Digitale Märkte und Öffentlichkeiten auf Plattformen
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- ItemThe Love of Large Numbers Revisited: A Coherence Model of the Popularity Bias(2020) Heck, Daniel W.; Seiling, Lukas; Bröder, ArndtPreferences 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.
- ItemDynamics of opinion expression(2020) Gaisbauer, Felix; Olbrich, Eckehard; Banisch, SvenModeling 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.
- ItemTwitter Explorer: A Framework for Observing Twitter through Interactive Networks(2021) Pournaki, Armin; Gaisbauer, Felix; Banisch, Sven; Olbrich, EckehardWe 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.
- ItemIdeological differences in engagement in public debate on Twitter(2021) Gaisbauer, Felix; Pournaki, Armin; Banisch, Sven; Olbrich, Eckehard; Guidi, BarbaraThis 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.
- ItemDigitale Öffentlichkeit und liberale Demokratie(Bundeszentrale für politische Bildung, 2022) Neuberger, Christoph; Bundeszentrale für politische Bildung
- ItemÖffentlich-rechtlicher Rundfunk und Plattformen: Programmatik, Prinzip, Praxis, Projekt(Nomos, 2022) Neuberger, Christoph; Gerlach, Frauke; Eilders, Christiane
- ItemHow 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, PhilippThe 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.
- ItemInformation 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.
- ItemGute 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.
- ItemOSD2F: 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, KasperThe 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.
- ItemDigitale Öffentlichkeit und liberale Demokratie(2022) Neuberger, Christoph
- ItemModelling Spirals of Silence and Echo Chambers by Learning from the Feedback of Others(2022) Banisch, Sven; Gaisbauer, Felix; Olbrich, EckehardWhat 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.
- ItemThe paradox of knowing more and less: Audience metrics and the erosion of epistemic standards on the internet(2022) Haim, Mario; Neuberger, ChristophDer 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.
- ItemExtracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach(2022) Fan, Yangliu; Lehmann, Sune; Blok, AndersAs 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.
- ItemSicherheit und Freiheit in der digitalen Öffentlichkeit(transcript, 2023) Neuberger, Christoph; Saam, Nicole J.; Bielefeldt, Heiner
- ItemCOVID-19 and the Internet: Lessons Learned(Emerald Publishing Limited, 2023) Stocker, Volker; Lehr, William; Smaragdakis, Georgios; Whalley, Jason; Stocker, Volker; Lehr, WilliamThe COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new nor- mal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post- COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.
- ItemMessage Deletion on Telegram: Affected Data Types and Implications for Computational Analysis(Taylor & Francis, 2023) Bühling, KilianEphemeral 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.
- ItemProceedings of the Weizenbaum Conference 2023. AI, Big Data, Social Media and People on the Move(Weizenbaum Institute, 2023) Berendt, Bettina; Krzywdzinski, Martin; Kuznetsova, ElizavetaThe 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.
- ItemMeasuring Mobile Broadband: Challenges and Implications for Policymaking(2023) Frías, Zoraida; Lehr, William; Stocker, Volker; Mendo, LuisMobile 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.
- ItemNext-generation networks: Necessity of edge sharing(2023) Lehr, William; Stocker, Volker