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I Am Dissolving into Categories and Labels - Agency Affordances for Embedding and Practicing Digital Sovereignty
Get PDFWhile the notion of digital sovereignty is loaded with a multitude of meanings referring to various actors, values and contexts, this paper is interested in how to actualize individual digital sovereignty. We do so by introducing the concept of agency affordances, which we see as a precondition for achieving digital sovereignty. We understand this notion as the ability to exercise power to, as autonomy and agency for (digital) self-sovereignty, and as power over the infrastructural sovereignty of the privately owned automated decision-making systems (ADM) systems of digital media platforms. Building our characterization of digital sovereignty on an empirical inquiry into individuals' requirements for agency, our analysis shows that digital sovereignty consists of two distinct but interrelated elements - data sovereignty and algorithmic sovereignty. Enabling practicable digital sovereignty through agency affordances, however, will require going beyond the just technical and extending towards the wider societal (infra)structures. We outline some initial steps on how to achieve that.This work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII111, 16DII112, 16DII113, 16DII114, 16DII115, 16DII116, 16DII117 – „Deutsches Internet-Institut“
Algorithm dependency in platformized news use
Get PDFPrevious research has highlighted the ambiguous experience of algorithmic news curation whereby people are simultaneously comfortable with algorithms, but also concerned about the underlying data collection practices. The present article builds on media dependency theory and news-finds-me (NFM) perceptions to explore this tension. Empirically, we analyze original survey data from six European countries (Germany, Sweden, France, Greece, Poland, and Italy, n = 2,899) to investigate how young Europeans’ privacy concerns and attitudes toward algorithms affect NFM. We find that a more positive attitude toward algorithms and more privacy concerns are related to stronger NFM. The study highlights power asymmetries in platformized news use and suggests that the ambivalent experiences might be a result of algorithm dependency, whereby individuals rely on algorithms in platformized news use to meet their information needs, despite accompanying risks and concerns
The rise of metric-based digital status: an empirical investigation into the role of status perceptions in envy on social networking sites
Get PDFWidespread on social networking sites (SNSs), envy has been linked to an array of detrimental outcomes for users’ well-being. While envy has been considered a status-related emotion and is likely to be experienced in response to perceiving another’s higher status, there is a lack of research exploring how status perceptions influence the emergence of envy on SNSs. This is important because SNSs typically quantify social interactions and reach with metrics that indicate users’ relative rank and status in the network. To understand how status perceptions impact SNS users, we introduce a new form of metric-based digital status rooted in SNS metrics that are available and visible on a platform. Drawing on social comparison theory and status literature, we conducted an online experiment to investigate how different forms of status contribute to the proliferation of envy on SNSs. Our findings shed light on how metric-based digital status influences feelings of envy on SNSs. Specifically, we could show that metric-based digital status impacts envy through increasing perceptions of others’ socioeconomic and sociometric statuses. Our study contributes to the growing discourse on the negative out comes associated with SNS use and its consequences for users and society.The research by Antonia Meythaler, Hannes-Vincent Krause, Annika Baumann and Hanna Krasnova was supported by the German Federal Ministry of Education and Research under grant no. 16DII127 and 16DII131
Weizenbaum Panel’s Literature Digest: February 2023
No full textDer Literatur Digest ist eine monatlich erscheinende Zusammenstellung des aktuellen Forschungsstandes zu Themen an der Schnittstelle zwischen Digitalisierung und Politik. Er präsentiert die neuesten Erkenntnisse zu Fragen der politischen Partizipation und guter Bürgerschaft in Zeiten der Digitalisierung.
Zusätzlich zum PDF bieten wir den Digest im BibTeX-Austauschformat an.The Literature Digest is a monthly compilation of the current state of research on topics at the nexus of digitalization and politics. It presents the latest findings on issues of political participation and good citizenship in times of digitalization.
In addition, we provide this Literature Digest as BibTeX file.This work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII111, 16DII112, 16DII113, 16DII114, 16DII115, 16DII116, 16DII117 – „Deutsches Internet-Institut“
Diversity and bias in DBpedia and Wikidata as a challenge for text-analysis tools
Get PDFDiversity Searcher is a tool originally developed to help analyse diversity in news media texts. It relies on automated content analysis and thus rests on prior assumptions and depends on certain design choices related to diversity. One such design choice is the external knowledge source(s) used. In this article, we discuss implications that these sources can have on the results of content analysis. We compare two data sources that Diversity Searcher has worked with – DBpedia and Wikidata – with respect to their ontological coverage and diversity, and describe implications for the resulting analyses of text corpora. We describe a case study of the relative over- or underrepresentation of Belgian political parties between 1990 and 2020. In particular, we found a staggering overrepresentation of the political right in the English-language DBpedia.We thank the Fonds Wetenschappelijk Onderzoek – Vlaanderen (FWO) for funding DIAMOND under project code S008817N
“They just won't listen”—The role of blame in narratives of past extreme weather events for anticipating future crisis
Get PDFThe phase before an extreme weather event is crucial for the actual reaction to the impacts of such an event. In this phase, professionals in the field of civil protection and emergency management anticipate the intensity and impact of the event and use these expectations for action. We argue that anticipation is—beyond others—shaped by the organizations’ shared narratives of past crisis that resulted from extreme weather events. The findings focus on the frame of ‘blame’ in the narration and are based on two fields of study, road maintenance services and forest fire control. Qualitative group discussions and semistructured interviews show two very different views on blame depending on the organization: human factors and fate. This contrast can be traced back to the character of the weather events itself, but also with the self‐image of the organization and perceived external expectations. Depending on the narrative plot and threshold of the event, narratives can affect and alter practices of anticipation through narrations of renewal. Findings contribute to the understanding of organizational sensemaking through narratives of blame and consequences.Bundesministerium für Verkehr und Digitale Infrastruktur, Grant/Award Number: DWD2014P3
Machine Learning and the End of Theory: Reflections on a Data-Driven Conception of Health
Get PDFTaking the notion of health as a leitmotif, this paper discusses some conceptual boundaries for using machine learning - a data-driven, statistical, and computational technique in the field of artificial intelligence - for epistemic purposes and for generating knowledge about the world based solely on the statistical correlations found in data (i.e., the "End of Theory" view).The thrust of the argument is that prior theoretical conceptions, subjectivity, and values would - because of their normative power - inevitably blight any effort at knowledge-making that seeks to be exclusively driven by data and nothing else. The conclusion suggests that machine learning will neither resolve nor mitigate the serious internal contradictions found in the "biostatistical theory" of health - the most well-discussed data-driven theory of health. The definition of notions such as these is an ongoing and fraught societal dialogue where the discussion is not only about what is, but also about what should be. This dialogical engagement is a question of ethics and politics and not one of mathematics.This work has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII111, 16DII112, 16DII113, 16DII114, 16DII115, 16DII116, 16DII117 – „Deutsches Internet-Institut“
Im Maschinenraum politischer Repräsentation: Über den Umgang mit politischen Grundbegriffen in der digitalen Konstellation
Get PDFMaking Arguments with Data: Resisting Appropriation and Assumption of Access/Reason in Machine Learning Training Processes
Get PDFThis article presents an approach to practicing ethics when working with large datasets and designing data representations. Inspired by feminist critique of technoscience and recent problematizations of digital literacy, we argue that machine learning models can be navigated in a multi-narrative manner when access to training data is well articulated and understood. We programmed and used web-based interfaces to sort, organize, and explore a community-run digital archive of radio signals. An additional perspective on the question of working with datasets is offered from the experience of teaching image synthesis with freely accessible online tools. We hold that the main challenge to social transformations related to digital technologies comes from lingering forms of colonialism and extractive relationships that easily move in and out of the digital domain. To counter both the unfounded narratives of techno-optimismand the universalizing critique of technology, we discuss an approachto data and networks that enables a situated critique of datafication and correlationism from within.This publication has been funded by the Federal Ministry of Education and Research of Germany (BMBF) (grant no.: 16DII121, 16DII122, 16DII123, 16DII124, 16DII125, 16DII126, 16DII127, 16DII128 – “Deutsches Internet-Institut”)
Transnational issue agendas of the radical right? Parties’ Facebook campaign communication in six countries during the 2019 European Parliament election
Get PDFIn this study, we investigate to what degree radical right parties use social media for pushing a common issue agenda to mobilise voters on a pan-European scale. Using the 2019 European Parliament (EP) election as a case, we analysed radical right parties’ campaign agendas in Austria, France, Germany, Italy, Poland and Sweden and identified the transnationally shared issue repertoire in their Facebook communication. Based on the structural topic modelling we used for analysis, our results reveal a set of shared issues – immigration and blaming elites –which are typical of the populist core of those parties. Moreover, all parties use social media to draw attention to the election itself. While radical right parties mobilise their voters based on a transnationally recurring set of shared issues, national political opportunity structures account for party-specific topics and national adaptations of shared issues in their campaigns on Facebook