Abstract

This study aims to examine how the ethnic-based Pashtun Tahafuz Movement (PTM) uses collective action frames on Twitter to define problems, assign blame, convey a plan of action, and inspire participation. Social movement framing theory was the guiding theory of the study. The study employed quantitative content analysis. The analysis of tweets revealed that Pashtun Tahafuz Movement was clear about the issues of the Pashtun community and who was responsible for those issues. However, they have few solutions and remedies to offer that could mitigate those problems. As for motivational framing, the study found Twitter to be a campaigning and information-sharing platform for PTM’s public demonstrations. This study contributes to the social movement literature by highlighting how social media, specifically Twitter, can empower and improve the visibility of the previously excluded community disregarded by the established institutes i.e., legacy media and social institutions.

Key Words

Social movements, activism, social media, Twitter, mobilization

The Origin of the Pashtun Tahafuz Movement

On January 13, 2013, Naqeebullah Mehsud, a 27-year-old tribesman was killed in Karachi by a senior superintendent of police (SSP) Rao Anwar (Baloch, 2018). On 20th January, the same day the probe committee submitted its report, protestors blocked the Superhighway demanding an inquiry into the "fake encounter" of Naqeebullah and others by SSP Rao Anwar. The protest was the first of many and it gave birth to a movement called Pashtun Tahafuz Movement headed by a Pashtun tribesman, Manzoor Pashteen (Khan, 2019). PTM, according to Khan (2019) is a movement demanding the basic rights of Pashtuns and fighting against “injustice.”

This study establishes from the literature and argues that social movements emerge in response to a significant event but they address broader social issues in society (Blevins, Lee, McCabe, & Edgerton, 2019; Xiong, Cho, & Boatwright, 2019). This study examines how the killing of Naqeebullah Mehsud, sparked country-wide protests and initiated a Pashtun rights movement. This study seeks to understand the use of Twitter by the Pashtun Tahafuz Movement to define problems, assign blame, convey a plan of action, and inspire participation.




Pashtun Tahafuz Movement and Social Movements Around the World

As new social movements are emerging throughout the world, scholars are examining the role of social media in these social movements (Himelboim, Smith, Rainie, Shneiderman, & Espina, 2017; Kharroub & Bas, 2016; LeFebvre & Armstrong, 2018; Wang & Chu, 2017).  This research citing the most recent social movements around the world examined how Pashtun Tahafuz Movement is similar or dissimilar to them in its use of social media for its cause. Also, the research pens down the theories and studies that explain the dynamics of social movements and the role of social media in empowering previously excluded communities. For example, some of the recent social movements emerged as a response to some major events. The killing of Michael Brown in Ferguson America by Darren Wilson on August 9, 2014, for example, resulted in riots and protests in different parts of the world referred to as the Ferguson Unrest (Telafaro, 2016).

Building on the suggestion of Jungherr, Schroeder, & Stier (2019), this study would fill the gap in the literature by testing their speculation that digital media helps promote pluralism in public discourse and empower and improve the visibility of the previously excluded community disregarded by the established institutes i.e. legacy media and social institutions.

Research Objectives

? To discern what Pashtun Tahafuz Movement perceives to be the issues the Pashtun community is facing and who are responsible for these problems. 

? To find out what Pashtun Tahafuz Movement perceives to be the solutions and remedies to the identified issues.

? To identify the motivational themes that could have inspired participation by the members of the Pashtun Tahafuz Movement.




Research Questions

RQ1: What are the identified issues and who is responsible for the identified issues by the Pashtun Tahafuz Movement concerning Pashtuns? 

RQ2: What are the identified solutions by Pashtun Tahafuz Movement to the issues?

RQ3: What are the motivational themes used by Pashtun Tahafuz Movement that are shared through Twitter?

Literature Review

As new social movements are emerging across the globe, scholars are examining the role of social media in these movements. On the one hand, literature attests that social media has enhanced the engagement and participation of individuals and groups to collectively address social and political issues in the digital spaces (Himelboim, Smith, Rainie, Shneiderman, & Espina, 2017; LeFebvre & Armstrong, 2018; Wang & Chu, 2017). The networks on social media on the other hand help individuals to disseminate and communicate their contention and ideology to potential participants and opponents effectively (Saeed & Rohde, 2010; Van de Donk, Loader, Nixon, & Rucht, 2004). The current state of knowledge on the concept used in this study, and the theoretical frameworks native to social movements are as follows.




Social Movements

Social movements are the amalgamation of a heterogeneous, decentralized, large group of individuals who share common goals, objectives, or opponents and work collectively to achieve certain goals (Bogad, 2010; Tilly & Wood, 2015). Their opponents are commonly governments and states (Oberschall, 2001). Social movements according to Lim (2018), emerge because of a “complex historic condition evolving and are formed gradually through the everyday building and expansion of social networks and spaces of resistance, a growing diffusion of collective contentions and increasingly articulated and collectively framed claim-making acts”. Modern social movements are an assortment of various “contentious politics” and are independent of space where individuals form a collective identity through solidarity. This, in turn, mobilizes the individuals for collective action (Tilly & Wood, 2015). Political alienation is another cause. When individuals feel powerless, estranged, or hopeless from society, they may participate in a social movement (Johnston, 2013).




Social Movements and Twitter 

This study is specifically looking at Twitter and its role in social movements. Twitter is conceived to be a disorganized, luminal space, where heterogeneous users from different walks of society unite and form temporary relationships disregarding social hierarchies. The interaction of users on Twitter with other users forms complex connections and structures in the "Twittersphere.” This connection indicates patterns of the types of relationships whether formal or informal and reflects the flow of information in a network and what kind of media the users are sharing (audio, visuals, text, hyperlinks) (Himelboim, Smith, Rainie, Shneiderman & Espina 2017).




Collective Action

Collective action is at the centre of social movements. There is not a clear definition of collective action as different disciplines describe it differently. But some concepts are important for understanding collective action. According to Encyclopedia Britannica collective action refers to “action taken together by a group of people whose goal is to enhance their status and achieve a common objective.” A clearer definition comes from Wright, Taylor, & Moghaddam (1990) who argue that an individual engages in collective action "any time she or he acts as a representative of the group and where the action is directed at improving the conditions of the group as a whole.”

Framing and Collective Action

Framing 

For this study purpose, the focus is more on collective action frames: the process and the production of frames.




Collective action frames

Framing can be conceptualized as the construction of meaning by social movement activists. Social movement actors engage in the “production and maintenance of meaning” for bystander publics, antagonists, and constituents (Benford & Snow, 2000, p. 613). The framing concept used in social movements is derived from Goffman's (1974) work. According to Goffman (1974, p. 50), "Framing is a schema of interpretation, a collection of anecdotes and stereotypes, that individuals rely on to understand and respond to events." According to Snow & Benford (2000), one function of the collective action frame is forming meaning and beliefs that are action-oriented and that can legitimize the activities of social movement activity.




How Twitter Aides Social Movements

Twitter in social movements is used for many purposes. Literature suggests the following roles and purposes that Twitter plays in social movements.




To Share Grievances and Form a Collective Identity

McCarthy and Zald (1977) consider grievances to be a crucial resource for the emergence of a social movement. And Twitter gives individuals a space to share grievances with others with the same issues (Wright, 2009). A grievance can be defined as the "feeling of a group or person is experiencing illegitimate inequality, has been the victim of injustice, or feels general moral indignation about some state of affairs” (Klandermans, 1984, p. 261). McCarthy and Zald (1977) argue that discontent produced because of some structural conditions prevalent in a society is a necessary if not a condition of the emergence of a social movement.




Public Gatherings as a Form of Collective Action

Twitter enables online communities with shared grievances to come together in the physical world. Collective action in the form of public gatherings is crucial for social movements. As the literature suggests, the more disruptive actions are the more it gets the attention of governments, outgroups, and bystanders (Wright, 2009). The online presence of a movement, on the other hand, is less likely to challenge the authorities. Street protests demonstrate public power to the authorities (Turner, Hogg, Oakes, Reicher, Wetherell 1987).  Public demonstrations express the symbolic power of a group as different individuals from different walks of life come together to show their grievances in the open (Ganesh & Stohl, 2013; Machado, Scartascini, & Tommasi, 2011).

Theoretical Framework

Social Movement Framing Theory 

This study employs the social movement framing theory (Benford & Snow, 2000). The theory explores the deliberate use of certain symbols and the meanings employed as “communicative strategies” by social movements to suit how they want to be discerned individually and collectively (Liu, Sidhu, Beacom, & Valente, 2017).  These frames “articulate grievances, generate consensus on the importance and forms of collective action to be pursued, and present rationales for their actions and proposed solutions to adherents, bystanders, and antagonists” (Williams, 2004, p. 231).

This theory focuses on how members of a social movement construct frames and symbols that draw support from other users in social media who share their goals and aspirations. Benford and Snow (2000) argued that agents (activists) actively produce and maintain symbols and meanings to present themselves and their cause to the antagonists, supporters, and other public. Individuals and organizations in social movements coordinate grievances and form narratives for the achievement of collective goals.

Social movement framing theory explains how a movement uses certain frames to obtain collective actions. Benford and Snow (2000) identified three methods of framing: Diagnostic framing is used for the diagnosis of issues and their attributes. Prognostic frames focus on the practical steps and strategies to achieve a certain goal. Motivational frames are the tools that move a sympathizer, someone whose attitudes align with a movement to an actor ready to collectively engage in creating change. These frames form the core to mobilize and sustain a social movement. Framing theory through identifying collective action framing can link online activism to offline action (Mare, 2016).

Methodology

The research design of this study is quantitative and the research method is quantitative content analysis. Quantitative content analysis was employed to discern the use of Twitter by the Pashtun Tahafuz Movement for framing.




Data Collection 

This research used NVivo for data collection. Nvivo has a Chrome extension for the retrieval of tweet datasets. Using NVivo, this research captured 47541 tweets in three days. The search keyword was “PTM.”




Sampling 

The study used purposive sampling. This sampling strategy is used in quantitative research when a researcher wants to select an information-rich event to understand a phenomenon.




Sample Size

Only one PTM event was analyzed for this study. Tweet samples were drawn from September 16, 17, and 18. These three dates were chosen to analyze the pre-event, day-of, and day-after tweets of the event.




Unit of Analysis

Individual tweets in the dataset were units of analysis.




Data Analysis

Microsoft Excel was used for the content analysis of the dataset. Excel spreadsheets also worked as a codebook.




Filtering

The first step was filtering the dataset. To make the data readable, easy to analyze, and more representative, the tweets were filtered in the following manner. The filtering was done in Microsoft Excel.

1. Removed retweets;

2. Removed Urdu and Pashto;

3. Deduplication of data;

4. Removed tweets that only contained a hashtag and no text. 

Table 1

Murray's (2020) Definitions of Core Framing Tasks

Frame Characteristics	Indicators
Core Framing Tasks Diagnostic Framing Prognostic Framing	The main problem is identified ?         Responsibility is assigned ?         Elements of "Us & Them" ?         Expressing feelings of injustice ?         Victims are identified Possible solutions to the problem ?         Plan of attack/goals for the movement ?         The actor refutes the solutions of opponents
Motivational Framing	?         Expressing fear ?         Communicating reasons why people should take action ?         Communicating a time limit, urgency ?         Calls for action, i.e. announcements of future events such as demonstrations that are planned to take place in the future ?         Expressing notions of right and wrong ?         Expressing social repercussions for non-action.

Quantitative Content Analysis

Since this study is using social movement theory, deductive content analysis is an appropriate approach because the researcher is testing social movement framing theory in the context of the Pashtun Tahafuz Movement and the theory has pre-defined categories i.e., diagnostic, prognostic, and motivational frames. But, to complete a content analysis, one must pay close attention to unitizing (segmenting the texts for analysis), sampling (choosing an appropriate group of units to investigate), reliability (having various researchers make codes consistently), and validity (using a coding scheme that adequately represents the specified phenomena) (Neuendorf, 2002, p. 10).

Table 2

Major Themes Founded in the Diagnostic Framing

Theme	Description	Example tweets
Violence	The tweet mentions the killing or torture of individual(s)  from the Pashtun community	“This is today’s photo from a PTM  rally in Bannu Pak, against Pak military for the killing of more than 100 thousand people by Pak military."
Missing persons/abduction	The tweet mentions a missing person(s) from the Pashtun community	"This kid came to Mashar @ManzoorPashteen bcoz her father was abducted by Pak Army for 3 to 4 years. She believes that @PashtunTM_Offi is the voice of 4 voiceless ppl."
Terrorism	The tweet mentions the problem of terrorism	"Pakistan Army has been sponsoring, training, and facilitating terror groups for decades."
Oppression	The tweet is about the oppression and repression of Pashtuns	”Pakistani military persecution of #Pashtuns”
Anti-Pashtun policies	The tweet mentions anti-Pashtun policies	The #PTM Bannu power show was a referendum against the insecure security state's anti-Pashtun policies.”

Category Development

The three framing tasks would mean different things to different researchers. So, the initial task was the operationalization of these concepts in accordance with my study. Fortunately, for this study, I found the indicators and definitions of Murray (2020) to be relevant (see Table 1). This was done for finding and focusing on texts that have “in some way or another, problems are identified, causes attributed, blame assigned, solutions proposed, strategies developed, responsibilities defined, incentives given, participation motivated, and so on” (Corbin and Strauss 2008).

Table 3

Major Themes Founded in the Prognostic Framing



The coding was done in two steps. First, using Murray's (2020) definitions, I identified the three core framing tasks in the dataset. The tweets that had at least one frame were divided into three broad categories of diagnostic, prognostic, and motivational frames. In step two, I studied the nature of the tweets identified in step one. Reading through texts, I identified and divided the tweets into subcategories or themes. Diagnostic frames were divided into 5 major themes (see Table 2). Prognostic frames were divided into 4 major themes (see Table 3). Motivational frames were divided into 5 major themes (see Table 4). 

Theme	Description	Example tweets
Political/policy solutions	The tweet demands a policy and political solution	“Pashtuns asking life from same GHQ, policy shift.”
Demand to produce missing persons	The tweet mentions the issue of the missing person(s) from the Pashtun community	"In Bannu, the relatives of the missing persons of the #PTM public have participated in large numbers and demand the extradition of their missing relatives be sentenced to the law if they are guilty, if innocent.”
Demand for rights	The tweet is demanding rights	"From the very first day, our demands are very clear because we want our rights under the umbrella of the Constitution of Pakistan."
Demand for peace	The tweet is demanding peace	“I want peace on my land.”

Table 4

Major themes founded in the motivation framing

Theme	Description	Example tweets
Join/participate	Tweet invited people to join or participate in the PTM demonstration	All are requested invited to join PTM #PashtunLongMarch2Bannu on 12 Jan 2020.”
Reasons why people should take action	Why people should support PTM and take action	PTM time isn't up. It's just beginning. It has become the formidable voice of marginalized & oppressed Pashtuns demanding an end to war & exclusion.`
Slogans	Any kind of slogan	“Long live Pashtun”
Sharing information about the gathering	Tweet share information about the PTM venue, time, routes, weather conditions, etc.	Great Pashtun nation will gather on 12th January against state atrocities at Bannu district"
Media blackout	Tweet about Pakistani media not covering the PTM’s gathering	Thousands of Pashtuns have gathered here demanding their basic Human Rights but Pakistani media are acting like these people are invisible to them.”

Results

General Description of the Dataset

A total of 47541 tweets were captured for data analysis during the 3 days. The dataset was filtered on multiple levels. Fig. 1 illustrates the filtering process. First, retweets were removed which resulted in 4988 original tweets. Next, the original tweets that were in Urdu and Pashto tweets were removed resulting in 1398 tweets remaining. One final step was the deduplication of data. After this step 458 tweets remained and these tweets were analyzed for this study. Moreover, 348 (76%) tweets out of a total dataset of 458 tweets had at least one of the three framing tasks in it. 

Figure 1

Figure 1 shows the filtering processing of the original dataset



Overview of the Framing Data

The dataset revealed that motivational framing (n=213, 61) was the most prominent framing task in the dataset. While prognostic framing (n=40, 12) had the lowest occurrence. Diagnostic framing was found in 95 (27%) tweets. The details of the frames can be found in Table 5.




Table 5

 Summary of frames found in 

Frame	Count	%*
Diagnostic	95	27
Prognostic	40	12
Motivational	213	61

the dataset

Diagnostic Framing

Owing to the theoretical framework of this study RQ1 has two parts to it. Diagnostic framing works both as (a) identification of problems by a social movement and (b) identifying causes i.e. who was held responsible for the problem. This framing task had 95 tweets which make up 27 per cent of the dataset.




Problem Identification:

The content analysis of the tweets revealed the following themes: (1) violence against the Pashtun community, (2) missing persons or abduction of the member(s) of the Pashtun community, (3) terrorism, (4) anti-Pashtun policies and (5) oppression of Pashtuns (Table. 6).

Table 6

Themes found in the diagnostic framing



Violence against the Pashtun community (n = 38, 40): The most prominent theme in the diagnostic framing was the violence against the Pashtun community. This theme included any mention of killing, assassination, or execution of member(s) or torture of the Pashtun community. The tweets in this category talked about how Pashtuns are killed illegally.Missing persons or abduction (n = 22, 23): Tweets containing the mention of missing persons or abduction of the members of the Pashtun community were coded for this theme. Different words were used in these tweets i.e. missing persons, enforced disappearances, or abduction. Terrorism (n = 12, 13): Another notable grievance found in the tweets was that of terrorism. These tweets talked about the problem of terrorism and its impact on the Pashtun community.


Them	Count	%*
Violence against the Pashtun community	38	40
Missing persons or abduction	22	23
Terrorism	12	13
Anti-Pashtun policies	8	8
Oppression of Pashtuns	10	11
Others	5	5




Causes or Attributes

For a tweet to be coded as a diagnostic frame, an actor must be present or identified in the same tweet. To this end, the Pashtun Tahafuz Movement identified the following factors: (1) State, tweets that attributed the problem to the state and its institutes (2) Army, tweets that attributed the problem to Army and its institutes (Table 7).

State, army, and its institutions were said to be responsible for the violence against Pashtuns, anti-Pashtun policies, terrorism in Pashtun areas, for the displacement of Pashtuns because of war.

 Table 7

Problem attribution of diagnostic framing

Theme	Count	%
State and its institutions	57	57
Army and its institutions	43	43

Prognostic Framing

RQ2 which is concerned with prognostic framing deals with the proposed solutions by a movement to their problems. Results found the following themes in this category: (1) political/policy solutions (2) demand to produce missing persons (3) peace (Table 8). This framing task had 40 tweets which make up 12 per cent of the dataset. 

Demand to produce missing persons (n = 16, 40): One of the themes in prognostic framing was PTM demand for producing missing persons and giving them a fair trial. Their solution to the missing person’s problem was that the missing person should be produced and given a fair trial. 

Table 8

Themes found in the prognostic framing



Demand for rights (n = 7):  Tweets in this theme demanded constitutional rights for Pashtuns. Demand for peace (n = 4): Another low-occurring theme was the demand for peace. Policy changes (n = 6): Policy changes were another theme (n = 6). Tweets also included a demand to end anti-Pashtun policies.

Theme	Count	%*
Produce missing persons	16	40
Political/policy solutions	6	15
Demand for Peace	4	10
Demand for rights	7	17.5
Others	7	17.5

Motivational Framing

For RQ3 which is motivational framing, tweets were coded to find a call to arms or rationale for action that goes beyond the diagnosis and prognosis of the problems. This framing task had 213 tweets which make up 61 per cent of the dataset. The results yielded the following themes in this framing (1) Join/participate theme (2) sharing information about the demonstrations(3) media blackout (4) slogans (5) congratulating and thanking people (6) communicating reasons why people should take action (see Table 9). 

Join/participate (n = 57, 27): This theme included tweets that invited people to join or participate in PTM  physical demonstrations in the city of Bannu in Khyber Pakhtunkhwa. In this category, tweets were coded when invitations to participate in PTM demonstrations or news of campaigns were founded. The tweets also included information about different offline campaigns that were initiated to invite people to participate in the gathering.

 Table 9

Themes found in the motivational f






Frame	Count	%*
Join/participate	57	27
Reasons why people should take action	40	19
Slogans	30	14
Sharing information about the gathering	38	18
Media blackout	20	9
Congratulating and thanking people	21	10
Others	7	3

raming

The percentage is out of the data with motivational frames 

Reasons why people should take action (n = 40, 19): Tweets in this theme emphasized the importance of PTM and what it means for the Pashtun community.

Sharing information about the demonstrations (n = 38, 18). In this theme, the tweets share information about the venue and timings. Also, tweets talked about the weather situation. 

Media blackout: Tweets in this theme talked about Pakistani media not covering the PTM’s  Bannu demonstrations (n = 20, 9). These tweets also urged PTM’s activists to use social media in the absence of mainstream coverage of its public gathering.




Discussion and Conclusion

The purpose of this study was to investigate how the Pashtun Tahafuz Movement uses Twitter for identifying problems, propose solutions, and call for action. The study is important because the literature suggests that social movements play a crucial role in facilitating policy formation, social change, and promoting democracy (De Moya & Bravo, 2016).




Diagnostic Framing and Problem Attribution

RQ1 sought to investigate how Pashtun Tahafuz Movement frame their issues and to whom they attribute these issues. The results indicate killing of Pashtuns was the most prominent theme. It is interesting to note that the tweets were framed in a way that showed them to be unlawful by using words like extrajudicial killing, and target killing. This finding is consistent with Black Lives Matter's diagnosis of the killing of African Americans at the hands of police (Clark, Dantzler, & Nickels, 2018 & Nummi, Jennings, & Feagin, 2019). The issue of unlawful killings of Pashtuns was followed by the matter of missing persons. Words like unlawful detentions, and enforced disappearances, were used. Terrorism was cited as another problem that is affecting the Pashtun community. PTM  calls it state-sponsored terrorism. These tweets talked about the problem of terrorism and its impact on the Pashtun community. Oppression and anti-Pashtun policies themes articulated Pashtun grievances regarding the oppression or repression of the Pashtun community because of Pashtun adverse policies of the state. 

As stated before, for a frame to be coded as diagnostic, it must have the actor to whom the blame is assigned. In the problem attribution part of diagnostic framing, PTM is very direct in assigning the blame to only two actors, the state of Pakistan, the army, and its institutions. This is in line with the Black Lives Matter movement's assignment of blame. Black Lives Matter blamed the state for perpetrating violence against black communities in the United States because of the anti-black laws and structures that systematically target black communities (Clark, Dantzler, & Nickels, 2018.)




Prognostic Framing

RQ2 investigated what are the proposed solutions by PTM to the identified problems. The prognostic framing saw the least framing activity. This means that while PTM was well aware of its problems it had fewer suggestions as to how these problems can be mitigated or solved. The most prominent theme in this category is the demand to stop the unlawful killing of Pashtuns. Terrell (2020) reviewing the literature on Black Lives Matter, found the demand to end the illegal killings of Black individuals by law enforcement to be the most popular trend.

For the issue of missing persons, the common solution was to give them missing persons a fair trial. The study found that Pashtun Tahafuz Movement demands that even if the missing Pashtuns are involved in unlawful activities, they should be tried according to the law. The policy change was another identified solution to the problem. The calls for policy change as a solution are found in the Black Lives Matter demands too. Shah & Widjay (2020) noted in their study that Black Lives Matter demanded policy changes that will hold or prevent law enforcement officers accountable.




Motivational Framing

The results of this study show motivational framing to be the dominant framing task; making 61% of the tweets with frames. The most common theme in the motivational framing was the tweets that urged the sympathizers to participate in PTM’s campaign both online and offline. Terrel (2020) called this phenomenon activist rhetoric. According to Terrell (2020), activist rhetoric is a narrative mode that seeks to convince, persuade, and garner engagement. These are the frames that inspire participation or motivate supporters to take action that enable them to achieve some outcomes (Dunivin, Yan, et al., 2022). This study found that the online campaign was to make people participate in a physical demonstration that PTM was holding. 

The second most prominent theme was Pashtun Tahafuz Movement’s reasoning for why people should take action. In this theme, arguments were made as to why people should support Pashtun Tahafuz Movement and participate in the demonstration. PTM was presented as a voice for “the marginalized and oppressed” Pashtun. 

In the theme of sharing information about the gathering, PTM activists disseminated information about the offline demonstration like weather conditions, venue, timing, and speeches of PTM leaders. 

The media blackout of the Pashtun Tahafuz Movement’s coverage was another theme. The media blackout theme called out the media for not giving PTM the coverage. Literature shows that movements have to move offline for visibility (Van Laer, 2010; Fernandez-Planells, et al. 2014). But for offline protests to gain visibility mainstream media has to cover them (McCurdy, 2012). In the case of the Pashtun Tahafuz Movement, their attempt at visibility was hindered by the Pakistani media not covering their demonstrations as one of the categories in Motivational framing suggests.

Limitations

The study has several limitations. First, in the filtering process, languages other than English were removed. Pashtun Tahafuz Movement is regional and ethnic-based and tweets in Pashto and Urdu would have yielded a better understanding of their problems, proposed solutions, and calls to action as the members would have better argued in their native language. 

Secondly, the scope of my study prevented me from employing tools and methodologies that are more compatible when dealing with Twitter.




Future Research

Future researchers can take into consideration the limitations of this study and attempt to explore different aspects of social movements on social media sites. Advanced and more compatible methods and tools should be employed to collect and analyze Twitter data to better understand social movements on Twitter. The native language of a movement should be included and analyzed which would give us unique insights.

Conclusion

There are proponents, opponents, and sceptics when it comes to the effectiveness of social movements on social media. But the ubiquitous presence of social movements on social media cannot be ignored. What this study found was Twitter is a space for the marginalized Pashtun community where they come together to present and have a conversation about the problems of the Pashtun community, propose solutions, and call to action for achieving their goals. This study contributes to the literature on social movements on social media. First, the research contributes to our understanding of marginalized communities on Twitter. Secondly, this research resuscitates the significance of Benford and Snow's (2000) social movement framing theory in understanding social movements--this research found framing in 76% of the tweets. It is suggested that researchers incorporate these findings in keeping up with the evolving nature of digital spaces and study what these spaces mean for communities.  

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