Digitale Märkte und Öffentlichkeiten auf Plattformen

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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.
The Love of Large Numbers Revisited: A Coherence Model of the Popularity Bias
(2020) Heck, Daniel W.; Seiling, Lukas; Bröder, Arndt
Preferences are often based on social information such as experiences and recommendations of other people. The reliance on social information is especially relevant in the case of online shopping, where buying decisions for products may often be based on online reviews by other customers. Recently, Powell, Yu, DeWolf, and Holyoak (2017, Psychological Science, 28, 1432-1442) showed that, when deciding between two products, people do not consider the number of product reviews in a statistically appropriate way as predicted by a Bayesian model but rather exhibit a bias for popular products (i.e., products with many reviews). In the present work, we propose a coherence model of the cognitive mechanism underlying this empirical phenomenon. The new model assumes that people strive for a coherent representation of the available information (i.e., the average review score and the number of reviews). To test this theoretical account, we reanalyzed the data of Powell and colleagues and ran an online study with 244 participants using a wider range of stimulus material than in the original study. Besides replicating the popularity bias, the study provided clear evidence for the predicted coherence effect, that is, decisions became more confident and faster when the available information about popularity and quality was congruent.
Twitter Explorer: A Framework for Observing Twitter through Interactive Networks
(2021) Pournaki, Armin; Gaisbauer, Felix; Banisch, Sven; Olbrich, Eckehard
We present an open-source interface for scientists to explore Twitter data through interactive network visualizations. Combining data collection, transformation and visualization in one easily accessible framework, the twitter explorer connects distant and close reading of Twitter data through the interactive exploration of interaction networks and semantic networks. By lowering the technological barriers of data-driven research, it aims to attract researchers from various disciplinary backgrounds and facilitates new perspectives in the thriving field of computational social science.
Ideological differences in engagement in public debate on Twitter
(2021) Gaisbauer, Felix; Pournaki, Armin; Banisch, Sven; Olbrich, Eckehard; Guidi, Barbara
This article analyses public debate on Twitter via network representations of retweets and replies. We argue that tweets observable on Twitter have both a direct and mediated effect on the perception of public opinion. Through the interplay of the two networks, it is possible to identify potentially misleading representations of public opinion on the platform. The method is employed to observe public debate about two events: The Saxon state elections and violent riots in the city of Leipzig in 2019. We show that in both cases, (i) different opinion groups exhibit different propensities to get involved in debate, and therefore have unequal impact on public opinion. Users retweeting far-right parties and politicians are significantly more active, hence their positions are disproportionately visible. (ii) Said users act significantly more confrontational in the sense that they reply mostly to users from different groups, while the contrary is not the case.
OSD2F: An Open-Source Data Donation Framework
(2022) Araujo, Theo; Ausloos, Jef; van Atteveldt, Wouter; Loecherbach, Felicia; Moeller, Judith; Ohme, Jakob; Trilling, Damian; van de Velde, Bob; De Vreese, Claes H.; Welbers, Kasper
The digital traces that people leave through their use of various online platforms provide tremendous opportunities for studying human behavior. However, the collection of these data is hampered by legal, ethical, and technical challenges. We present a framework and tool for collecting these data through a data donation platform where consenting participants can securely submit their digital traces. This approach leverages recent developments in data rights that have given people more control over their own data, such as legislation that now mandates companies to make digital trace data available on request in a machine-readable format. By transparently requesting access to specific parts of this data for clearly communicated academic purposes, the data ownership and privacy of participants is respected, and researchers are less dependent on commercial organizations that store this data in proprietary archives. In this paper we outline the general design principles, the current state of the tool, and future development goals.
Information processing on smartphones in public versus private
(2022) Ohme, Jakob; Searles, Kathleen; De Vreese, Claes H.
People increasingly turn to news on mobile devices, often while out and about, attending to daily tasks. Yet, we know little about whether attention to and learning from information on a mobile differs by the setting of use. This study builds on Multiple Resource Theory (Wickens, 1984) and the Resource Competition Framework (Oulasvirta et al., 2005) to compare visual attention to a dynamic newsfeed, varying only the setting: private or public. We use mobile eye-tracking to evaluate the effects of setting on attention and assess correspondent learning differences after exposure to the feed, which allows us to uncover a relationship between attention and learning. Findings indicate higher visual attention to mobile newsfeed posts in public, relative to a private setting. Moreover, scrolling through news on a smartphone in public attenuates some knowledge gain but is beneficial for other learning outcomes.
Digitale Öffentlichkeit und liberale Demokratie
(2022) Neuberger, Christoph
The paradox of knowing more and less: Audience metrics and the erosion of epistemic standards on the internet
(2022) Haim, Mario; Neuberger, Christoph
Der Journalismus ist für moderne Demokratien wichtig, weil er valides Wissen über aktuelle Ereignisse in Form von Nachrichten produziert. Gesellschaftlich akzeptierte epistemische Standards und die professionelle Objektivitätsnorm tragen zum gesellschaftlichen Wissensvorrat bei und ermöglichen fundierte Entscheidungen. Ergänzt wird diese journalistische Funktion der Umweltbeobachtung durch das Wissen über das Publikum. Das Wissen über das Publikum bestimmt sowohl die Erwartungen des Journalismus als auch jene der Rezipierenden an das Mitpublikum. Es ermöglicht die Herausbildung gemeinsamer epistemischer Standards, wodurch sich das Risiko von Kritik bei der Teilnahme am öffentlichen Diskurs verringert. Die veränderten Möglichkeiten und auch Notwendigkeiten der Publikumsbeobachtung im Internet haben den Weg dafür geebnet, dass sich Redaktionen mit maßgeschneiderten epistemischen Standards an das erwartete Publikum wenden. Ein solcher zielgruppenspezifischer Zuschnitt epistemischer Standards steht im Gegensatz zu geteilten Normen und hat zum Paradoxon geführt, dass die Zunahme des Wissens über das Publikum möglicherweise mit weniger gemeinsam geteiltem Wissen über aktuelle Ereignisse einhergeht, weil professionelle Standards nicht mehr geteilt werden. Auf der Grundlage dieser Diagnose diskutieren wir zwei mögliche Zukunftspfade für epistemische Standards im Internet: einen negativen, bei dem die Polarisierung aufgrund einer verstärkten Identifikation mit epistemisch distinkten Zielgruppen zunehmen könnte, und einen positiven, bei dem diskursive Räume einen institutionalisierten Diskurs epistemischer Standards zwischen Journalismus und Publikum ermöglichen.
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.
Modelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others
(2022) Banisch, Sven; Gaisbauer, Felix; Olbrich, Eckehard
What are the mechanisms by which groups with certain opinions gain public voice and force others holding a different view into silence? Furthermore, how does social media play into this? Drawing on neuroscientific insights into the processing of social feedback, we develop a theoretical model that allows us to address these questions. In repeated interactions, individuals learn whether their opinion meets public approval and refrain from expressing their standpoint if it is socially sanctioned. In a social network sorted around opinions, an agent forms a distorted impression of public opinion enforced by the communicative activity of the different camps. Even strong majorities can be forced into silence if a minority acts as a cohesive whole. On the other hand, the strong social organisation around opinions enabled by digital platforms favours collective regimes in which opposing voices are expressed and compete for primacy in public. This paper highlights the role that the basic mechanisms of social information processing play in massive computer-mediated interactions on opinions.
Digitale Öffentlichkeit und liberale Demokratie
(Bundeszentrale für politische Bildung, 2022) Neuberger, Christoph; Bundeszentrale für politische Bildung
Öffentlich-rechtlicher Rundfunk und Plattformen: Programmatik, Prinzip, Praxis, Projekt
(Nomos, 2022) Neuberger, Christoph; Gerlach, Frauke; Eilders, Christiane
How to capture the relations and dynamics within the networked public sphere? Modes of interaction as a new concept
(Nomos, 2022) Neuberger, Christoph; Krämer, Benjamin; Müller, Philipp
The aim of this chapter is to suggest ways to better capture the diversity of constellations and the dynamics of interactions in the public sphere, triggered by the digital transformation. The starting point is the question of why relations and dynamics should be considered more in communica tion studies and how they have been researched so far. In this respect, the limits of public sphere theory and social network analysis (SNA) are discussed. To overcome these limits, I propose a theoretical framework that combines public sphere theory and SNA with – as a third and new concept – modes of interaction. Such modes of interaction are ideal-typical patterns of interaction between actors in different constellations – namely, diffusion, mobilization, conflict, cooperation, competition, and scandal. Afterwards, I discuss these modes of interaction in the context of different societal subsystems and phases of media change in order to demonstrate their heuristic value. Traditional mass media foster the universalization of competition in several dimensions because competition requires only one- way relations of observation and influence. The Internet supports the interactive, multi-stage, and sequential communication that is characteristic of conflict and cooperation.
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.
Measuring Mobile Broadband: Challenges and Implications for Policymaking
(2023) Frías, Zoraida; Lehr, William; Stocker, Volker; Mendo, Luis
Mobile broadband networks constitute essential infrastructure to enable a wide range of innovative services and use cases anticipated for our digital economy future. Measuring performance is essential in many ways. First, to allow service providers to manage and develop their networks. Second, for the efficient operation of markets, and third, for evidence-based policymaking. In the rapidly evolving digital economy, capabilities for collecting more fine-grained measurements and analytics that deliver insights to enable real-time network management and localized control are expanding. As the fundamental methods used to collect measurement data are changing, the ecosystem of stakeholders with strategic interests in mobile measurement is growing and becoming more complex, posing challenges and opportunities for policymakers. Against the background of this growing complexity, this paper aims to discuss some basic features of a capable and reliable measurement ecosystem for mobile broadband. We document how the mobile broadband measurement ecosystem has changed and discuss its implications on a number of important broadband policy issues.
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
In Generative AI we Trust: Can Chatbots Effectively Verify Political Information?
(arXiv, 2023) Kuznetsova, Elizaveta; Makhortykh, Mykola; Vziatysheva, Victoria; Stolze, Martha; Baghumyan, Ani; Urman, Aleksandra
This article presents a comparative analysis of the ability of two large language model (LLM)-based chatbots, ChatGPT and Bing Chat, recently rebranded to Microsoft Copilot, to detect veracity of political information. We use AI auditing methodology to investigate how chatbots evaluate true, false, and borderline statements on five topics: COVID-19, Russian aggression against Ukraine, the Holocaust, climate change, and LGBTQ+ related debates. We compare how the chatbots perform in high- and low-resource languages by using prompts in English, Russian, and Ukrainian. Furthermore, we explore the ability of chatbots to evaluate statements according to political communication concepts of disinformation, misinformation, and conspiracy theory, using definition-oriented prompts. We also systematically test how such evaluations are influenced by source bias which we model by attributing specific claims to various political and social actors. The results show high performance of ChatGPT for the baseline veracity evaluation task, with 72 percent of the cases evaluated correctly on average across languages without pre-training. Bing Chat performed worse with a 67 percent accuracy. We observe significant disparities in how chatbots evaluate prompts in high- and low-resource languages and how they adapt their evaluations to political communication concepts with ChatGPT providing more nuanced outputs than Bing Chat. Finally, we find that for some veracity detection-related tasks, the performance of chatbots varied depending on the topic of the statement or the source to which it is attributed. These findings highlight the potential of LLM-based chatbots in tackling different forms of false information in online environments, but also points to the substantial variation in terms of how such potential is realized due to specific factors, such as language of the prompt or the topic.
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.
Proceedings of the Weizenbaum Conference 2023. AI, Big Data, Social Media and People on the Move
(Weizenbaum Institute, 2023) Berendt, Bettina; Krzywdzinski, Martin; Kuznetsova, Elizaveta
The contributions focus on the question of what role different digital technologies play for “people on the move” - with “people on the move” being understood both spatially (migration and flight) and in terms of economic and social change (changing working conditions, access conditions). The authors discuss phenomena such as disinformation and algorithmic bias from different perspectives, and the possibilities, limits and dangers of generative artificial intelligence.
Conditions of Campaigning in Dissonant Public Spheres and Crisis of Democracy
(2023) Pfetsch, Barbara
Political campaigns have always been closely related to the technical conditions of media infrastructures, the social conditions of voters, and the political opportunities within which parties and movements compete. As campaigning has developed through the four ages of political communication (Blumler, Citation2015; Norris, Citation2002), it is now shaped by the affordances of digital platforms and networked communication ecologies in addition to legacy media infrastructures. In the environment of hybrid media systems (Chadwick, Citation2013), campaigning has also become hybrid – a task divided between the use of conventional information subsidies and the dynamics of social media and digital platforms (Azari, Citation2016; Wells et al., Citation2016). What is more, contemporary political communications and voter mobilization are taking place under two significant context conditions: dissonant public spheres (Pfetsch, Citation2018) are coinciding with a profound crisis of liberal democracy (Bennett & Livingston, Citation2018). The communication ecology and the state of democracy have produced a style of campaigning that is no longer geared toward a consensus among the established political elites and parties to engage in civilized speech, to conduct fair competition, and to stay within the limits and norms of democracy. In this essay, I shall discuss some of the features and consequences of these contextual conditions. I shall further argue that the coincidence of disrupted democracy and dissonant public spheres is related to profound structural changes in the party organization, campaigning and political leadership.

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