Digitale Märkte und Öffentlichkeiten auf Plattformen

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A Common Effort: New Divisions of Labor Between Journalism and OSINT Communities on Digital Platforms
(2024) Charlton, Timothy; Mayer, Anna-Theresa; Ohme, Jakob
This article explores the interactions between journalistic actors and emerging open-source intelligence and investigation (OSINT) communities. It employs qualitative content analysis of discourse from two OSINT communities surrounding three events following the Russian invasion of Ukraine in 2022, which received substantial coverage in news media. OSINT practices are rapidly becoming a mainstay of the contemporary political process by allowing ordinary citizens to verify information shared through digital platforms, which is traditionally the societal task assigned to journalism. In doing so, they provide a timely factual baseline for opinion formation and political decision-making. This research explores the role constellations resulting from this shift in verification duties from journalistic actors to amateur online communities on digital platforms and maps the fundamental dynamics involved in OSINT. We analyze how information is received and processed in OSINT communities, how digital platforms facilitate the fact-checking process, and how journalism and OSINT interact. Based on our findings, we develop a theoretical framework that distinguishes between the input, throughput, and output phases of OSINT. Our model contributes to a baseline understanding of the crucial and novel partnership between citizens and journalists on digital platforms.
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.
Augmenting Data Download Packages – Integrating Data Donations, Video Metadata, and the Multimodal Nature of Audio-visual Content
(2024) Wedel, Lion; Ohme, Jakob; Araujo, Theo
This research explores the potential of augmented Data Download Packages (aDDPs) as a novel approach to analyze digital trace data, using TikTok as a use case to demonstrate the broader applicability of the method. The study demonstrates how these data packages can be used in social science research to understand better user behavior, content consumption patterns, and the relationship between self-reported preferences and actual digital behavior.We introduce the concept of aDDPs, which extend the conventional Data Download Packages (DDPs) by augmenting the collected data with survey data, metadata, content data, and multimodal content embeddings, among other possibilities - rendering aDDPs an unprecedentedly rich data source for social science research. This work provides an overview and guidance on collecting, augmenting DDPs, and analyzing the resulting aDDPs.In a pilot study on 18 aDDPs, we use the combination of data components in aDDPs to facilitate research on user engagement behavior and content classification. We showcase the potential of the information breadth and depth that aDDPs depict by exploiting the combination of multimodal content embeddings, the users’ watch history, and survey data. To do so, we train and compare uni- and multimodal classifiers, classify the 18 aDDPs’ videos, and investigate the extent to which user engagement behavior impacts future content suggestions. Furthermore, we compare the users retrieved content with the users’ self-reported content consumption.
Book review: Schützeneder, Jonas & Graßl, Michael. (Eds.). (2022). Journalismus und Instagram. Analysen, Strategien, Perspektiven aus Wissenschaft und Praxis [Journalism and Instagram. Analyses, strategies, perspectives from science and practice]. Springer Fachmedien.
(2023) Mayer, Anna-Theresa
Instagram spielt heute eine wichtige Rolle in der digitalen Medienlandschaft. Laut ARD/ZDF-Onlinestudie 2023 (vgl. Koch, W.: Soziale Medien werden 30 Minuten am Tag genutzt – Instagram ist die Plattform Nummer eins. Ergebnisse der ARD/ZDF-Onlinestudie 2023. Media Perspektiven, 2023, 26, S. 1–8) greifen 25 % der deutschsprachigen Bevölkerung täglich auf die Social-Media-Plattform zurück, 35 % mindestens einmal wöchentlich. Besonders in der jüngeren Altersgruppe ist ihre Beliebtheit erkennbar (täglich: 63 %; mindestens einmal wöchentlich: 79 %). Auch journalistische Inhalte sind längst auf Instagram verfügbar. Während man bereits im internationalen Kontext erste empirische Ansätze zur Erforschung und in der Praxisliteratur einige Reflektionen über das Zusammenspiel von Journalismus und Instagram findet, sind systematische Übersichtswerke zum (deutschen) Journalismus auf Instagram noch rar. Hier setzt der Sammelband „Journalismus und Instagram. Analysen, Strategie, Perspektive aus Wissenschaft und Praxis“ mit der übergreifenden Fragestellung an, „wie sich Journalismus und Instagram aus kommunikationswissenschaftlicher Perspektive analysieren lassen und welche praktischen Beispiele hierzu dienlich sind“ (S. 2–3). Das Ergebnis sind 17 Beiträge von insgesamt 27 Autorinnen und Autoren, die sich in drei Zugänge einteilen lassen.
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.
Cascades or salmons? Longitudinal upstream and downstream effects of political participation
(2024) Ohme, Jakob; Azrout, Rachid; Moeller, Judith
Digitally networked and new, unconventional activities allow citizens to participate politically in activities that are low in the effort and risks they bear. At the same time, low-effort types of participation are more loosely connected to democratic political systems, thereby challenging established modes of political decision-making. This can set in motion two competing dynamics: While some citizens move closer to the political system in their activities (upstream effects), others engage in political activities more distant from it (downstream effects). This study investigates non-electoral participation trajectories and tests intra-individual change in political participation types over time, exploring whether such dynamics depend on citizens’ exposure to political information. Utilizing a three-wave panel survey (n = 3490) and random intercept cross-lagged panel models with SEM, we find more evidence for downstream effects but detect overall diverse participation trajectories over time and a potentially crucial role of elections for non-electoral participation trajectories.
Chatting about the unaccepted: Self-disclosure of unaccepted news exposure behaviour to a chatbot
(2023) Ischen, Carolin; Butler, Janice; Ohme, Jakob
Conversational technologies such as chatbots have shown to be promising in eliciting self-disclosure in several contexts. Implementing such a technology that fosters self-disclosure can help to assess sensitive topics such as behaviours that are perceived as unaccepted by others, i.e. the exposure to unaccepted (alternative) news sources. This study tests whether a conversational (chatbot) format, compared to a traditional web-based survey, can enhance self-disclosure in the political news context by implementing a two-week longitudinal, experimental research design (n = 193). Results show that users disclose unaccepted news exposure signiﬁcantly more often to a chatbot, compared to a traditional web-based survey, providing evidence for a chatbots’ ability to foster the disclosure of sensitive behaviours. Unlike our hypotheses, our study also shows that social presence, intimacy, and enjoyment cannot explain self-disclosure in this context, and that self-disclosure generally decreases over time.
Comparative Digital Political Communication: Comparisons Across Countries, Platforms, and Time
(2024) Boulianne, Shelley; Larsson, Anders O.
Comparative communication research needs to catch up to other disciplines. In this special issue and the associated International Communication Association preconference, we focus on comparative work related to digital political communication. This introduction argues that comparative digital political communication needs to consider comparisons across various dimensions, including countries, platforms, and time, whereas existing comparative communication research focuses on country or territorial comparison. We highlight the six submissions’ approaches to comparative work. Each submission provides at least one of these three dimensions of contrast. We conclude with a discussion of enduring gaps in this field of research, such as the lack of studies using time as a dimension of comparison. Time is crucial for understanding ever-changing digital media platforms. We also conclude by discussing some ongoing challenges in political communication research.
Crisis Communication on Twitter: Differences Between User Types in Top Tweets About the 2015 “Refugee Crisis” in Germany
(2023) Kapidzic, Sanja; Frey, Felix; Neuberger, Christoph; Stieglitz, Stefan; Mirbabaie, Milad
The study explores differences between three user types in the top tweets about the 2015 “refugee crisis” in Germany and presents the results of a quantitative content analysis. All tweets with the keyword “Flüchtlinge” posted for a monthlong period following September 13, 2015, the day Germany decided to implement border controls, were collected (N = 763,752). The top 2,495 tweets according to number of retweets were selected for analysis. Differences between news media, public and private actor tweets in topics, tweet characteristics such as tone and opinion expression, links, and specific sentiments toward refugees were analyzed. We found strong differences between the tweets. Public actor tweets were the main source of positive sentiment toward refugees and the main information source on refugee support. News media tweets mostly reflected traditional journalistic norms of impartiality and objectivity, whereas private actor tweets were more diverse in sentiments toward refugees.
Datafication Markers: Curation and User Network Effects on Mobilization and Polarization During Elections
(2023) Gagrčin, Emilija; Ohme, Jakob; Buttgereit, Lina; Grünewald, Felix
Social media platforms are crucial sources of political information during election campaigns, with datafication processes underlying the algorithmic curation of newsfeeds. Recognizing the role of individuals in shaping datafication processes and leveraging the metaphor of news attraction, we study the impact of user curation and networks on mobilization and polarization. In a two-wave online panel survey (n = 943) conducted during the 2021 German federal elections, we investigate the influence of self-reported user decisions, such as following politicians, curating their newsfeed, and being part of politically interested networks, on changes in five democratic key variables: vote choice certainty, campaign participation, turnout, issue reinforcement, and affective polarization. Our findings indicate a mobilizing rather than polarizing effect of algorithmic election news exposure and highlight the relevance of users’ political networks on algorithmic platforms.
Delegated Regulation on Data Access Provided for the Digital Services Act
(Weizenbaum Institute, 2023) Klinger, Ulrike; Ohme, Jakob
Response to the Call for Evidence DG CNECT-CNECT F2 by the European Commission
Digital Inclusion Through Algorithmic Knowledge: Curated Flows of Civic and Political Information on Instagram
(2024) Boulianne, Shelley; Hoffmann, Christian P.
Social media platforms are a critical source of civic and political information. We examine the use of Instagram to acquire news as well as civic and political information using nationally representative survey data gathered in 2019 in the US, the UK, France, and Canada (n = 2,440). We investigate active curation practices (following news organizations, political candidates or parties, and nonprofit organizations or charities) and passive curation practices (liking friends’ political posts and those from parties or politicians and nonprofits or charities). Young adults (18 to 24 years) are far more likely to curate their Instagram feed than older adults in all four countries. We consider two possible explanations for this behavior: political interest and an understanding of how algorithms work. Young adults have more (self-assessed) knowledge of algorithms in all four countries. Algorithmic knowledge relates to curation practices, but there are some cross-national differences. Algorithmic knowledge is theoretically relevant for passive curation practices and the UK sample provides support for the stronger role of algorithmic knowledge in passive than active curation. In all four countries, political interest positively relates to active and passive curation practices. These findings challenge depictions of young adults as news avoiders; instead, they demonstrate that algorithmic knowledge can help curate the flow of information from news organizations as well as civic and political groups on Instagram. While algorithmic knowledge enables youth’s digital inclusion, for older adults, the lack of knowledge may contribute to digital exclusion as they do not know how to curate their information flows.
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.
Digitale Öffentlichkeit und liberale Demokratie
(Bundeszentrale für politische Bildung, 2022) Neuberger, Christoph; Bundeszentrale für politische Bildung
Digitale Öffentlichkeit und liberale Demokratie
(2022) Neuberger, Christoph
Dynamics of opinion expression
(2020) Gaisbauer, Felix; Olbrich, Eckehard; Banisch, Sven
Modeling efforts in opinion dynamics have to a large extent ignored that opinion exchange between individuals can also have an effect on how willing they are to express their opinion publicly. Here, we introduce a model of public opinion expression. Two groups of agents with different opinion on an issue interact with each other, changing the willingness to express their opinion according to whether they perceive themselves as part of the majority or minority opinion. We formulate the model as a multigroup majority game and investigate the Nash equilibria. We also provide a dynamical systems perspective: Using the reinforcement learning algorithm of Q-learning, we reduce the N-agent system in a mean-field approach to two dimensions which represent the two opinion groups. This two-dimensional system is analyzed in a comprehensive bifurcation analysis of its parameters. The model identifies social-structural conditions for public opinion predominance of different groups. Among other findings, we show under which circumstances a minority can dominate public discourse.
Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach
(2022) Fan, Yangliu; Lehmann, Sune; Blok, Anders
As science is becoming more interdisciplinary and potentially more data driven over time, it is important to investigate the changing specialty structures and the emerging intellectual patterns of research ﬁelds and domains. By employing a clustering-based network approach, we map the contours of a novel interdisciplinary domain – research using social media data – and analyze how the specialty structures and intellectual contributions are organized and evolve. We construct and validate a large-scale (N = 12,732) dataset of research papers using social media data from the Web of Science (WoS) database, complementing it with citation relationships from the Microsoft Academic Graph (MAG) database. We conduct cluster analyses in three types of citation-based empirical networks and compare the observed features with those generated by null network models. Overall, we ﬁnd three core thematic research subﬁelds – interdisciplinary socio-cultural sciences, health sciences, and geo-informatics – that designate the main epicenter of research interests recognized by this domain itself. Nevertheless, at the global topological level of all networks, we observe an increasingly interdisciplinary trend over the years, fueled by publications not only from core ﬁelds such as communication and computer science, but also from a wide variety of ﬁelds in the social sciences, natural sciences, and technology. Our results characterize the specialty structures of this domain at a time of growing emphasis on big social data, and we discuss the implications for indicating interdisciplinarity.
Fulfilling data access obligations: How could (and should) platforms facilitate data donation studies?
(2024) Hase, Valerie; Ausloos, Jef; Boeschoten, Laura; Pfiffner, Nico; Janssen, Heleen; Araujo, Theo; Carrière, Thijs; de Vreese, Claes; Haßler, Jörg; Loecherbach, Felicia; Kmetty, Zoltán; Möller, Judith; Ohme; Schmidbauer, Elisabeth; Struminskaya, Bella; Trilling, Damian; Welbers, Kasper; Haim, Mario
Research into digital platforms has become increasingly difficult. One way to overcome these difficulties is to build on data access rights in EU data protection law, which requires platforms to offer users a copy of their data. In data donation studies, researchers ask study participants to exercise this right and donate their data to science. However, there is increasing evidence that platforms do not comply with designated laws. We first discuss the obligations of data access from a legal perspective (with accessible, transparent, and complete data as key requirements). Next, we compile experiences from social scientists engaging in data donation projects as well as a study on data request/access. We identify 14 key challenges, most of which are a consequence of non-compliance by platforms. They include platforms’ insufficient adherence to (a) providing data in a concise and easily accessible form (e.g. the lack of information on when and how subjects can access their data); (b) being transparent about the content of their data (e.g. the lack of information on measures); and (c) providing complete data (e.g. the lack of all available information platforms process related to platform users). Finally, we formulate four central recommendations for improving the right to access.
Grounding force-directed network layouts with latent space models
(2023) Gaisbauer, Felix; Pournaki, Armin; Banisch, Sven; Olbrich, Eckehard
Force-directed layout algorithms are ubiquitously used tools for network visualization. However, existing algorithms either lack clear interpretation, or they are based on techniques of dimensionality reduction which simply seek to preserve network-immanent topological features, such as geodesic distance. We propose an alternative layout algorithm. The forces of the algorithm are derived from latent space models, which assume that the probability of nodes forming a tie depends on their distance in an unobserved latent space. As opposed to previous approaches, this grounds the algorithm in a plausible interaction mechanism. The forces infer positions which maximise the likelihood of the given network under the latent space model. We implement these forces for unweighted, multi-tie, and weighted networks. We then showcase the algorithm by applying it to Facebook friendship, and Twitter follower and retweet networks; we also explore the possibility of visualizing data traditionally not seen as network data, such as survey data. Comparison to existing layout algorithms reveals that node groups are placed in similar configurations, while said algorithms show a stronger intra-cluster separation of nodes, as well as a tendency to separate clusters more strongly in multi-tie networks, such as Twitter retweet networks.
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.

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Auflistung Digitale Märkte und Öffentlichkeiten auf Plattformen nach Forschungsgruppen "Dynamiken digitaler Nachrichtenvermittlung"

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