Military Organization’s Use of Social Media and Its Relationship with Politics: Evidence from Pakistan

Abstract

The literature on social media (SM) use in government organizations primarily focuses on service delivery, publicity, and public relations. But, how a public sector security organization’s use of social media is related to electoral politics in a country is least understood. This paper conceptualizes the Pakistani military’s use of digital media, drawing on the theory of organizational impression management (IM). It further explores the impact of military-related social media activists (SMAs) on electoral politics in Pakistan. Structural equation modeling was used to test the conceptual model, demonstrating that the citizens’ connectedness with military-related SMAs is significant and positively associated with their voting realignments during the 2018 elections in Pakistan. The results revealed that the citizens’ greater online political participation increases their likelihood of connecting with military-related SMAs. On the contrary, their engagement with the offline political process reduces the chances of consuming the military’s impression management content over social media.

Keywords

social media social media activists political participation the Pakistani military voting realignments

Introduction

Social media platforms constitute the most visible and prominent social space for public communication. Past studies indicate that public sector organizations use social media for a variety of purposes, such as dissemination of information, interaction with customers, public service delivery, publicity, crisis management, and public relations (Benthaus et al., 2016; Cao et al., 2021; Tran & Bar-Tur, 2020). However, public sector organizations’ use of social media (SM) and its relationship with the country’s electoral politics is least discussed in the literature.

Military organizations in some countries are actively involved in domestic politics, yet, how their use of social media impacts the citizens’ political behaviors is least understood in the literature. In October 2020, the Twitter administration identified and suspended more than 900 Twitter accounts linked to the Royal Thai Army (RTA) engaged in amplifying pro-RTA and pro-government content while engaging in deceptive behaviors targeting prominent political opposition figures (Goldstein et al., 2020; The Reporter, 2020). The military in Myanmar also actively engages itself over social media in what it calls “information combat” by asking the soldiers to make several social media accounts and denounce opponents. The mission of these information operations in Myanmar includes spreading the junta’s view among the population, monitoring dissenters, and attacking them online as traitors (Potkin & Lone, 2021). Reports suggest that the military members in Myanmar were prime operatives behind a systematic campaign on Facebook inciting genocide against the Rohingya minority group in 2018 (Mozur, 2018). The military regime in Egypt hires social media influencers for its image-building, masquerading them as organic homegrown support for the junta. Similarly, militaries in other regions have also been mobilizing political discourse to pursue their corporate interests (Djuyandi, 2015; Luo, 2022). The military in Pakistan uses social media skillfully to project its heroic image and discredit its critics, which it terms combating a “fifth-generation warfare” (Rashid, 2021; Syeed, 2019). Other than media reports, there has been no theory-driven empirical analysis of how politically motivated military organizations influence citizens’ political behavior using social media.

We attempt to bring this new insight into the organizational use of social media by investigating how the military in Pakistan, with deep roots in the country’s economy and politics, can use social media (SM) to achieve its political goals. Our study contributes to the literature on democratization and organizational use of digital media from empirical and theoretical perspectives. First, it brings new insights into the role of SM in Pakistan’s politics. Secondly, it introduces and empirically tests a new conceptual construct of Social Media Activists (SMAs) aligned with a military organization. It also investigates the relationship between the military organization’s use of social media and the citizen’s political behaviors.

In the following section, we briefly discuss the literature on the use of social media in public sector organizations from the perspective of impression management theory and draw an analytical framework for the study. Next, we develop hypotheses based on our empirical model. Subsequently, the research methods are explained, and the outcome of statistical analysis are presented. Finally, the results are discussed, and research gaps are identified for future studies.

Literature Review

Public Sector Organization’s Use of Social Media

Social media is a crucial tool in the hands of public sector organizations for sharing public awareness information, activating social networks, supporting communities, and reducing uncertainties during crisis periods such as floods, earthquakes, traffic accidents, and rescue operations (Bonsón et al., 2015; Tran & Bar-Tur, 2020). Business management literature has focused on public organizations’ use of SM related to social customer relationship management, digital advertising, opinion mining, crowdfunding, conducting viral campaigns, and e-recruitments (Springer, 2012). Arshad and Khurram (2020) argue that government presence on social media can stimulate citizens’ political participation. However, electoral dimensions of politics and public sector organizations’ use of social media have primarily remained neglected.

Some studies have employed the theory of organizational impression management (IM) to investigate the corporate use of social media (Benthaus et al., 2016; Schniederjans et al., 2013). Organizational IM is defined as “any action that is intentionally designed and carried out to influence an audience’s perceptions of the organization” (Bolino et al., 2008; Mohamed et al., 1999). Organizations are social actors engaged in enhancing their respectability and impressiveness in front of their constituents.

The traditional aspect of IM research assumes that creating a favorable or “good” image is the objective of impression management. Most of the literature on organizational IM concentrates on presenting a legitimate and proper appearance, ostensibly neglecting the aspects of bad image management or image-spoiling tactics (Yang & Liu, 2017). Amin Mohamed and Gardner (2004) explained that the practice of “image spoiling” is also a legitimate domain of organizational IM theory. Organizations can bolster their image by denigrating the image of competing entities. However, the political dimensions of image spoiling are least understood in the literature.

We conceptualize both image-building and image-spoiling aspects of social media activists related to the military organization in Pakistan using the taxonomy (self/others vs. good/bad) derived from the study of Amin Mohamed and Gardner (2004) (Table 1). Organizations use various means to manage their impressions over social media, including organizational accounts and pages or outsourcing marketing activities to third parties. Sometimes, the organization’s fan following and members of political parties also carry out corporate image-building activities free of charge, known as digital political labor (DPL) (Falasca et al., 2019). Other times, when the IM content demands anonymity, organizations behind it may not reveal their identity. We extend the impression management matrix to the social media domain by adding the means of IM, as shown in Table 1. The good/bad images can be fostered for self and others using social media activists in cyberspace.

Table 1.

The Matrix of Impression Management over Social Media Space.

The objective of impression management	Means of impression management in cyberspace	The target of impression management
The objective of impression management	Means of impression management in cyberspace	Self	Others
Good (image building)	Directly and indirectly aligned social media activists (SMAs)	Highlighting the positive and downplaying the negative
Bad (image spoiling)		Highlighting the negative and downplaying the positive

Source. Derived from the study of Amin Mohamed and Gardner (2004).

Social Media Activists (SMAs) Aligned with the Military in Pakistan

Pakistani military’s management of media affairs has been extensive. Still, surprisingly, little attention has been paid in the past literature about the military’s control of the vast spectrum of media, especially social media. Khan and Pratt (2020) find that the army in Pakistan strategically engages with different segments of society and uses motivational frames of communication to gain public support for its war against terrorism. The Directorate of Inter-Services Public Relations (ISPR) is the formal communication channel of the military. The military runs an official Twitter handle and official Facebook, YouTube, and Instagram pages—each drawing millions of followers (ISPR, 2022, 2023). Nevertheless, the military also operates a vast network of covert media operations. Some accounts claim that the military intelligence agencies co-opt print and TV journalists to toe the official narratives (DW, 2018; Sirrs, 2017). The nature of transactions between the military and co-opted media influencers is not revealed publicly; however, there exists a clientelist relationship between the parties based on mutual benefit (Rahman & Shurong, 2021). In April 2019, Facebook removed “103 pages, accounts, and groups engaged in coordinated inauthentic behavior” originating from Pakistan (Syeed, 2019). These accounts had more than 2.8 million followers. Facebook’s head of cyber security revealed that the people involved in these activities attempted to hide their identities; however, the investigation found that they were linked to ISPR. Many fan pages are aligned with the military narratives on various social media platforms, some drawing millions of followers. These fan pages promote similar content aimed at the military’s image-building, political commentary, and rebuking the critics of the Pakistani army (Grossman et al., 2020; Mughal, 2021).

The military in Pakistan uses various techniques to shape public opinion through social media. It runs an internship scheme for the youth as part of its outreach strategy to influence content writers on social media (Malhotra, 2020). The military also “backs several analysts and political commentators that toe the military’s line” (DW, 2018). Over time, the military switches its support for political parties based on its interests; therefore, their media narratives in favor or opposition to political parties also keep changing (Rahman et al., 2022). Some of the social media influencers used for the military’s narrative building during the 2018 elections to promote the military’s ally political party— Pakistan Tehreek-e-Insaaf (PTI)—refused to abandon their support to PTI when the party fell out of favors with the military establishment (RSF, 2023). These social media influencers had built their ideological and financial stakes in PTI, and abandoning them would mean a financial loss due to losing fan following on monetized social media platforms. These social media influencers were persecuted because of their insubordination. Some of them disclosed that intelligence agencies provided documents about the corruption of Pakistan Muslim League-Nawaz (PML-N) leadership (Jahangir, 2022; RSF, 2023). We term social media pages, accounts, and groups across SM platforms contributing to the military’s narrative building as Social Media Activists (SMA’s).

Literature suggests that the citizens connect with different pages, personalities, groups, and political pundits over social media “to satisfy their curiosity and add to their political knowledge”—known as social media activists (SMAs) within the social media space (Kofi Frimpong et al., 2020). In literature, these SMAs are recognized to be affiliated with political parties. However, we extend the discussion to the use of SMAs by a politically entrenched military organization and introduce a new conceptual construct called “SMAs aligned with the military organization” in the case of Pakistan.

Pakistani military uses directly and indirectly associated SMAs to manage its impression over the social media domain. We term social media accounts, pages, and groups formally affiliated with the organization as directly aligned SMAs. In contrast, the indirectly aligned SMAs are those accounts, pages, and groups that are not officially associated with the military but contribute to its image-building and support its organizational narrative over social media. Both types of SMAs can be used to project good/bad impressions about self/others, as shown in Table 2.

Table 2.

Taxonomy of IM Behaviors Expressed by the Military Organization in Pakistan.

Objective of IM	Means of IM	The target of IM (self/others)
Good (image building)	Directly aligned SMAs	Projection of organizational achievements or downplaying of adverse events through social media accounts owned by the organization. Most of the content on the official social media channels of the Pakistani military falls into this category.
Good (image building)	Indirectly aligned SMAs	Projection of organizational achievements or downplaying of adverse events by social media content writers not directly related to the organization, such as the social media channels belonging to retired employees, fake accounts, co-opted social media influencers, and fan pages.
Bad (image spoiling)	Directly aligned SMAs	Propagation of image-spoiling content using SM accounts and pages owned by the organization. DG ISPR’s tweet rejecting the government notification about Dawn Leaks is an example of highlighting the negative of others (Hashim, 2017). The Army Chief’s statement about the government’s economic performance that “growth has picked up, but the debts are sky high” is an example of downplaying the positive of others (K. Hussain, 2017).
Bad (image spoiling)	Indirectly aligned SMAs	Spreading image-spoiling content using social media content writers not directly related to the organization. These indirectly associated SMAs may include both real and fake SM accounts used to spoil others' images. The discovery of hundreds of accounts and pages by the Facebook administration—linked indirectly with Pakistan’s military—engaged in coordinated unauthentic behaviors falls into this category (Syeed, 2019).

Theoretical Framework of the Study

Our study uses a mixed-method approach by first conceptualizing SMAs used by the military organization in Pakistan. The study further investigates citizens’ connectedness with these SMAs and the impact of this connectedness on their political behaviors, as reflected in the framework of the study (Figure 1). Previous studies have used the theory of IM to understand organizational activities in cyberspace (Benthaus et al., 2016; Caliskan & Esen, 2018). Our study contributes to theory building by investigating how military-aligned social media activists are associated with electoral politics in Pakistan. Present research does not test an existing theory. Instead, it attempts theory-building through an explorative study of how the scope of IM theory can be extended to the use of social media in politics.

Figure 1.

Theoretical framework of the study.

Hypothesis Development

Voting Realignments

Voters’ preferences can change either suddenly or over a long period. These (re)alignments can be caused by the upheaval and changes in political structures, systems, ideologies, or national policies and leadership. Key (1955) introduced the term voting realignments for such changes in voters’ preferences for political parties. Social media can influence citizens’ voting choices more effectively through a two-way interaction than traditional media.

The broader phenomenon of connections between politics and social media (SM) is mainstream. However, the influence of SM on voting realignment is least understood in literature, as Kofi Frimpong et al. (2020) pointed out. In Pakistan, citizens connect with media activists in cyberspace. Social media has been found to influence voting patterns (Javid, 2019). We extend the debate into the domain of a politically entrenched military organization by investigating the military’s use of social media for impression management and its relationship with citizens’ voting behavior. Pakistani military establishes clientelistic relationships with political parties to assist them in winning power, as pointed out by Rahman and Shurong (2021) and Mazhar (Aziz, 2007). Citizens’ connectedness with military-related SMAs in Pakistan can influence them to align their voting preferences with parties considered close to the military’s ideology and away from the political parties critical of the military organization (Shurong & Rahman, 2017). Thus:

Hypothesis 1: Citizens’ connectedness with military-aligned SMAs was likely to be positively associated with their voting realignments during the 2018 elections in Pakistan.

Online Political Participation over Social Media

There has been contrasting evidence about the impact of SM on politics. Many studies report a positive association between online political participation (ONPP) and the use of social media (Yamamoto & Morey, 2019). In contrast, others provide contradictory evidence that social media use does not motivate citizens to ONPP (Zhang et al., 2010). Some of the studies indicate that those citizens participate in online politics who are already engaged in offline politics. Citizens interested in engaging with political content in cyberspace are also likely to connect with military organizations’ image-building content over social media due to the partisan nature of the content posted by some military-aligned SMAs. Many social media activists anticipate, appreciate, and justify the military’s role in politics in their social media posts. The more citizens participate in online politics, their chances of connecting with military-aligned SMAs also increase (Yamamoto & Morey, 2019).

Hypothesis 2: Citizen’s online political participation is likely to be positively associated with their connectedness with military-aligned SMAs in Pakistan.

Scherman and Arriagada (2012) conclude that individuals’ news consumption over social media positively relates to their disposition to vote. Past studies have discussed the relationship between online political participation and voting intention, ostensibly neglecting the voting realignments during elections (Kofi Frimpong et al., 2020).

Studies suggest that the structure of interaction imposed by features of SM platforms can reinforce their existing political beliefs. The auto-generated platform algorithms present SM content based on the likings of the users, thus reinforcing their perceptions. This “echo chamber” phenomenon is likely to collect like-minded individuals together, strengthening their existing party affiliations (Shen et al., 2020). Choi et al. (2017) argue that the people who actively participate in online politics over SM are likely to develop more extreme political attitudes over time than those who do not use SM. Therefore, online political participation over social media may strengthen users’ association with their favorite political parties. Thus,

Hypothesis 3: Citizens’ online political participation over social media was likely to be negatively associated with their voting realignments during the 2018 elections in Pakistan.

Offline Political Participation and Use of Social Media

Offline Political Participation (OFPP) is defined in literature as a citizen’s permissible acts aimed to influence or support the selection of persons in government and the actions taken by government officials (Verba et al., 1978).

Offline political participation will likely increase citizens’ interaction with their favorite political parties (Oser et al., 2013). How citizens deeply engaged in traditional offline politics respond to military organizations’ impression management content over social media has remained a relatively unexplored area. This paper attempts to fill this gap in empirical research. The military establishment in Pakistan has been portraying political elites as a corrupt, incompetent, and dishonest cohort who come to power to plunder national wealth (Shaikh, 2009). The citizens who are part of the offline political process and closely integrate with political parties are not likely to be deeply engaged with the military’s image-building content over social media.

Hypothesis 4: The citizen’s offline political participation is likely to be negatively associated with their connectedness to military-aligned SMAs.

Political Disposition

Disposition is “the dominant or prevalent tendency of one’s spirits including natural, mental and emotional condition or mood” (Dictionary, 2021). It refers to a “person’s intentional state of identification” and how persons intentionally identify themselves (Hamlin, 2005).

Political disposition is considered a person’s self-belief about one’s political efficacy, skills, and knowledge. Past studies have examined the impact of social media on single elements of political disposition, such as a person’s political knowledge (Dimitrova et al., 2014) and efficacy (Arshad & Khurram, 2020). We combine the citizens’ perceived political knowledge and skills into a single construct to understand how it affects their tendency to participate in electoral politics.

Reichert (2016) argues that citizens’ political knowledge increases their chances of participating in politics. Since the military organization’s social media activists propagate political content, politically curious minds will likely engage with them in cyberspace. Social media users with solid political dispositions will likely connect with military-related SMAs in Pakistan.

Hypothesis 5: Strong political disposition is likely to be positively related to the connectedness with military-aligned SMAs, as the citizens possessing strong political spirits would seek political knowledge from various online sources, including the military’s image-building content.

Political knowledge is one of the strongest predictors of electoral participation. Political knowledge has been found to influence how citizens decide what party or candidate to vote for (Singh & Roy, 2014). Marquis (2010) found that political knowledge enhances voters’ voting propensity. Corrigall-Brown and Wilkes (2014) argue that media exposure leads to voting because it increases political knowledge. Past literature suggests that citizens possessing more political knowledge and skills will increasingly turn out to vote . However, how it translates into their switching of candidates during elections along partisan lines is largely missing from the literature. We hypothesize that a person’s belief that they have a better understanding of the political situation and policy knowledge will enhance their propensity to vote for their favorite political party in Pakistan (Figure 2). Because they may have already made an informed choice before drawing party lines. Therefore,

Hypothesis 6: Strong political dispositions are likely to be negatively associated with voting realignments. Citizens' perceptions of possessing solid political knowledge and skills will encourage them to stay loyal to their political ideology and party.

Figure 2.

Conceptual model of the study.

Research Methods

Measurements and Data Collection

The construct measurements are primarily drawn from past studies and adapted to the current research context of social media and political participation in Pakistan. The details about construct measurement items, measurement scales, and reference studies are given in Appendix A. The study employed an online questionnaire disseminated via Google Forms through a shareable web link. We used purposive sampling, which included the snowball sampling technique by encouraging the participants to share the survey link with their contacts (Creswell, 2013). The listed-based sampling technique complemented the method (Fricker, 2012). The researchers shared the survey link with personal connections on social media platforms and heterogeneous social media groups and pages related to academia, food, and the fashion industry, drawing participants from all provinces of Pakistan.

Pakistan has witnessed huge internet and social media growth during the last decade. It had 82.9 million internet users (36.5% of the population), and 71.7 million social media users (31.5% of the population), as of January 2022 (Kemp, 2022). Pakistan witnessed a 52% voter turnout (105 million total registered voters) during the 2018 general elections, indicating that the number of social media users (71.7 million) in Pakistan was more than the number of people who turned out to vote (54.6 million). Therefore, social media users were an appropriate representation of the voting population. We selected social media users aged 21 years and older for our survey to ensure they were eligible to vote during the 2018 elections in Pakistan. The study pertains to the use of social media for politics; therefore, SM users are a suitable target population for collecting samples.

The survey was conducted from March 2021 to July 2021. A total of 508 responses was deemed sufficient to make statistical inferences. After data screening and removing significant outliers, 407 responses were selected for further statistical analysis.

Analysis Technique

We employed structural equation modeling (SEM) to test hypothesized relationships. SEM allows the testing of multi-layered models through path analysis in a single run; therefore, it is efficient for such research models as ours (Arshad & Khurram, 2020). Following Gefen et al. (2000), we conducted Confirmatory factor analysis (CFA) and convergent and discriminant validity tests to assess the validity of the measurement model. To validate the appropriateness of our model (five factors), we compared the model fitness indices of our baseline model (five factors) with other models (comprising three and four factors), and the results indicate that the five-factor model fits best. The study used a stepwise modeling approach by first testing the hypothesized model and then including the control variables of age, gender, and education in subsequent models to observe any differences in results.

Using maximum likelihood estimations, we tested the statistical significance of SEM results (bootstrapping with 5,000 subsamples; Bollen & Hoyle, 2012; Kline, 2011). Studies show that the bootstrapping technique alleviates the problems of non-normality in data. Moreover, large sample sizes from 100 to 400 observations can also ease non-normality issues, as pointed out by several researchers (Hair et al., 1998).

Results

Descriptive Statistics

The demographic profile of respondents indicates that Punjab province, which comprises more than 50% of the country’s population, draws the bulk of the samples (Table 3). The data further revealed that half of the respondents voted for PTI during the 2018 elections. PML-N supporters comprised the next largest group (37%). These two political parties were the winners and runners-ups during the 2018 elections in Pakistan. The gender distribution was 55% and 44% for females versus males, compared to their representation of 51% and 48.7%, respectively. Among demographic characteristics, the respondent’s age was the only significant predictor of connectedness with military-aligned SMAs (β = −.161, p < .01) and voting realignments (β = −.123, p < .05) (Table 7). The negative sign of coefficients (β) indicates that the older age groups were less likely to change their voting candidates during the 2018 elections due to the use of social media. The older age groups were also less likely to remain connected with military-aligned SMAs.

Table 3.

Demographic and Voting Party Profile of Respondents.

	Characteristics	Frequency	Percent
Gender	Female	224	55
Gender	Male	183	45
Age	21–30	265	65
	31–40	57	14
	41–50	49	12
	51–60	36	9
Education Level	Higher secondary school certificate	85	21
	Bachelor’s degree	194	48
	Master’s degree	103	25
	PhD degree	21	5
	Others	4	1
Voting Party	PTI	205	50
	PMLN	147	37
	PPP	24	6
	Others	31	7
Province	Punjab	321	79
	Sindh	38	9
	KPK	32	8
	Baluchistan	16	4

Assessment of Measurement Model

The examination of collinearity diagnostics (Table 4) indicates that the value of VIF for all the indicators was within the acceptable range (<3). All the outer loadings of items were between .731 and .917 (Hair et al., 2017). The Cronbach’s α and Jöreskog (1971) CR scores were observed between .795 and .922, indicating the construct’s consistency and reliability. The average variance extracted (AVE) values were found to be from .564 to .748, meaning there were no concerns about convergent validity.

Table 4.

Measurement Model Evaluation.

Indicator	Indicator	Factor loadings	α	CR	AVE	MSV	VIF
Voting realignments	VR1	.797	.821	.821	.605	.306	1.35
	VR2	.774
	VR3	.762
Connections with social media activists aligned with the military	CSMA1	.778	.795	.795	.564	.306	1.66
	CSMA2	.746
	CSMA3	.731
Online political participation	ONPP2	.816	.845	.844	.645	.640	2.94
	ONPP3	.816
	ONPP5	.803
Offline political participation	OFPP2	.850	.922	.922	.748	.640	2.56
	OFPP3	.836
	OFPP6	.855
	OFPP7	.917
Political disposition	PD1	.763	.841	.845	.646	.541	1.66
	PD3	.797
	PD5	.849

Note. The values for AVE, factor loadings, Cronbach’s alpha (α), and CR should be above .5, .6, .7, and .7, respectively. Values for MSV should be lower than AVE for all the variables. Values for VIF should be <3. All factor loadings are significant (at p < .05 levels).

We used traditional Fornell and Larcker (1981) metrics (Table 5) to test discriminant validity. For all the constructs, the square roots of AVE (given in bold in diagonals of Table 5) were compared with their correlations with other constructs. This test indicated that there are no discriminant problems in our structural model.

Table 5.

Fornell-Larcker Test for Discriminant Validity.

	OFPP	VR	SMA	ONPP	PD
OFPP	.865
VR	.421	.778
CSMA	.316	.554	.751
ONPP	.80	.543	.549	.803
PD	.658	.485	.47	.736	.804

Note. The values in bold in diagonals are the square roots of AVEs, while off-diagonal values are their correlations with other constructs.

The fit indices indicate that the model perfectly fits the data. Although the χ² test is significant (χ² = 265.7, df = 137, p = .000), it is sensitive to large sample sizes. Therefore, past studies have not considered it a problem (Arshad & Khurram, 2020; Gefen et al., 2000). All other model fitness indices of model-1 and model-2 given in Table 6 are within the suggested ranges (Hair et al., 2017; Henseler et al., 2015)

Table 6.

Model Fitness Indices.

Parameter estimation index	Model 1 (without controls variables)	Model 2 (with controls variables)	Suggested threshold
CFI	.978	.973	>0.95 excellent; >0.90 normal; >0.80 sometimes allowed
AGFI	.927	.912	>0.80
NFI	.953	.931	>0.90
TLI	.972	.956	>0.90
CMIN/DF	174.3/95 = 1.835	265.7/137 = 1.940	<3 good; <5 sometimes allowed
p-Value	.000	.000	p at most .05 significant
GFI	.949	.936	>0.90
RMSEA	.045	.048	<0.05 good; 0.05–0.10 moderate; >0.10 bad
PCLOSE	.756	. 629	>0.05
SRMR	.034	.043	<0.09

Model and Hypothesis Testing

Table 7 reports the comparison of models about the hypothesized relationships, including critical ratios (t-value), the standardized regression weights (coefficient β), significance (p values), and results for both models. We did not observe any significant change between model 1 (excluding control variables) and model 2 (including control variables).

Table 7.

Model Comparisons for hypothesis testing.

Hypothesis	Constructs	Model-1 (β) excluding control variables	t	Model-2 (β) including control variables	t	Status of hypothesis
H1	SMA → VR	.367**	5.19	.340**	4.782	Supported
H2	ONPP → SMA	.666**	5.053	.693**	5.366	Supported
H3	ONPP → VR	.174*	1.98	.214*	2.445	Not supported
H4	OFPP → SMA	−.383**	−3.973	−.366**	−3.877	Supported
H5	PD → SMA	.223*	2.389	.202*	2.220	Supported
H6	PD → VR	.210*	2.452	.202*	2.430	Not supported
Control	Gen → SMA			−.080	−1.629
Control	Age → SMA			−.161**	−3.063
Control	Edu → SMA			.032	0.619
Control	Gen → VR			.008	0.166
Control	Age → VR			−.123*	−2.487
Control	Edu → VR			.072	1.547

Note: t stands for Critical ratio. Significance values should be smaller than .05, and the critical ratios should be larger than ±1.96.

p < .050. **p < .01.

The construct of voting realignments measured respondents’ perceived change in their voting candidates during the 2018 elections due to the use of social media. The results found that the citizens who consumed more social media content propagated by military-aligned SMAs changed their voting candidates (β = .340, p < .000). Online political participation was strongly and positively associated with netizens’ connection with military-related SMAs (β = .693, p < .000). These results supported hypotheses 1 and 2 of our research model. Our third postulation was that citizens’ political participation over social media is negatively related to their voting realignments. The results did not support this statement, and the citizens’ online political involvement was positively associated with their voting realignments (β = .214, p < .05) during the 2018 elections in Pakistan. The offline political participation had a significant negative relationship with citizens’ connectedness with military-aligned SMAs (β = −.366, p < .000), as predicted by hypothesis 4. Political disposition was positively associated with the citizens’ connectedness with military-aligned SMAs (β = .202, p < .05), validating our hypothesis 5. In hypothesis 6, we predicted a negative association between political disposition and voting realignments, which was rejected. The results revealed a positive relationship (β = .202, p < .05) between political disposition and voting realignments. The citizens with higher political knowledge and skills perceived that social media influenced them to change their voting candidates. Even politically aware citizens also changed their voting candidates during the 2018 elections in Pakistan, and they believed that social media played a role in their voting behavior.

Figure 3 displays SEM output for maximum likelihood estimations and the R² values for two dependent variables, that is, citizen’s connectedness with military-aligned SMAs (.41) and Voting Realignments (.44). Based on the study of Hair et al. (2019), the values of R² in our research are moderate to strong. Our model explains a 41% variation in citizens’ connectedness with military-aligned SMAs and a 44% variation in voting realignments based on social media use.

Figure 3.

SEM output of maximum likelihood estimation.

Discussion

This article uses impression management as an explorative theoretical framework to investigate the Pakistani military’s use of social media and its relationship with electoral politics in the country. It provides a generalizable model for politically motivated military organizations’ image-building and image-spoiling activities. Militaries involved in domestic politics use social media to boost their own image and also engage in deceptive behaviors to spoil the image of their political opponents; however, this aspect lacks a clear understanding. We introduced a new conceptual construct to measure the citizen’s connectedness with military-related social media activists and tested its association with electoral politics through an empirical study. The study extends the scope of organizational IM theory: how a military organization can influence politics while conducting impression management over social media, especially when the organization is linked with the country’s authoritarian past.

The study found that the voters’ connectedness with military-aligned SMAs was positively associated with their voting realignments during the 2018 elections in Pakistan. Social media activists are a critical component of the military’s strategy to shape political discourse in the country. When the citizens connect with these narratives, their choice of voting candidate will likely be influenced. During the 2018 elections in Pakistan, the ruling political party—PMLN—was not on good terms with the military establishment; therefore, a positive relationship between the citizen’s connectedness with the military’s impression management content over social media and citizens’ voting realignment supports ground realities. Social media use has been positively associated with political participation (S. Hussain et al., 2021; Iqbal, 2017; Kofi Frimpong et al., 2020). However, military organizations’ use of social media and its association with politics is least understood in the literature. Pakistan’s military uses formal and informal means to form political narratives that influence public opinion.

The military spokesman conducts regular press briefings, often commenting about politics and the personalities it considers detrimental to the national interest, directly impacting citizens’ perceptions (DW, 2018). The Military also maintains an official presence on all major social media platforms (Facebook, Twitter, YouTube, and Instagram), possessing huge public followings and propagating its views on national issues for the consumption of the public. Army chief frequently interacts with media influencers, revealing off-the-record information, and the media influencers leak this information into the media, quoting them from “powerful sources” (Rahman & Jan 2023). There is also an aspect of covert media operations conducted by intelligence agencies. Influencers in the media industry are co-opted to promote political parties and personalities that suit the “national interests” and expose the elements in politics, media, and society that are working against the “national interests”— as determined by the military in Pakistan (Husain, 2012). There is a Clientelist relationship between the military and media influencers based on mutual benefit. Media influencers get leaked information, career advancements, popularity, and following on social media. There are reports of some journalists being on the payroll of intelligence agencies as well (Grare, 2015). At times, personal information, private telephone conversations, and obscene videotapes of high-profile figures are released on social media to tarnish the image of the targeted individuals. Former Prime Minister Imran Khan claimed that his residence and office security line was breached, and his private conversations were leaked on social media (News Desk, 2022).

The results found that citizens’ online political participation positively relates to their consumption of the military’s image-building campaign over social media. We examined the relationship between social media users’ engagement with military-related social media content and citizens’ broader political participation without ascertaining the impact on partisan politics. Future studies can investigate political party-level connections with military-related SMAs. For example, the voters of which political party remain more connected with military-related SMAs, or the citizens voted for which party because of their voting realignment. Literature on the military’s indulgence in Pakistani politics provides evidence that the military organization establishes clientelistic relationships with political parties and supports them in winning power (Rahman & Shurong, 2021). The military’s support for its favored political parties can extend into cyberspace. Mazhar (2008) and Shah (2014, 2019) extensively examined how the military in Pakistan manipulates the political process through traditional means. Our study provided empirical evidence of how the military’s cyberspace activity relates to Pakistan’s electoral politics.

Our results indicated that the citizens who participated more in online politics also changed their political party affiliations during the 2018 elections, negating the “echo chamber” hypothesis about the use of social media in the case of Pakistan. Possible explanations can be that the more citizens engage with social media, they confront negative press about the ruling political party due to its poor performance. Pakistan has a politically complex social media landscape as many stakeholders contest for online political space, including military organization; vying to influence netizens (T. Ahmad et al., 2019; Siddiqua, 2021). Pakistan has been termed as a hard country to govern (Stewart, 2012). The ruling political parties get discredited during their rule; therefore, citizens’ consumption of political content over social media can make them dissatisfied with the ruling parties, thus shaking the confidence of voters and resulting in voting realignments. No political party in Pakistan has ever won a second term after completing its tenure in office. These findings are reinforced by the results of the 2018 elections in Pakistan, where the incumbent political party (PMLN) lost a sizeable vote bank, and an opposition party (PTI) doubled its vote bank as compared to the previous election (Administrator, 2018).

Offline political participation was found to be negatively related to citizens’ connectedness with military-aligned SMAs, confirming the hypothesis that the citizens’ involvement with the offline political process and their engagement with military-aligned SMAs are antithetical to each other, such that the rise of one can be attributed to the fall for other (Aziz, 2007). Citizens’ support for the democratic political process can reduce their chances of getting influenced by the military’s political narrative. On the contrary, citizens’ alienation from the political process increases the military’s legitimacy to indulge in domestic politics. This result shows that citizens’ involvement in traditional politics can be a panacea for reducing the military’s influence in domestic politics in Pakistan.

Political disposition is considered a citizen’s self-actualization or the belief that they possess political skills and knowledge. Political disposition was significantly and positively associated with the citizens’ connectedness with military-aligned SMAs. Citizens who consider themselves more expert on political matters are likely to engage in different online avenues of political updates to satisfy their curiosity. This result confirms the findings of Dimitrova et al. (2014) that the citizens who demonstrate more political wisdom are likely to participate more in online platforms to abreast themselves with updated political knowledge (T. Ahmad et al., 2019). At the same time, political disposition had a positive and significant relationship with voting realignments in Pakistan. In other words, citizens with political skills and knowledge also perceived that social media influenced them to change their voting candidates. Regular voting realignments of voters in Pakistan may also explain this phenomenon,that the most knowledgeable voters also change their voting candidates in subsequent elections. Social media influenced even politically sound citizens to change their voting candidates during the 2018 elections in Pakistan. Our model explains a 41% variance in citizens’ connectedness with military-aligned SMAs and a 44% variance in voter realignments. Our model’s explanatory power is robust compared to other studies in the field (Arshad & Khurram, 2020).

Conclusion

The study investigates the use of social media by a military organization with an authoritarian past and how its use of social media is related to the country’s electoral politics. The results supported our hypothesis that the citizen’s connectedness with SMAs aligned with the military organization is positively and significantly related to their political behavior in the case of Pakistan. The study brings new insights into a politically entrenched military organization’s social media use for impression management and its relationship with citizens’ political participation and voting realignments. The current understanding of the Pakistani military’s use of social media (SM) and its relationship with politics is inadequate, even though the military in Pakistan uses a vast network of social media operations to influence citizens’ public opinion. Our study’s conceptual framework applies to politicized militaries and far-right political parties that use defensive (image-building) and offensive (image-spoiling) tactics over social media to influence public spheres.

This study provided a counter-democratic view of SM, in that how a security sector organization linked with the country’s authoritarian past relates to the country’s electoral politics. An optimistic perspective is also present about the use of social media and democratization research (Jha & Kodila-Tedika, 2020; Lee et al., 2018). Future studies can investigate political parties’ use of social media activists and their relationship with electoral politics in transitional democracies like Pakistan. Moreover, using the framework and conceptual constructs developed in this study, investigating other politically active military organizations is also an unexplored avenue for future studies.

Footnotes

Appendix

Appendix A.

Constructs and Measures of the Study.

Construct	Code	Measures	Representative studies
Social media influence on the voting realignments	VR1	Social media (Facebook, YouTube, WhatsApp, Twitter.) Influenced my voting pattern (choice of candidate) in the 2018 elections in Pakistan	Kofi Frimpong et al. (2020)
	VR2	Social media motivated me to switch my voter preference
	VR3	Issues on social media affected my voting preference
Connection with military-aligned social media activists (SMAs)	SMA1	I connect with (join, follow, write posts, read, watch, comment, retweet, share) journalists, commentators, and defense analysts on social media (Facebook, YouTube, Twitter) who provide information about the Pakistani military's contribution to the country.	Kim and Chen (2016) and Kofi Frimpong et al. (2020)
	SMA2	I connect with (join, write posts, read, watch, comment, retweet, share) social media (Facebook, YouTube, WhatsApp, Twitter) groups, Vlogs, or pages that promote the role of the Pakistan Army in the country.
	SMA3	I connect with (join, write posts, read, watch, comment, retweet, and share) the official social media channels of ISPR.
Online Political Participation (ONPP)	ONPP2	I am interested in and a member of/joining social media political groups, Pages, or Vlogs made for political commentary/news.	Gan et al. (2017), Kim and Chen (2016), and Lim (2008)
	ONPP3	I take part in discussing politics and associated issues on social media
	ONPP5	Online voluntary activities such as political parades and meetings are essential to me, and I encourage people to participate.
Offline Political Participation (OFPP)	OFPP2	I write for newspapers and take part in radio discussions and television programs about political issues	Choi et al. (2017)
	OFPP3	I call politicians, political experts, or political parties and talk clearly about political issues
	OFPP6	I write letters to political officials about political issues
	OFPP7	I contact political parties and social organizations on the telephone about political issues
Political disposition (PD)	PD1	I feel my skills can affect the political system, so I participate in making a difference	Gan et al. (2017)
	PD3	I have adequate political evaluation/knowledge
	PD5	I have adequate policy knowledge

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Saif Ur Rahman

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the first author upon reasonable request.

References

Administrator. (2018). Voter turnout in 2018 dropped by more than 3%. The Express Tribune. https://tribune.com.pk/story/1770156/1-1770156/

Ahmad

Alvi

Ittefaq

(2019). The use of social media on political participation among university students: An analysis of survey results from rural Pakistan. SAGE Open, 9(3), 1–9. https://doi.org/10.1177/2158244019864484

Amin Mohamed

Gardner

W. L.

(2004). An exploratory study of interorganizational defamation: An organizational impression management perspective. Organizational Analysis, 12(2), 129–145. https://doi.org/10.1108/eb028989

Arshad

Khurram

(2020). Can government’s presence on social media stimulate citizens’ online political participation? Investigating the influence of transparency, trust, and responsiveness. Government Information Quarterly, 37(3). https://doi.org/10.1016/j.giq.2020.101486

Aziz

(2007). Military control in Pakistan: The parallel state. New York: Routledge.

Benthaus

Risius

Beck

(2016). Social media management strategies for organizational impression management and their effect on public perception. Journal of Strategic Information Systems, 25(2), 127–139. https://doi.org/10.1016/j.jsis.2015.12.001

Bolino

M. C.

Kacmar

M. K.

Turnley

W. H.

Gilstrap

B. J.

(2008). A multi-level review of impression management motives and behaviors. Journal of Management, 34(6), 1080–1109. https://doi.org/10.1177/0149206308324325

Bollen

K. A.

Hoyle

R. H.

(2012). Latent variables in structural equation modeling. In Hoyle

R. H.

(Ed.), Handbook of structural equation modeling (pp. 56–67). The Guilford Press.

Bonsón

Royo

Ratkai

(2015). Citizens’ engagement on local governments’ Facebook sites. An empirical analysis: The impact of different media and content types in Western Europe. Government Information Quarterly, 32(1), 52–62. https://doi.org/10.1016/j.giq.2014.11.001

10.

Caliskan

A. O.

Esen

(2018). Sustainability disclosures and impression management on social media. Pressacademia, 7(1), 213–216. https://doi.org/10.17261/pressacademia.2018.883

11.

Cao

Meadows

Wong

Xia

(2021). Understanding consumers’ social media engagement behaviour: An examination of the moderation effect of social media context. Journal of Business Research, 122(5), 835–846. https://doi.org/10.1016/j.jbusres.2020.06.025

12.

Choi

Lee

J. K.

Metzgar

E. T.

(2017). Investigating effects of social media news sharing on the relationship between network heterogeneity and political participation. Computers in Human Behavior, 75, 25–31. https://doi.org/10.1016/j.chb.2017.05.003

13.

Corrigall-Brown

Wilkes

(2014). Media exposure and the engaged citizen: How the media shape political participation. Social Science Journal, 51(3), 408–421. https://doi.org/10.1016/j.soscij.2014.03.009

14.

Creswell

(2013). Research design: Qualitative and quantitative approaches. Sage.

15.

Dictionary. (2021). Disposition definition. Dictionary.Com 6. Retrieved (https://www.dictionary.com/browse/disposition).

16.

Dimitrova

D. V.

Shehata

Strömbäck

Nord

L. W.

(2014). The effects of digital media on political knowledge and participation in election campaigns: Evidence from panel data. Communication Research, 41(1), 95–118. https://doi.org/10.1177/0093650211426004

17.

Djuyandi

(2015). The professionalism of Indonesian National Army in civil-military relations. A case study in general election 2014. Journal of Social Research and Policy, 6(1), 1–12.

18.

DW. (2018). How Pakistan’s military uses media for image making. DW Pakistan.

19.

Falasca

Dymek

Grandien

(2019). Social media election campaigning: Who is working for whom? A conceptual exploration of digital political labour. Contemporary Social Science, 14(1), 89–101. https://doi.org/10.1080/21582041.2017.1400089

20.

Fornell

Larcker

D. F.

(1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312

21.

Fricker

R. D.

(2012). Sampling methods for web and e-mail surveys. In Fricker

R. D.

(Ed.), The SAGE handbook of online research methods (pp. 195–216). Sage. https://doi.org/10.4135/9780857020055.n11

22.

Gan

Lee

F. L. F.

(2017). Social media use, political affect, and participation among university students in urban China. Telematics and Informatics, 34(7), 936–947. https://doi.org/10.1016/j.tele.2017.04.002

23.

Gefen

Straub

Boudreau

M.-C.

(2000). Structural equation modeling and regression: Guidelines for research practice (Vol. 4). Communications of the Association for Information Systems.

24.

Goldstein

J. A.

Sinpeng

Bush

Ewald

John

(2020). Cheerleading without fans: A low-impact domestic information operation by the Royal Thai Army. Stanford Internet Observatory.

25.

Grare

(2015, December). The challenges of civilian control over intelligence agencies in Pakistan. In Ali Ashraf

A. S. M.

(Ed.), Intelligence, national security and foreign policy: A south Asian narrative (pp. 1–18). Bangladesh Institute of law and International Affairs, BILIA. Carnegie Endowment for International Peace.

26.

Grossman

Ewald

John

Mir

Ngo

Patel

(2020). Reporting for duty: How a network of Pakistan-based accounts leveraged mass reporting to silence critics. Stanford Internet Observatory Cyber Policy Center.

27.

Hair

J. F.

Anderson

R. E.

Tatham

R. L.

Black

W. C.

(1998). Multivariate data analysis (Vol. 87). Harlow Pearson Education.

28.

Hair

J. F.

Matthews

Sarstedt

(2017). PLS-SEM or CBSEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123.

29.

Hair

J. F.

Risher

J. J.

Sarstedt

Ringle

C. M.

(2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

30.

Hamlin

(2005). Political dispositions and dispositional politics. Manchester Centre for Political Theory (MANCEPT), University of Manchester.

31.

Hashim

(2017). Pakistan Army `rejects’ PM’s actions on security leak. Aljazeera.

32.

Henseler

Ringle

C. M.

Sarstedt

(2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

33.

Husain

(2012, November 10). Who defines national interest? The Dawn.

34.

Hussain

(2017, October 12). Army chief says economy showing mixed indicators. The Daily Dawn.

35.

Hussain

Iqbal

Abbasi

S. N.

(2021). Impact of social media on voting behavior of youth during Pakistan general elections-2018. Psychology and Education, 58(4), 1537–1548

36.

Iqbal

Y. W.

(2017). The influence of interpersonal communication, traditional media, and new media sources on youth’s voting behavior: A study of Pakistan general election 2013 campaign. Journal of Mass Communication & Journalism, 7(4), 2. https://doi.org/10.4172/2165-7912.1000343

37.

ISPR. (2022). Pakistan Army official Facebook page. https://www.facebook.com/officialpakarmy

38.

ISPR. (2023). DGISPR official page on Twitter. https://twitter.com/officialdgispr

39.

Jahangir

(2022, June 5). Riding the social media tiger. The Daily Dawn.

40.

Javid

(2019). Patronage, populism, and protest: Student politics in Pakistani Punjab. South Asia Multidisciplinary Academic Journal, 22, 6497. https://doi.org/10.4000/samaj.6497

41.

Jha

C. K.

Kodila-Tedika

(2020). Does social media promote democracy? Some empirical evidence. Journal of Policy Modeling, 42(2), 271–290. https://doi.org/10.1016/j.jpolmod.2019.05.010

42.

Jöreskog

K.G.

(1971). Simultaneous factor analysis in several populations. Psychometrika 36, 409–426 (1971). https://doi.org/10.1007/BF02291366

43.

Kemp

(2022). Digital 2022: Pakistan. Datareportal.

44.

Key

V. O.

(1955). A theory of critical elections. The Journal of Politics, 17(1), 3–18. https://doi.org/10.2307/2126401

45.

Khan

M. K.

Pratt

C. B.

(2020). Strategic communications: The Pakistan Military’s use of social media against terrorism. Media, War and Conflict, 15(4), 450–485. https://doi.org/10.1177/1750635220972127

46.

Kim

Chen

H. T.

(2016). Social media and online political participation: The mediating role of exposure to cross-cutting and like-minded perspectives. Telematics and Informatics, 33(2), 320–330. https://doi.org/10.1016/j.tele.2015.08.008

47.

Kline

(2011). Principles and practice of structural equation modeling. The Guilford.

48.

Kofi Frimpong

A. N.

Nyame

Hossin

M. A.

(2020). The impact of social media political activists on voting patterns. Political Behavior, 44, 599–652.

49.

Lee

P. S. N.

C. Y. K.

Lee

Leung

Chan

(2018). Social media and political partisanship—A subaltern public sphere’s role in democracy. Telematics and Informatics, 35(7), 1949–1957. https://doi.org/10.1016/j.tele.2018.06.007

50.

Lim

(2008). Social networks and political participation: How do networks matter? Social Forces, 87(2), 961–982. https://doi.org/10.1353/sof.0.0143

51.

Luo

(2022). Politicalization or professionalism? A case study of the military’s discourse in China. Armed Forces & Society, 48(1), 185–204. https://doi.org/10.1177/0095327X20906848

52.

Malhotra

(2020). Inter-Services Public Relations (ISPR) assessment of the Pakistan Military’s discreet propaganda factory post-1990. Journal of Defence Studies, 14(4), 37–57.

53.

Marquis

(2010). Understanding political knowledge and its influence on voting preferences in the 2007 federal election. Swiss Political Science Review, 16(3), 425–456.

54.

Mazhar

(2008). Military control in Pakistan: The parallel state. Routledge.

55.

Mohamed

Gardner

W. L.

Paolillo

J. G. P.

(1999). A taxonomy of organizational impression management tactics. Advances in Competitiveness Research, 7, 108–130.

56.

Mozur

(2018, October 15). A genocide incited on Facebook, with posts from Myanmar’s military. The New York Times.

57.

Mughal

(2021, April 20). Fake social media accounts and marginalisation of women in Pakistan. The Nation.

58.

News Desk. (2022, October 4). Imran Khan wants security agencies grilled over audio leaks. The Daily News.

59.

Oser

Hooghe

Marien

(2013). Is online participation distinct from offline participation? Political Research Quarterly, 66(1), 91–101.

60.

Potkin

Lone

(2021). “Information combat”: Inside the fight for Myanmar’s soul. Reuters.

61.

Rahman

S. U.

Shurong

(2021). Governing through informal mechanisms: Military control over state institutions in Pakistan. Asian Survey, 61(6), 942–970. https://doi.org/10.1525/as.2021.1433283

62.

Rahman

S. U.

Shurong

Jan

(2022). Social media and authoritarian legacies: The impact of military aligned social media activists (SMAs) on politics. Public Organization Review, 23(2), 715–737. https://doi.org/10.1007/s11115-022-00691-0

63.

Rahman

S. U.

Jan

(2023). Pakistan in 2023: On the Brink of a Full-Blown Crisis. India Quarterly, 79(3), 293–303. https://doi.org/10.1177/09749284231183320

64.

Rashid

(2021). Social media in Pakistan: The war of the narratives. Future Directions International.

65.

Reichert

(2016). How internal political efficacy translates political knowledge into political participation: Evidence from Germany. Europe’s Journal of Psychology, 12(2), 1095. https://doi.org/10.5964/ejop.v12i2.1095

66.

RSF. (2023). Behind Pakistan’s civilian government, army tightens its grip on journalists. RSF.

67.

Scherman

Arriagada

(2012). Disposition to vote and media consumption patterns among Chilean youth. Jóvenes, Disposición a Votar y Consumo de Medios En Chile. 25(1), 85–112.

68.

Schniederjans

Cao

E. S.

Schniederjans

(2013). Enhancing financial performance with social media: An impression management perspective. Decision Support Systems, 55(4), 911–918. https://doi.org/10.1016/j.dss.2012.12.027

69.

Shah

(2014). Constraining consolidation: Military politics and democracy in Pakistan (2007–2013). Democratization, 21(6), 1007–1033. https://doi.org/10.1080/13510347.2013.781586

70.

Shah

(2019). Pakistan: Voting under military tutelage. Journal of Democracy, 30(1), 128–142. https://doi.org/10.1353/jod.2019.0010

71.

Shaikh

R. A.

(2009). A state of transition: Authoritarianism and democratization in Pakistan. Asia Journal of Global Studies, 3(1), 4–21.

72.

Shen

Xia

Skoric

(2020). Examining the roles of social media and alternative media in social movement participation: A study of Hong Kong’s umbrella movement. Telematics and Informatics, 47, 101303.

73.

Shurong

Rahman

S. U.

(2017). Rethinking civil-military relations in a Pakistan: Some lessons from Turkey. Journal of Socialomics, 6(3). https://doi.org/10.4172/2167-0358.1000209

74.

Siddiqua

(2021). Use of cyber hate in the electoral campaigns by the mainstream political parties of Pakistan. Humanities & Social Sciences Reviews, 9(2), 325–332. https://doi.org/10.18510/hssr.2021.9232

75.

Singh

S. P.

Roy

(2014). Political knowledge, the decision calculus, and proximity voting. Electoral Studies, 34, 89–99. https://doi.org/10.1016/j.electstud.2013.11.007

76.

Sirrs

O. L.

(2017). Pakistan’s inter-services intelligence directorate covert action and internal operations. Routledge.

77.

Springer

(2012). Social media-risk management. Plastic Surgical Nursing, 32(1), 22–24.

78.

Stewart

(2012). Pakistan: A hard country. Asian Affairs, 43(1), 144–145. https://doi.org/10.1080/03068374.2012.642558

79.

Syeed

(2019). Facebook removes accounts linked to Pakistani military employees. Reuters.

80.

The Reporter. (2020). Twitter takes down Thai army IO network. The Bangkok Post.

81.

Tran

Bar-Tur

(2020). Social media in government: Benefits, challenges, and how it’s used. Hootsuite.

82.

Verba

Nie

N. H.

Kim

J.-O.

(1978). Participation and political equality (Vol. 21). Cambridge University Press.

83.

Yamamoto

Morey

A. C.

(2019). Incidental news exposure on social media: A campaign communication mediation approach. Social Media + Society, 5(2), 205630511984361. https://doi.org/10.1177/2056305119843619

84.

Yang

J. H.

Liu

(2017). Accounting narratives and impression management on social media. Accounting and Business Research, 47(6), 673–694. https://doi.org/10.1080/00014788.2017.1322936

85.

Zhang

Johnson

T. J.

Seltzer

Bichard

S. L.

(2010). The revolution will be networked: The influence of social networking sites on political attitudes and behavior. Social Science Computer Review, 28(1), 75–92. https://doi.org/10.1177/0894439309335162