Open Access-Publikationen

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Are Campaigns Getting Uglier, and Who Is to Blame? Negativity, Dramatization and Populism on Facebook in the 2014 and 2019 EP Election Campaigns
(2023) Klinger, Ulrike; Koc-Michalska, Karolina; Rußmann, Uta
Relating to theories of dissonant public spheres and affective publics, we study negativity, dramatization, and populist content in political party Facebook posts across 12 countries during the 2014 and 2019 European Parliament Election campaigns. A quantitative content analysis of 14,293 posts from 111 (2014) and 116 (2019) political parties shows that negative emotion, negative campaigning, dramatization, and populist content has increased over this time. We show that political parties sought to evoke more negative emotions and generate more dramatization, engaged more in negative campaigning, and included more populist content in their Facebook posts in the 2019 EP election than in 2014. Further, we show that posts evoking negative emotions and dramatization and involving negative campaigning yield higher user engagement than other posts, while populist content also led to more user reactions in 2014, but not in 2019. Negative, exaggerated, and sensationalized messaging therefore makes sense from a strategic perspective, because the increased frequencies of likes, shares, and comments make parties’ messages travel farther and deeper in social networks, thereby reaching a wider audience. It seems that the rise in affective and dissonant communication has not emerged unintentionally, but is also a result of strategic campaigning.
Can Fighting Misinformation Have a Negative Spillover Effect? How Warnings for the Threat of Misinformation Can Decrease General News Credibility
(2023) Van Der Meer, Toni G. L. A.; Hameleers, Michael; Ohme, Jakob
In the battle against misinformation, do negative spillover effects of communicative efforts intended to protect audiences from inaccurate information exist? Given the relatively limited prevalence of misinformation in people’s news diets, this study explores if the heightened salience of misinformation as a persistent societal threat can have an unintended spillover effect by decreasing the credibility of factually accurate news. Using an experimental design (N = 1305), we test whether credibility ratings of factually accurate news are subject to exposure to misinformation, corrective information, misinformation warnings, and news media literacy (NML) interventions relativizing the misinformation threat. Findings suggest that efforts like warning about the threat of misinformation can prime general distrust in authentic news, hinting toward a deception bias in the context of fear of misinformation being salient. Next, the successfulness of NML interventions is not straight forward if it comes to avoiding that the salience of misinformation distorts people’s creditability accuracy. We conclude that the threats of the misinformation order may not just be remedied by fighting false information, but also by reestablishing trust in legitimate news.
Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking
(2023) Ohme, Jakob; Araujo, Theo; Boeschoten, Laura; Freelon, Deen; Ram, Nilam; Reeves, Byron B.; Robinson, Thomas N.
In social media effects research, the role of specific social media content is understudied, in part attributable to the fact that communication science previously lacked methods to access social media content directly. Digital trace data (DTD) can shed light on textual and audio-visual content of social media use and enable the analysis of content usage on a granular individual level that has been previously unavailable. However, because digital trace data are not specifically designed for research purposes, collection and analysis present several uncertainties. This article is a collaborative effort by scholars to provide an overview of how three methods of digital trace data collection - APIs, data donations, and tracking - can be used in studying the effects of social media content in three important topic areas of communication research: misinformation, algorithmic bias, and well-being. We address the question of how to collect raw social media content data and arrive at meaningful measures with multiple state-of-the-art data collection techniques that can be used to study the effects of social media use on different levels of detail. We conclude with a discussion of best practices for the implementation of each technique, and a comparison of their advantages and disadvantages.
Gute Wissenschaftskommunikation in der digitalen Welt. Politische, ökonomische, technische und regulatorische Rahmenbedingungen ihrer Qualitätssicherung
(Berlin-Brandenburgische Akademie der Wissenschaften, 2022) Weingart, Peter; Wormer, Holger; Schildhauer, Thomas; Fähnrich, Birte; Jarren, Otfried; Neuberger, Christoph; Passoth, Jan-Hendrik; Wagner, Gert G.
Die Interdisziplinäre Arbeitsgruppe „Implikationen der Digitalisierung für die Qualität der Wissenschaftskommunikation“ der BBAW hat von 2018 bis 2021 untersucht, wie sich die Qualität der Wissenschaftskommunikation unter den Bedingungen der Digitalisierung verändert und welche Herausforderungen sich aus den Veränderungen für die aufgeklärte Meinungsbildung in der Demokratie ergeben. Im vorliegenden Heft erfolgt eine Beschreibung und Analyse der Kontextfaktoren von Wissenschaftskommunikation in der digitalen Medienumwelt, der damit verbundenen wissenschaftspolitischen Veränderungen, von medienökonomischen Faktoren für die Qualitätssicherung der Wissenschaftskommunikation und der soziotechnischen Veränderungen. Es werden zudem die Herausforderungen bei der Regulierung von Plattformen zur Qualitätssicherung von Wissenschaftskommunikation skizziert und Empfehlungen für Akteur:innen des Wissenschaftssystems sowie Gesetzgeber und Regulierer formuliert.
“Intervening Is a Good Thing but . . .”: The Role of Social Norms in Users’ Justifications of (Non-)Intervention Against Incivility
(2023) Gagrčin, Emilija; Milzner, Miriam
User intervention against incivility as social enforcement of democratic norms on social media platforms is considered an act of “good citizenship” by citizens and scholars alike. However, between ideals and behavior, multiple social norms are at play in shaping individuals’ sense of personal responsibility for intervening. This study explores the role of conflicting norms in situations requiring user intervention against online incivility. By combining the perspectives of norms as expectations and norms as cultural vocabularies, we investigate users’ salient norms, and how these norms influence users’ justifications for (non-)intervention. Based on qualitative interview data from Germany (N = 20), we identified three distinct reasoning patterns employed to justify (non-)intervention: the pragmatic, the dismissive, and the aspirational. By identifying fault lines, our typology points to normative origins of ambivalence related to user intervention. The findings offer insights into strategies to motivate intervention against online incivility.
Mapping a Dark Space: Challenges in Sampling and Classifying Non-Institutionalized Actors on Telegram
(2023) Jost, Pablo; Heft, Annett; Bühling, Kilian; Zehring, Maximilian; Schulze, Heidi; Bitzmann, Hendrik; Domahidi, Emese
Crafted as an open communication platform characterized by high anonymity and minimal moderation, Telegram has garnered increasing popularity among activists operating within repressive political contexts, as well as among political extremists and conspiracy theorists. While Telegram offers valuable data access to research non-institutionalized activism, scholars studying the latter on Telegram face unique theoretical and methodological challenges in systematically defining, selecting, sampling, and classifying relevant actors and content. This literature review addresses these issues by considering a wide range of recent research. In particular, it discusses the methodological challenges of sampling and classifying heterogeneous groups of (often non-institutionalized) actors. Drawing on social movement research, we first identify challenges specific to the characteristics of non-institutionalized actors and how they become interlaced with Telegram’s platform infrastructure and requirements. We then discuss strategies from previous Telegram research for the identification and sampling of a study population through multistage sampling procedures and the classification of actors. Finally, we derive challenges and potential strategies for future research and discuss ethical challenges.
Message Deletion on Telegram: Affected Data Types and Implications for Computational Analysis
(Taylor & Francis, 2023) Bühling, Kilian
Ephemeral digital trace data can decrease the completeness, reproducibility, and reliability of social media datasets. Systematic post deletions thus potentially bias the results of computational methods used to map actors, content, and online information diffusion. Therefore, the aim of this study was to assess the extent and distribution of message deletion across different data types using data from the hybrid messenger service Telegram, which has experienced an influx of deplatformed users from mainstream social media platforms. A repeatedly scraped sample of messages from public Telegram groups and channels was used to investigate the effect of message ephemerality on the consistency of Telegram datasets. The findings revealed that message deletion introduces biases to the computational collection and analysis of Telegram data. Further, message ephemerality reduces dataset consistency, the quality of social network analyses, and the results of computational content analysis methods, such as topic modeling or dictionaries. The implications of these findings for scholars aiming to use Telegram data for computational research, possible solutions, and contributions to the methodological advancement of studying online political communication are discussed further in this article.
Next-generation networks: Necessity of edge sharing
(2023) Lehr, William; Stocker, Volker
Pandemic protesters on Telegram: How platform affordances and information ecosystems shape digital counterpublics
(2023) Bühling, Kilian; Heft, Annett
This study analyzes how platform affordances, their appropriation by movement actors, and these actors’ leveraging of information ecosystems—in combination—helped form a digital counterpublic during the COVID-19 pandemic. It draws on public communication data sent by more than 300 Telegram channels and group chats affiliated with the Querdenken movement over a 2-year period, and combines automated and manual text classification with network analysis. The study demonstrates how Telegram afforded connective and collective action in distinct ways that reflected the movement’s organizational structure and aims, as well as the impact of individual information-sharing on the process of movement-building itself. Accounting for time-dependent dynamics, the study also found that different parts of the counterpublic latched onto and sustained distinct information ecosystems to articulate their claims and mobilize contentious action.
Search engines in polarized media environment: Auditing political information curation on Google and Bing prior to 2024 US elections
(2025) Makhortykh, Mykola; Rorhbach, Tobias; Sydorova, Maryna; Kuznetsova, Elizaveta
Search engines play an important role in the context of modern elections. By curating information in response to user queries, search engines influence how individuals are informed about election-related developments and perceive the media environment in which elections take place. It has particular implications for (perceived) polarization, especially if search engines' curation results in a skewed treatment of information sources based on their political leaning. Until now, however, it is unclear whether such a partisan gap emerges through information curation on search engines and what user- and system-side factors affect it. To address this shortcoming, we audit the two largest Western search engines, Google and Bing, prior to the 2024 US presidential elections and examine how these search engines' organic search results and additional interface elements represent election-related information depending on the queries' slant, user location, and time when the search was conducted. Our findings indicate that both search engines tend to prioritize left-leaning media sources, with the exact scope of search results' ideological slant varying between Democrat- and Republican-focused queries. We also observe limited effects of location- and time-based factors on organic search results, whereas results for additional interface elements were more volatile over time and specific US states. Together, our observations highlight that search engines' information curation actively mirrors the partisan divides present in the US media environments and has the potential to contribute to (perceived) polarization within these environments.
Stochastic lies: How LLM-powered chatbots deal with Russian disinformation about the war in Ukraine
(2024) Makhortykh, Mykola; Sydorova, Maryna; Baghumyan, A; Vziatysheva, Victoria; Kuznetsova, Elizaveta
Research on digital misinformation has turned its attention to large language models (LLMs) and their handling of sensitive political topics. Through an AI audit, we analyze how three LLM-powered chatbots (Perplexity, Google Bard, and Bing Chat) generate content in response to the prompts linked to common Russian disinformation narratives about the war in Ukraine. We find major differences between chatbots in the accuracy of outputs and the integration of statements debunking Russian disinformation claims related to prompts’ topics. Moreover, we show that chatbot outputs are subject to substantive variation, which can result in random user exposure to false information.
The public sphere as a dynamic network
(2023) Friemel, Thomas N.; Neuberger, Christoph
This article proposes to conceptualize the public sphere as a dynamic network of actors and contents that are linked with each other by communicative actions. This perspective allows us to theoretically derive and empirically describe the entire range of small to large network structures and their evolution over time. First, we will define the elements of these networks, which include the actors, content, communicative actions, and content relations. Based on these entities, four communicative roles (producer, recipient, curator, isolate) will be distinguished. Second, we will summarize how these actors perceive the communicative situation and how they select from behavioral options. Third, we will show how this combines with the network dynamics and outcomes that are discussed in the different lines of research. This provides not only the basis for understanding the link between the communicative actions on the micro-level and macro-level structures, but also new avenues for normative discussions.
Veiled conspiracism: Particularities and convergence in the styles and functions of conspiracy-related communication across digital platforms
(2025) Buehling, Kilian; Zhang, Xixuan; Heft, Annett
Digital communication venues are essential infrastructures for anti-democratic actors to spread harmful content such as conspiracy theories. Capitalizing on platform affordances, they leverage conspiracy theories to mainstream their political views in broader public discourse. We compared the word choice, language style, and communicative function of conspiracy-related content to understand its platform-dependent differences and convergence. Our cases are the conspiracy theories of the New World Order and Great Replacement, which we analyzed on 4chan/pol/, Twitter, and seven alternative US news media longitudinally from 2011 to 2021. The conspiracy-related texts were comparatively analyzed using a multi-method approach of computational and quantitative text analyses. Our results show that conspiracy narrations are increasingly present in all venues. While language differs vastly between platforms, we observed a style convergence between Twitter and 4chan. The results show how more coded language veils the spread of racist and antisemitic content beyond the so-called dark platforms.

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Auflistung Open Access-Publikationen nach Forschungsbereichen "Digitale Märkte und Öffentlichkeiten auf Plattformen"

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