Source Criticism of Data Platform Logics on the Internet

Source criticism is an epistemological practice in social and cultural studies that is crucial for specifying the range and scope of the findings, or in other words their validity and reliability. In the context of big data, source criticism is not yet established in the fashion as it is known in other areas of social and cultural research. Currently emerging discussions in historical research emphasize the relevance of source criticism of digital objects or data. In the context of these discussions, this contribution suggests exploring the potentials of source criticism for platform logics. We focus on big data sourced from the internet. Nevertheless our results aim to be transferrable to other sources of big data. The inclusion of source criticism into big data analysis may in turn foster the integration of data-driven analyses into social and cultural studies research approaches. For an integration of source criticism, the paper proposes source critical analyses of information systems, in particular internet platforms, in big data analysis with regard to a) types of big data platforms, b) researchers as data makers, and c) mixed realities of platform usage practices. In analogy to source repertoires (Quellentypen) it suggests to classify internet platforms as providers of particular types of big data sources depending on their infrastructural materiality and ontologies for tracing the key issues of (external) source criticism: provenance, authenticity, and integrity

Data Sprint Learning. Exercising Proximity to Data in Teaching Situations

This paper reports on a data sprint conducted as part of a PhD course on digital methods and data critique at the [University name redacted for peer review]. We reflect on how our data sprint contributed to this higher educational setting, and point to ways in which the data sprint method can be developed further based on our experience. The paper discusses how the sprint fabricated a moment of “critical proximity” for students that were mainly working with qualitative social science methods. The data sprint allowed them to put their critique on “big data” into practice by working with selected sets of data from Twitter and Scopus. We reflect on our collective experience and draw conclusions on the use of data sprints in teaching. Data sprints encourage us to engage with feelings of being underwhelmed and overwhelmed by data that provoke our social science way of critique. Our data sprint tangibly demonstrates that data work is in fact “messy”: transgressing ideals of good data management, biassed, ambiguous and open-ended. But instead of turning away from this “wildness” , we urge to make use of it in teaching settings. This wildness allows to step out of conventional modes of critique, and into modes of action. We conclude with a protocol as a practical guide for everyone who wants to introduce data sprints in their teaching

Kulturanalyse in einem interdisziplinären Kontext: Das Journal kommunikation@gesellschaft

Dieser Artikel erzählt die Entstehungs- und Entwicklungsgeschichte des 2000 gegründeten Open Access-Journals aus Sicht von vier Herausgeber:innen, die die Arbeit und den Inhalt der Zeitschrift mitgeprägt haben. Dieser Artikel ist zuerst in dem Sammelband "Widerständigkeiten des Alltags" (Hamm, Holfelder, Ritter, Schwell & Sutter, 2019) aus Anlass des 60. Geburtstages von Klaus Schönberger erschienen, einem der beiden Gründer und Herausgeber von kommunikation@gesellschaft

Web Futures: Inclusive, Intelligent, Sustainable The 2020 Manifesto for Web Science

International audienceThis Manifesto was produced from the Perspectives Workshop 18262 entitled "10 Years of Web Science" that took place at Schloss Dagstuhl from June 24-29, 2018. At the Workshop, we revisited the origins of Web Science, explored the challenges and opportunities of the Web, and looked ahead to potential futures for both the Web and Web Science. We explain issues that society faces in the Web by the ambivalences that are inherent in the Web. All the enormous benefits that the Web offers-for information sharing, collective organization and distributed activity, social inclusion and economic growth-will always carry along negative consequences, too, and 30 years after its creation negative consequences of the Web are only too apparent. The Web continues to evolve and its next major step will involve Artificial Intelligence (AI) at large. AI has the potential to amplify positive and negative outcomes, and we explore these possibilities, situating them within the wider debate about the future of regulation and governance for the Web. Finally, we outline the need to extend Web Science as the science that is devoted to the analysis and engineering of the Web, to strengthen our role in shaping the future of the Web and present five key directions for capacity building that are necessary to achieve this: (i), supporting interdisciplinarity, (ii), supporting collaboration, (iii), supporting the sustainable Web, (iv), supporting the Intelligent Web, and (v), supporting the Inclusive Web. Our writing reflects our background in several disciplines of the social and technical sciences and that these disciplines emphasize topics to various extents. We are acutely aware that our observations occupy a particular point in time and are skewed towards our experience as Western scholars-a limitation that Web Science will need to overcome

Social Media Monitoring of the Campaigns for the 2013 German Bundestag Elections on Facebook and Twitter

As more and more people use social media to communicate their view and perception of elections, researchers have increasingly been collecting and analyzing data from social media platforms. Our research focuses on social media communication related to the 2013 election of the German parliament [translation: Bundestagswahl 2013]. We constructed several social media datasets using data from Facebook and Twitter. First, we identified the most relevant candidates (n=2,346) and checked whether they maintained social media accounts. The Facebook data was collected in November 2013 for the period of January 2009 to October 2013. On Facebook we identified 1,408 Facebook walls containing approximately 469,000 posts. Twitter data was collected between June and December 2013 finishing with the constitution of the government. On Twitter we identified 1,009 candidates and 76 other agents, for example, journalists. We estimated the number of relevant tweets to exceed eight million for the period from July 27 to September 27 alone. In this document we summarize past research in the literature, discuss possibilities for research with our data set, explain the data collection procedures, and provide a description of the data and a discussion of issues for archiving and dissemination of social media data

Bias in data-driven artificial intelligence systems - An introductory survey

Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions that have far‐reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well‐grounded in a legal frame. In this survey, we focus on data‐driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth

"Book of Anonymity" von Anon Collective

Dies ist eine Rezension über das Buch "Book of Anonymity“ herausgegeben vom Anon Collective, erschienen bei punctum books, 2021, 484 Seiten, ISBN: 9781953035301