Digitale Märkte und Öffentlichkeiten auf Plattformen

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Auflistung Digitale Märkte und Öffentlichkeiten auf Plattformen nach Autor:in "Araujo, Theo"

Gerade angezeigt 1 - 4 von 4
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    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.
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    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.
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    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.
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    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.