Suchergebnisse

Social media represent an important source of news for many users. They are, however, affected by misinformation and they might be playing a role in the growth of political polarization. In this paper, we create an agent based model to investigate how policing content and backlash on social media (i.e. conflict) can lead to an increase in polarization for both users and news sources. Our model is an advancement over previously proposed models because it allows us to study the polarization of both users and news sources, the evolution of the audience connections between users and sources, and it makes more realistic assumptions about the starting conditions of the system. We find that the tendency of users and sources to avoid policing, backlash and conflict in general can increase polarization online. Specifically polarization comes from the ease of sharing political posts, intolerance for opposing points of view causing backlash and policing, and volatility in changing one's opinion when faced with new information. On the other hand, it seems that the integrity of a news source in trying to resist the backlash and policing has little effect.

Many people view news on social media, yet the production of news items online has come under fire because of the common spreading of misinformation. Social media platforms police their content in various ways. Primarily they rely on crowdsourced 'flags': users signal to the platform that a specific news item might be misleading and, if they raise enough of them, the item will be fact-checked. However, real-world data show that the most flagged news sources are also the most popular and—supposedly—reliable ones. In this paper, we show that this phenomenon can be explained by the unreasonable assumptions that current content policing strategies make about how the online social media environment is shaped. The most realistic assumption is that confirmation bias will prevent a user from flagging a news item if they share the same political bias as the news source producing it. We show, via agent-based simulations, that a model reproducing our current understanding of the social media environment will necessarily result in the most neutral and accurate sources receiving most flags.

While political protest is essentially a visual expression of dissent, both social movement research and media studies have thus far been hesitant to focus on visual social media data from protest events. This research explores the visual dimension (photos and videos) of Twitter communication in the Blockupy protests against the opening of the European Central Bank (ECB) headquarters in Frankfurt am Main on 18 March 2015. It does so through a novel combination of quantitative analysis, content analysis of images, and identification of narratives. The article concludes by arguing that the visual in political protest in social media reproduces existing visualities and hierarchies rather than challenges them. This research enhances our conceptual understanding of how activists' struggles play out in the visual and contributes to developing methods for empirical inquiry into visual social media content.

While political protest is essentially a visual expression of dissent, both social movement research and media studies have thus far been hesitant to focus on visual social media data from protest events. This research explores the visual dimension (photos and videos) of Twitter communication in the Blockupy protests against the opening of the European Central Bank headquarters in Frankfurt am Main on 18 March 2015. It does so through a novel combination of quantitative analysis, content analysis of images, and identification of narratives. The article concludes by arguing that the visual in political protest in social media reproduces existing visualities and hierarchies rather than challenges them. This research enhances our conceptual understanding of how activists' struggles play out in the visual and contributes to developing methods for empirical inquiry into visual social media content.

This article investigates the relationship between the invention of new media technologies and scholarship concerning protest and political engagement. Building on an innovative approach that moves beyond a systematic literature review, this article contributes to our understanding of scholarship concerning digital communication technologies and how they may have been adopted and shaped protest movements and political engagement. Based on visualisations, we draw a sociotechnical timeline of protest and media technology scholarship within three dimensions: Technological development, methods and techniques, and the social phenomena under investigation. The article concludes by identifying major trends in protest and media technologies scholarship over the past 15 years. The sociotechnical timeline enhances our understanding of academic discourse at the intersection of protest and media technologies by highlighting shortcomings and potential for future research.

This paper contributes to the ongoing effort to describe and quantify the quality of information that is shared on large social media platforms. We do this by complementing existing research that provided a first quantitative assessment of the quality of the information circulating on Facebook among US users. Leveraging an updated version of the same data source — Meta's URL Shares Dataset — and replicating much of the methodology, we quantify the trustworthy and untrustworthy links to external websites that have been shared on Facebook in the period between 2019 and 2022 in three major European countries (Germany, France, and Italy). We observe a clear decline in the number of URLs present in the dataset and an increase in the URLs from untrustworthy domains as a percentage of the total URLs shared in a year. This increase seems to be higher in electoral years (in Germany and in Italy) but it does not translate into an increase of Views received from untrustworthy sources.

In this article, we reconstruct the academic discourse surrounding social media and elections in an Italian context. We follow Neumayer and Rossi's conceptualization of academic discourse concerning political protest and digital technology as constructed out of three components: (a) the social phenomena under investigation, (b) technological development, and (c) methods and techniques. In the context of social media and elections, these three components may be identified as (a) the research questions that researchers seek to answer, (b) the social media platforms and data used for the analysis, and (c) the methods adopted to analyze the data. While these three dimensions are deeply intertwined, we argue that, when analyzed independently, it is possible to better see both the longitudinal evolution of each dimension and their interdependencies.