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Twitter has pushed public opinion on foreign policy into partisan bubbles that often value alternative media sources over traditional media or political elites. Public opinion on China is no exception. On the left, some alternative media outlets support China as a socialist ideal, while others criticize it as a key player in global capitalism and neoliberal order. This leads to an important puzzle: How and why do some transnational left media disseminate pro-China messaging while others do not? We focus on two leftist alternative media outlets: the Qiao Collective and Lausan. Both organizations claim to offer a variety of counter-hegemonic-oriented discourses. We first qualitatively analyze the differences in how these two organizations frame key topics in contemporary Chinese politics including Uyghurs in Xinjiang and the Hong Kong protests. We then use quantitative social network analysis to show how their communication efforts lead to different follower audiences. In the last step, we analyze what issues the Qiao Collective is using to achieve its inward- and outward-oriented goals. Our study shows how both outlets focus on the transnational left, but each reaches distinct audiences that do not overlap. We find that the Qiao Collective jumps on traditional left-wing issues in the US to extend its reach while regularly posting positive, often revisionist perspectives about Chinese politics. This specific element conflicts with its claim of supporting anti-imperialist and pro-democracy politics and distinguishes the Qiao Collective from other transnational left outlets.

The internet, and especially social media platforms, offer scientists new opportunities to connect with a broader public. While many studies have focused on science communication on Twitter, surprisingly few have analyzed how scientists use Facebook, even though it is an essential platform for the general public in many countries. A possible explanation for this lack of research is that scientists keep their Facebook profiles separate from their work life and are more active on Twitter in their professional roles. Our study challenges this assumption by focusing on Taiwan as a peculiar case. Due to the local culture, Twitter is less popular there, and scientists are more active on Facebook, even in their professional roles. In our study, we analyzed 35 public pages of scientists on Facebook and assessed the factors explaining the reach of their communication using content analysis in combination with a multilevel model that allowed us to test predictors on the page level, such as the number of fans, in combination with predictors on the post level, such as the complexity of the language used. Our study shows that Facebook can play an influential role in science outreach. To effectively communicate with the audience on Facebook, it is best to use strategies that appeal to new and existing followers. Posts that address current issues and include opinions are likely to be shared widely, while humor or personal self-disclosure is likely to engage the existing audience. Our study contributes to the current debate about alternatives to Twitter in science communication.

The news media are among the most important sources of information about political events, such as referendums. For young adults, the smartphone has become the main device for accessing news. However, we know little about the factors influencing mobile news consumption and how this consumption is related to political knowledge and political participation. This study investigates the antecedents of young individuals’ smartphone news consumption and how it is correlated with their knowledge about and participation in two referendums in Switzerland. We record the mobile internet usage of 309 young adults and link their digital trace data to survey data. We show that trust in news media and the use of broadcast media are positively correlated with the duration of mobile news consumption. The use of social media leads to more news source diversity. However, we find that the duration of mobile news consumption and news source diversity are not correlated with political knowledge about or participation in the referendum. As interest in politics is also positively correlated with the diversity of news sources used by individual participants, our study supports the idea that attentive audiences use a broader range of news sources to inform themselves about referendums.

Twitter has pushed public opinion on foreign policy into partisan bubbles that often value alternative media sources over traditional media or political elites. Public opinion on China is no exception. On the left, some alternative media outlets support China as a socialist ideal, while others criticize it as a key player in global capitalism and neoliberal order. This leads to an important puzzle: How and why do some transnational left media disseminate pro-China messaging while others do not? We focus on two leftist alternative media outlets: the Qiao Collective and Lausan. Both organizations claim to offer a variety of counter-hegemonic-oriented discourses. We first qualitatively analyze the differences in how these two organizations frame key topics in contemporary Chinese politics including Uyghurs in Xinjiang and the Hong Kong protests. We then use quantitative social network analysis to show how their communication efforts lead to different follower audiences. In the last step, we analyze what issues the Qiao Collective is using to achieve its inward- and outward-oriented goals. Our study shows how both outlets focus on the transnational left, but each reaches distinct audiences that do not overlap. We find that the Qiao Collective jumps on traditional left-wing issues in the US to extend its reach while regularly posting positive, often revisionist perspectives about Chinese politics. This specific element conflicts with its claim of supporting anti-imperialist and pro-democracy politics and distinguishes the Qiao Collective from other transnational left outlets.

Inequities in China are reflected within state-run media coverage due to its specific role “guiding public opinion,” and with our study we contribute to the geographic turn in the Chinese context with regard to media and journalism. As a subject of a spatial study, China is unique due to several factors: geographic diversity, authoritarian control, and centralized media. By analyzing text from 53,000 articles published in People’s Daily (rénmín rìbào, 人民日報) from January 2016 to August 2020, we examine how the amount of news coverage varies by region within China, how topics and sentiments manifest in different places, and how coverage varies with regard to foreign countries. Automated methods were used to detect place names from the articles and geoparse them to specific locations, combining spatial analysis, topic modeling and sentiment analysis to identify geographic biases in news coverage in an authoritarian context. We found remarkably uniform and positive coverage domestically, but substantial differences towards coverage of different foreign countries.

The content moderation practice of deplatforming, i.e., the removal of undesired actors, has become common on social media platforms such as YouTube. Our study aims to examine the impact of deplatforming on prominent far-right channels on YouTube. In our study, we are particularly interested in the deplatforming of prominent far-right channels such as Alex Jones, James Allsup, or Red Ice TV to understand the impact deplatforming has on them. To do so, we analyze two datasets: We check whether 11,198 YouTube channels have been removed in 22 months between 2018 and 2019 and for what reason. We then focus on the far right and check whether the deplatformed far-right channels have found a new home on the alternative video platform BitChute. The time frame for this study includes the removal of some critically important far-right figures. Our analysis shows that deplatforming effectively minimizes the reach of disinformation and extreme speech, as alternative platforms allowing this kind of content cannot mitigate the negative effect of being deplatformed on YouTube. [ABSTRACT FROM AUTHOR]

Alternative news media (ANM) have become an important information source for certain audiences. Research shows that ANM usage is linked to a preference for populist parties and the use of digital media. However, ANM existed before the rise of populism and digital media over the last two decades. Thus, we must assume that additional factors are related to ANM usage. To investigate such factors, we conducted a cross-sectional online survey (N  = 1,212) of the Swiss population. We analyze how affinity toward conspiracy myths, preference for populist parties, the usage of social media, and the Telegram messenger app are related to ANM usage. The results indicate that people with a high affinity toward conspiracy myths are more likely to use ANM. Different than in previous studies, preference for populist politics is not related to higher ANM usage in Switzerland. Our results suggest that the political context matters when studying ANM usage and that the strong focus on right-wing populism might lead to scholars missing part of the bigger picture. Furthermore, our findings indicate that the use of social media and Telegram, which recently gained relevance as a channel for mobilizing protests during the COVID-19 pandemic, positively connect with ANM consumption. [ABSTRACT FROM AUTHOR]

Scholars from different theoretical schools have posited that in recent decades, science and society have moved closer together, and the concept of academic engagement has been proposed to capture one part of this approximation empirically. This study analyzes the academic engagement of individual scholars towards politicians, industry representatives and journalists. It uses comprehensive survey data on Swiss professors from all disciplines, all the country's universities and from associated research institutes. It assesses, firstly, the degree to which these professors have professional contacts to journalists, politicians and industry representatives. Secondly, it explains the extent of these contacts, using multi-level modelling that incorporates individual factors as well as organizational and institutional contexts. Our study shows that academic engagement is quite common with strong differences between disciplines. Furthermore, professors with higher academic productivity, positive personal attitude towards communication activities as well as a leadership position have more outside contacts. The gender and nationality of the professors, however, only play a role for some of the contacts with non-scientific actors.

Algorithms and especially recommendation algorithms play an important role online, most notably on YouTube. Yet, little is known about the network communities that these algorithms form. We analyzed the channel recommendations on YouTube to map the communities that the social network is creating through its algorithms and to test the network for homophily, that is, the connectedness between communities. We find that YouTube’s channel recommendation algorithm fosters the creation of highly homophilous communities in the United States ( n = 13,529 channels) and in Germany ( n = 8,000 channels). Factors that seem to drive YouTube’s recommendations are topics, language, and location. We highlight the issue of homophilous communities in the context of politics where YouTube’s algorithms create far-right communities in both countries.

Taiwan’s exceptionally high Internet penetration and social media adoption rates, combined with the growing centrality of digital tools and networks in shaping national politics, make it an interesting case for Internet researchers. This essay considers Andrew Chadwick’s notion of The Hybrid Media System in the context of recent political events in Taiwan. While Chadwick’s analysis is particularly useful in understanding political anomalies like the Sunflower Movement, we argue for the value of considering more substantial long-standing structural issues in attempts to understanding the political media landscape in Taiwan. Using the examples of online astroturfing during political campaigns and the spread of disinformation during the Kansai airport incident, we point out that long-standing structural factors such as the dysfunctional practices of journalists in newsrooms, the clear political slants of media in accordance with media ownership, and the traditional political power rooted in the society hold enduring sway on how politics is mediated.

The identification of bots is an important and complicated task. The bot classifier "Botometer" was successfully introduced as a way to estimate the number of bots in a given list of accounts and, as a consequence, has been frequently used in academic publications. Given its relevance for academic research and our understanding of the presence of automated accounts in any given Twitter discourse, we are interested in Botometer's diagnostic ability over time. To do so, we collected the Botometer scores for five datasets (three verified as bots, two verified as human; n = 4,134) in two languages (English/German) over three months. We show that the Botometer scores are imprecise when it comes to estimating bots; especially in a different language. We further show in an analysis of Botometer scores over time that Botometer's thresholds, even when used very conservatively, are prone to variance, which, in turn, will lead to false negatives (i.e., bots being classified as humans) and false positives (i.e., humans being classified as bots). This has immediate consequences for academic research as most studies in social science using the tool will unknowingly count a high number of human users as bots and vice versa. We conclude our study with a discussion about how computational social scientists should evaluate machine learning systems that are developed for identifying bots.

In recent years, several instances of political actors who created fake grassroots activity on the Internet have been uncovered. We propose to call such fake online grassroots activity digital astroturfing, and we define it as a form of manufactured, deceptive and strategic top-down activity on the Internet initiated by political actors that mimics bottom-up activity by autonomous individuals. The goal of this paper is to lay out a conceptual map of the phenomenon of digital astroturfing in politics. To that end, we introduce, first, a typology of digital astroturfing according to three dimensions (target, actor type, goals), and, second, the concept of digital astroturfing repertoires, the possible combinations of tools, venues and actions used in digital astroturfing efforts. Furthermore, we explore possible restrictive and incentivizing countermeasures against digital astroturfing. Finally, we discuss prospects for future research: Even though empirical research on digital astroturfing is difficult, it is neither impossible nor futile.

Experts have ranked Taiwan as the number one country regarding the exposure to disinformation. This assessment is not surprising as many exposed disinformation cases can be linked to Chinese state-aligned actors but also domestic political actors. Academic researchers, journalists, and the civic tech community have played an essential role in the fight against disinformation in Taiwan and the emergence of misinformation studies as a new research field. While disinformation in Taiwan is a major recurring issue, the "Western" debate within academia and journalism has taken a critical turn regarding the assumed effects of disinformation. Our study focuses on this potential disconnect between the international and the Taiwanese debate about disinformation. With automatic and manual content analysis, we evaluate what role academics and journalism play in the public discourse and what part of this debate reaches the largest audience. We show how Taiwan's public misinformation discourse has evolved vis-a-vis the international discourse, what role misinformation studies play in this discourse, what part of the discourse reaches the widest audience, and what parts of the discourse could be problematic. [ABSTRACT FROM AUTHOR]

Social media, and Twitter in particular, have become important sources for journalists in times of crises. User-generated content (UGC) can provide journalists with on-site information and material they otherwise would not have access to. But how they source and verify UGC has not yet been systematically analyzed. This study analyzes sourcing and verification practices on Twitter during the Brussels attacks in March 2016. Based on quantitative content analysis, we identified (1) the journalists and news organizations sourcing during the attacks, (2) classified different forms of sourcing and verification requests, and (3) analyzed the sourced UGC. Results show that sourcing on Twitter has become a global phenomenon. During the first hours of the attack, journalists rely on UGC. Their sourcing and verification practices vary widely and often lack basic verification procedures, which leads to a discussion about the ethical implications of sourcing practices.

Issues continuously compete for attention in the news media and on social media. Climate change is one of the most urgent problems for society and (re)gained wide public attention in 2019 through the global climate strike protest movement. However, we hypothesize that the outbreak of the COVID-19 pandemic in early 2020 challenged the role of climate change as a routine issue. We use extensive news media and Twitter data to explore if and how the pandemic as a so-called killer issue has shifted public attention away from the issue of climate change in Switzerland. Results show that the climate debate fell victim to the impact of the COVID-19 pandemic in the news media and the Twitter-sphere. Given the vast dominance of the pandemic, there is a strong indication this finding applies similarly to various other issues. Additional hashtag co-occurrence analysis shows that some climate activists react to this development and try to connect the issue of climate change to the pandemic. We argue that suppression of climate change by the pandemic is a problem for its long-term resolution, as it seems to have turned climate change back into a struggling issue. [ABSTRACT FROM AUTHOR]

Almost since the advent of the Internet, there has been great interest in analyzing and understanding online communication from the perspective of public sphere theory. The question of whether the properties of the Internet and, specifically, social media actually contribute to the public sphere is the matter of ongoing and somewhat heated scientific debate. The aim of the article is twofold. First, we propose a hierarchical model of generalized functions of public sphere. On a theoretical level, we interweave different strands of thought on the public sphere, and the resulting model is more inclusive and less rigid than each of those strands on their own. We identify four generalized functions: identity building, agenda-setting, control and criticism, and deliberation. The Internet does not contribute equally to these functions and we evaluate the impact of the Internet on each of these functions as a diminishing marginal utility. Second, we empirically explore the plausibility of our model in a global comparative analysis with focus on the Internet. With the help of macro-level variables which indicate the structural preconditions for a public sphere, we identify the highest possible function of the public sphere for each country to which the Internet can potentially contribute. Based on this approach, future research can be contextualized: case-study-based research can plausibly articulate expectations regarding the impact of the Internet on the public sphere.

Comparative approaches are frequently used in communication research, especially journalism studies. The purpose of this article is to argue that Bayesian multilevel regression is the most justifiable option for analyzing comparative data. We argue that it is the only approach that can simultaneously account for the non-atomicity (nested nature) and non-stochasticity (nonrandom sampling) of comparative data. Using the openly available Worlds of Journalism Study and useNews data sets, we demonstrate how to apply the Bayesian approach for the analysis of comparative data. We address the common challenges when using the Bayesian approach and highlight the advantages of posterior predictive checks for modeling checking. [ABSTRACT FROM AUTHOR]