing content (57. 5% and 49. 8% respectively). It can be seen that more than half of Twitter users who reported their gender were male while women comprised only 13% of accounts. RQ2 examines what type of Twitter user shared the most visual content about the protests. Most of users that share visual content about the 2017 Iran protests on Twitter were ordinary users (35. 3%). Another notable finding of this research shows that only 5% of accounts revealed their location as Iran while nearly than half of the users reported or revealed their location in countries other than Iran or do not report it at all (54. 3% and 40. 7% respectively).
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