This paper investigates why the Philippines and Vietnam delayed the establishment of their cyber commands until 2024 and 2017, respectively, despite both countries experiencing foreign cyberattacks linked to the South China Sea disputes since the early 2010s and explains the seven-year disparity between them. Findings reveal that the Philippines initially focused on combating cybercrimes, whereas Vietnam prioritized addressing regime-threatening cyber activities. When the two countries eventually recognized cyberspace as a domain of warfare, different alignment choices, strategic cultures, and domestic institutions led to divergent pathways in creating their cyber commands.
While social media plays a prominent role in global journalism, its influence on media diversity is under debate. This paper aims to examine the relationship between social media and online media diversity. The research framework posits that online media diversity is shaped between social media empowerment and the existing power structure. Social media empowerment is specified by the degree to which social media allows audience participation, consisting of two levels of participatory intensity - social media adoption (low) and organization (high). We explore how adoption and organization are associated with online media diversity in three country groups with varied levels of press freedom (low, middle, and high), which specifies the degree to which the existing power structure controls online media outlets by shaping their functions, norms, and practices. Using country-level data from Varieties of Democracy and other sources, we analyze a panel sample of 150 countries from 2014 to 2022. We find that social media adoption and organization are associated with online media diversity in different ways within and between country groups. From a comparative perspective, the findings enhance our understanding of the theories of normalization and power shift, which account for power relations between social media and media organizations.
Existing scholarship on social media polarization has predominantly focused on political polarization in developed countries. However, the interplay between social media and other forms of polarization, such as ethnic polarization, which is equally harmful and arguably more prevalent in developing nations, has not received sufficient attention. Drawing on cross-sectional survey data (N = 549) from Afghanistan, this study examines the relationship between Facebook network heterogeneity and ethnic polarization. Results from two serial mediation analyses showed no significant direct association between network heterogeneity and ethnic polarization. However, network heterogeneity is positively associated with diverse content exposure, perceived knowledge acquisition, intergroup contact quality, and trust, thereby indirectly attenuating ethnic polarization. By extending the scope of polarization research beyond the political divide in the Western context, this study contributes to the emerging literature on ethnic polarization in social media.
This article examines how Facebook reaction metrics structure party leaders' communication incentives during COVID-19. Using 7,264 posts from twelve Norwegian leaders, it codes nine crisis-message strategies and models Angry, Sad, Love, and Care counts with negative binomial regressions. Two visibility-oriented affective profiles emerge. Heat (Angry, Sad) aligns most with criticism and crisis framing, while affiliation (Love, Care) aligns most with accommodative and promotional messaging. These associations vary across crisis phases and between government and opposition. Disaggregating engagement into emotion-specific signals clarifies incentive patterns that aggregate engagement can obscure.
Politicians use the multimodal affordances of social media to strategically interact with voters. Previous scholarship focused on national elections, but how local candidates use verbal and non-verbal strategies on Instagram, remains comparatively unexplored. A quantitative content analysis of Instagram posts (N = 1194) was conducted to examine how candidates running in seven Italian regional elections employed verbal and non-verbal strategies. Findings showed that candidates used Instagram to convey professionalism (verbally and non-verbally) and to describe policies, but politicians leading center-left coalitions and female candidates were more likely to use Instagram to mobilize voters, attack opponents, and talk about policies. Verbal and non-verbal strategies often diverged rather than reinforced each other, and multimodal alignment was mainly limited to convey professionalism and to emphasize regional heritage and identity. Results indicate that in the Italian regional context verbal and non-verbal modalities on Instagram are frequently used as independent channels that do not necessarily convey the same meaning within a single post. Italian politicians used Instagram to post images with facial expressions conveying optimism and positivity, but no differences between female and male politicians were detected for facial expression, contradicting literature finding gender is a predictor of visual emotionalization on social media.
Using a preregistered two-wave panel of Japanese young adults during the 2025 election, this study tests links between political-video viewing and (i) perceived intergenerational unfairness and (ii) distrust of mainstream media. Fixed-effects estimates show both directions non-significant, implying minimal short-term attitude conversion. A two-wave CLPM finds only the attitude -> viewing path significant, consistent with demand-driven "sorting." Declining political satisfaction consistently predicts higher media distrust. We propose an integrated framework: (i) a short-run upper bound on within-person change, (ii) video's primary function as sorting, and (iii) a three-way linkage of demand, supply, and institutional evaluations.
This study contributes methodologically by adapting McGuire's Communication-Persuasion Matrix into a structured thematic analysis framework applied to both visual and textual content on Instagram. We analyzed 2,114 posts from five influential antivaccine accounts in Turkey, focusing on 1,747 posts directly relevant to persuasion strategies used before and during the COVID-19 pandemic (2018-2020). Using MAXQDA software and a coding scheme validated with high inter-coder reliability (kappa = 0.91), we identified 13 distinct persuasion tactics. These include framing potential risks, presenting pseudo-scientific translations, employing sarcasm, advancing conspiracy theories, referencing non-expert authorities, and advocating vaccine refusal. The tactics were mapped to McGuire's model components - such as message content, message style, source credibility, and receiver characteristics - highlighting how classical persuasion theory can inform qualitative content analysis. Our findings reveal that these Instagram accounts function as echo chambers in a post-truth environment, where misinformation circulates unchecked and is reinforced within the network. This study not only enhances our understanding of antivaccine rhetoric but also offers a replicable method for applying communication theory to digital health discourse.
Empirical studies have yielded mixed results regarding the relationship between the emergence of social media and the perceived unraveling of the democratic consensus in established democracies. This article contributes to the existing literature by examining a previously overlooked avenue for understanding this relationship: we investigate users' characteristics and self-selection into different social media platforms. The central hypothesis tested in the article is that the political use of social media is more prevalent among individuals with more extreme (non-democratic) values than among individuals with more mainstream (democratic) views. Our analysis of novel survey data from six European countries reveals that political users of Facebook, Twitter, and Instagram tend to align with non-democratic values. We discuss several theoretical mechanisms that could account for this self-selection process and speculate on how our findings may help understand the role of social media platforms in political polarization.
For democratic societies, forums of political discussions are needed to exchange opinions which nowadays can be found in social media. Still, in line with theoretical assumptions of the privacy calculus, benefits of political expression in social media also come with risks of privacy invasions, both affecting people's expression behavior. To better understand the longitudinal between- and within-person dynamics of anticipating costs and benefits when expressing political opinions online, this study uses a three-wave-longitudinal survey to analyze the reciprocal relationships between privacy concerns, political expression, as well as expected cost and benefits in social media. Results indicated that when individuals are more concerned than usual about data collection by companies or governments (i.e. vertical privacy concerns), they express political opinions less frequently. In contrast, heightened concerns about misuse by other social media users (i.e. horizontal privacy concerns) are associated with more frequent political expression. In terms of users' weighing of costs and benefits, we found that while frequent opinion expressors see the benefit of persuading others in social media, non-expressors are inhibited by assuming that their opinion expression might be a waste of time. This suggests that people's political expression online is not solely driven by abstract privacy concerns but by very specific worries about who will use their opinionated message and with which consequences.
This study extends the Uses and Gratifications (U&G) framework by integrating sociopolitical constructs - specifically, psychological reactance and patriotism - to examine motivations behind continued TikTok use. While U&G has traditionally focused on individual-level functional gratifications, global platforms now operate within political and cultural tensions, calling for a broader analytical lens. Drawing on survey data from South Korean and Chinese users (N = 526), this study investigates how four functional motivations - entertainment, information seeking, social interaction, and economic benefit - alongside sociopolitical factors, shape user behavior. Among South Korean users, entertainment and social interaction significantly predicted continued use. Psychological reactance not only exhibited a direct effect but also moderated the relationship between gratifications and continued use, weakening the influence of entertainment and information-seeking motivations among users high in reactance. This suggests that reactance may serve both as an independent driver and as a filter that reshapes how gratifications are interpreted. In contrast, among Chinese users, continued use was significantly associated with information seeking and patriotism, but no moderating effects were found. Patriotism functioned as a standalone motivation rather than a moderator. These divergent patterns demonstrate that the same psychological constructs can function differently depending on how platforms are situated within national sociopolitical contexts.
This paper asks: What is digital democracy? It outlines some foundations of a theory of digital democracy and introduces a novel approach. A review of influential understandings of digital democracy shows the dominance of the two models of deliberative and participatory democracy. In the contemporary poly-crisis of world society, there is an antagonism between digital communicative participation and digital fascism. Participation and deliberation can result in participatory fascism and deliberative fascism. As a consequence, we need an understanding of digital democracy that goes beyond the pure stress on participatory and deliberative digital democracy and foregrounds the potential combination of constitutional democracy on the one side and deliberative and participatory democracy on the other side. This paper suggests a novel approach to conceptualizing digital democracy that is multi-perspectival, multidimensional, non-dualistic, and based on a dialectic of technology and society. It suggests a typology of digital democracy that consists of four dimensions and six related and interacting models of democracy: constitutionalist digital democracy, representative digital democracy, direct digital democracy, pluralist digital democracy, deliberative digital democracy, and participatory digital democracy.
Disinformation plays a key role in contemporary hybrid warfare, particularly in the Russia - Ukraine conflict, where media narratives shape public perception. This study examines whether established linguistic indicators of disinformation appear in pro-Kremlin news discourse and identifies context-specific strategies. A corpus of English-language articles from the EUvsDisinfo database (2021-2023) was analyzed using Critical Discourse Analysis and corpus linguistics, integrating quantitative measures with qualitative interpretation. Critical Discourse Analysis allows identifying the features that express meaning, reveal ideologies, and influence discourse. On the other hand, corpus linguistics provides a quantitative basis by examining the frequency and the distribution of these features in the corpus. The findings confirm the presence of known disinformation markers designed to influence the reader's perception through text, rhetoric, and semantic manipulation mechanisms. Disinformation thus emerges as a coherent, context-driven discursive practice rather than a fixed set of features.
Do perceptions of citizen identity affect policymaker responsiveness to different communication channels? This study considers that policymakers prefer to engage through communication channels that are more highly used by their supporters. To investigate this possibility, I field complementary surveys of local policymakers and the US public. I find some evidence that policymakers are more willing to respond when their supporters are seen as more likely to use a communication channel. In addition, I do not find that policymakers are more responsive to only high-cost channels, and, amongst the public, supporters are more likely than other groups to use both high-cost and low-cost channels. The findings complicate costly signaling explanations for political communication and encourage attention to disagreement driven disagreement as a potential factor in policymakers' engagement through increasingly diversified social media and alt-tech platforms.
Transformative digital platforms, including generative artificial intelligence (GenAI), have accelerated the production and circulation of misinformation in contemporary political communication. While the creation of false or misleading content is a significant concern, the perceived credibility of such material and the ways it is taken up within online discourse generate negative externalities that extend beyond individual users. This study examines how AI-driven deepfake artifacts related to the 2024 U.S. presidential election are framed and discussed within polarized political discourse on the social media platform X (formerly Twitter). Using qualitative content analysis, the study analyzes AI-generated deepfake images and videos alongside user comments responding to these artifacts. The findings show that deepfake content is embedded within highly polarized discourse characterized by emotional intensity, partisan alignment, and antagonistic representations of political figures. Recurring themes include emotional polarization, political satire and humor, and manipulative framing strategies that structure how candidates and political issues are portrayed in deepfake artifacts and subsequent user responses. Rather than assessing behavioral effects or audience influence, the analysis highlights how deepfakes circulate within online environments that reflect and reproduce polarized narratives. Based on these patterns, the study proposes the Deepfake-Driven Framing and Polarization Framework (DDFPF) to conceptualize how different types of deepfake images and videos correspond to distinct patterns of framing and commenter engagement in polarized political contexts.
Outside groups have become increasingly central to U.S. election campaigns since Citizens United, but their true reach remains opaque: gaps in reporting requirements and limited ad library data obscure how much they spend and which races they target. This gap limits our ability to evaluate their role in shaping electoral competition and influencing policy. We develop a scalable multimodal system that attributes digital ads to contests by identifying referenced candidates in text and images, aligning with FEC rules. Applied to 1.4 million Meta ads from 2020, our system leverages both text and images to yield more comprehensive estimates of outside-group spending than either modality alone, reallocates tens of millions in spending, and enables ad tone analysis. Our framework provides generalizable, race-level attribution and supports research on outside-group influence and campaign strategy.
The expansion of surveillance in Central Asia has unfolded not as a neutral process of digital modernization but as a politically charged response to regime insecurity, mobility, and shifting geopolitical alignments. Focusing on Kazakhstan, Uzbekistan, and Turkmenistan, this article examines how surveillance infrastructures linked to China's Digital Silk Road are embedded across distinct spatial and political sites, including urban camera networks in Almaty, border surveillance posts in the Ferghana Valley, and biometric databases and control systems along Turkmenistan's southern frontier. Drawing on geospatial analysis, regional documentation, activist interviews, and digital ethnography of dissident networks, the study traces both the institutional adoption of Chinese surveillance technologies and the forms of resistance they provoke. Rather than producing a uniform model of digital authoritarianism, these systems are selectively adapted to existing coercive practices, allowing states to recalibrate sovereignty, manage sociopolitical tensions, and extend authority beyond conventional territorial boundaries. Surveillance thus functions simultaneously as an instrument of domestic political discipline and as a geopolitical interface through which China's technological influence is consolidated. At the same time, these infrastructures generate new, adaptive forms of civic resistance, revealing surveillance as a contested field of power rather than a settled architecture of control.
This study examines whether and how Iranian Telegram channels coordinated to disseminate propaganda and disinformation during the 12-day Israel - Iran war (13-24 June 2025). Building on digital repression and computational propaganda research that remains Twitter-centric mainly, the analysis centers on Telegram and includes channel types typically treated as nonpolitical intermediaries. A dataset of 47,567 posts from 29 channels was collected and analyzed using a mixed-methods design integrating natural language processing, social network analysis of co-posting ties, and rhetorical analysis. The results reveal a highly saturated coordination network in which political-news outlets acted as key hubs, but entertainment channels also occupied structurally central positions. Proxy and entertainment channels formed an amplification layer that, to a great extent, repeatedly reproduced regime-aligned narratives. Disinformation was less prevalent than propaganda, yet replication was frequent and often packaged in humorous or sarcastic terms, enabling message diffusion to broader audiences. The findings show how infrastructural and leisure-oriented channels can be incorporated into wartime influence operations in authoritarian settings.
Social media is a central arena for political engagement among youth in Lebanon's crisis-affected and polarized context. This study distinguishes active social media political engagement from passive news consumption in association with offline political participation among youth. Drawing on the Uses and Gratifications Theory, the Spiral of Silence Theory, and Resource Mobilization Theory, this study analyzes data collected from 450 Lebanese young adults aged 18-34. The findings divulge that social media influencers significantly enhance political advocacy but do not directly translate into real-life political participation. Social media news use is positively related to online political communication; however, it does not significantly influence offline political engagement. In contrast, social media activism and online political communication are significantly associated with real-life political participation, implying that active and expressive forms of online engagement are more likely to mobilize offline political action than passive news consumption. By distinguishing between different modes of social media engagement, this study contributes to ongoing debates on the online-offline participation nexus and challenges assumptions about the mobilizing power of social media news exposure. The findings bestow theoretical and practical insights for understanding youth political engagement in fragile democratic and crisis-driven contexts such as Lebanon.
The diffusion of generative artificial intelligence (GenAI) raises questions not only about productivity but also about inequality, labor politics, and the future of development models. This paper examines South Korea - an economy long reliant on export-oriented manufacturing - to assess whether early GenAI adoption is associated with emerging differences in productivity across industries. Using quarterly data for 18 industries from 2013 to 2025, the analysis shows that industries with greater exposure to AI-augmentable tasks, many of which are in services, experienced short-run productivity increases after 2023, while routine-intensive manufacturing displayed limited change. These uneven outcomes extend task-based accounts of technological change to the industry level and suggest emerging sectoral differences in GenAI adoption. The paper contributes by providing early national evidence on sector-level patterns of GenAI exposure and by situating these patterns within debates about South Korea's manufacturing-centered growth model. The findings point to the policy challenges associated with uneven technological adoption and to their implications for industrial strategy and labor relations.
This study investigates the use of emotional appeals by British political parties on Facebook during and outside election campaigns, and the relationship between emotions and engagement. Drawing on theories of emotion from political psychology, I conduct a manual content analysis of parties' posts (N = 1,710) across long and short campaigns, post-election, and routine periods. Results reveal widespread and strategic use of emotional appeals: appeals to enthusiasm and anger were more frequent than fear, with patterns varying across parties and periods. The relationship between emotions and engagement differs by type of interaction and across periods. Enthusiasm predicted likes, anger predicted shares and comments, and fear showed no significant association with any engagement form. The association between emotions and engagement also varied across periods, indicating their context-dependent nature. The findings are consistent with Facebook's nature as an arena for partisan mobilization and raise normative concerns about the limited space for deliberative engagement in political discourse on the platform.
