Challenging social media analytics

Tinati, Ramine; Phillipe, Olivier; Pope, Catherine; Carr, Les; Halford, Susan

doi:10.1145/2615569.2615690

Cited by 6 publications

(4 citation statements)

References 34 publications

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“…Consequently, the way SMA is applied and understood may significantly differ. While researchers from computational sciences are equipped with sophisticated methods for the analysis of social media data, they are often less concerned with methodological underpinnings and theoretical models, which researchers from social science employ to make sense out of social media data (Stieglitz et al, 2018;Tinati, Phillipe, Pope, Carr, & Halford, 2014).…”

Section: Relevance Cycle -Institutional Challenges Of Ethical Sma Res...mentioning

confidence: 99%

‘Cambridge Moralica’ - Towards an Ethical Framework for Social Media Analytics

Jung

Clausen

Franzke

et al. 2022

AJIS

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En route to the unravelling of today’s multiplicity of societal challenges, making sense of social data has become a crucial endeavour in Information Systems (IS) research. In this context, Social Media Analytics (SMA) has evolved to a promising field of data-driven approaches, guiding researchers in the process of collecting, analysing, and visualising social media data. However, the handling of such sensitive data requires careful ethical considerations to protect data subjects, online communities, and researchers. Hitherto, the field lacks consensus on how to safeguard ethical conduct throughout the research process. To address this shortcoming, this study proposes an extended version of a SMA framework by incorporating ethical reflection phases as an addition to methodical steps. Following a design science approach, existing ethics guidelines and expert interviews with SMA researchers and ethicists serve as the basis for redesigning the framework. It was eventually assessed through multiple rounds of evaluation in the form of focus group discussions and questionnaires with ethics board members and SMA experts. The extended framework, encompassing a total of five iterative ethical reflection phases, provides simplified ethical guidance for SMA researchers and facilitates the ethical self-examination of research projects involving social media data.

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Section: Relevance Cycle -Institutional Challenges Of Ethical Sma Res...mentioning

confidence: 99%

‘Cambridge Moralica’ - Towards an Ethical Framework for Social Media Analytics

Jung

Clausen

Franzke

et al. 2022

AJIS

View full text Add to dashboard Cite

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“…Chen et al 2014). Similarly, Tinati et al (2014) propose to analyze Twitter data via content analysis and quantitative measures (e.g., number of followers, interaction with others, retweets, etc.) to provide a richer and more contextualized view of the data.…”

Section: Combining Social Media Analysis Approachesmentioning

confidence: 99%

“…Second, applying a mixed method approach generates beneficial insights that are superior to those findings that will be received from performing a singular analysis approach that either prioritizes structured or unstructured data (e.g., Chen et al 2014;Tinati et al 2014). As an example, by the target-oriented combination of analysis approaches, it is not only possible to cluster user suggestions on how to improve the product or service portfolio by topic and sentiment, but also to easily deduce a ranking of these propositions, e.g., based on "likes" and "shares" immediately.…”

Section: Contribution For Practicementioning

confidence: 99%

UR: SMART–A tool for analyzing social media content

Schwaiger

Hammerl

Johannsen

et al. 2021

Inf Syst E-Bus Manage

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The digital transformation, with its ongoing trend towards electronic business, confronts companies with increasingly growing amounts of data which have to be processed, stored and analyzed. Instant access to the “right” information at the time it is needed is crucial and thus, the use of techniques for the handling of big amounts of unstructured data, in particular, becomes a competitive advantage. In this context, one important field of application is digital marketing, because sophisticated data analysis allows companies to gain deeper insights into customer needs and behavior based on their reviews, complaints as well as posts in online forums or social networks. However, existing tools for the automated analysis of social content often focus on one general approach by either prioritizing the analysis of the posts’ semantics or the analysis of pure numbers (e.g., sum of likes or shares). Hence, this design science research project develops the software tool UR:SMART, which supports the analysis of social media data by combining different kinds of analysis methods. This allows deep insights into users’ needs and opinions and therefore prepares the ground for the further interpretation of the voice. The applicability of UR:SMART is demonstrated at a German financial institution. Furthermore, the usability is evaluated with the help of a SUMI (Software Usability Measurement Inventory) study, which shows the tool’s usefulness to support social media analyses from the users’ perspective.

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“…Die Sozialwissenschaften sollen sich den Herausforderun-Big Social Media Data als epistemologische Herausforderung für die Soziologie gen durch die neuen Daten und Methoden stellen und zudem interdisziplinäre Zusammenarbeiten eingehen(Savage/Burrows 2007;Ruppert 2013). Die technischen Fähigkeiten und die Programmierkenntnisse der Informatiker/innen könnten sich so mit fundierten Kenntnissen sozialwissenschaftlicher Methoden und analytischer Interpretation ergänzen(Tinati et al 2014). Die epistemologische Strategie, die in der Big-Data-Forschung zur Anwendung kommen könnte, wäre damit eine, die wissens-und theoriegeleitet potentielle Fragen oder Hypothesen identifiziert, die einer weitergehenden Untersuchung wert sind.Neben explorativen, interdisziplinären Epistemologien werden auch neue Modelle notwendig, um Partizipation abzubilden.Sieber und Haklay (2015) weisen am Beispiel von Geoinformationssystemen darauf hin, dass in der Forschung mit nutzergenerierten Internetdaten häufig auf der Basis einer Epistemologie gearbeitet wird, die von der Erzeugung der Daten durch Experten ausgeht; etwa verschiedene Grade gewollter und ungewollter Partizipation an der Erzeugung dieser Daten werden oft nicht berücksichtigt.Eine Epistemologie für Big-Data-Forschung mit Social-Media-Daten muss sich zudem der spezifischen Blindheiten der Forschung bewusst sein, sich auf existierende, auch kritische soziale Theorien beziehen und anerkennen, dass Forschung nicht neutral oder objektiv ist, sondern immer von einem bestimmten Standpunkt aus unternommen wird, und zudem, dass Datensätze, Forschung und Interpretationen immer auch von politischen oder strategischen Überlegungen durchzogen sind.…”

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Soziologie des Digitalen - Digitale Soziologie?

Maasen¹,

Passoth²

2020

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About ten years ago, we were still able to justify the reservations of sociology with regard to digitisation as a healthy caution against the hype of the ‘virtual world’ and ‘cyberspace’; today, the situation looks different: beyond the usual rhetoric of media revolutions, new forms of practice, organisation and order have emerged around digital technologies in more or less all fields, posing tangible challenges to sociological theory-building, methods development and empirical social research. Are our theories based on action, communication or practice suitable for describing the contribution of algorithms? Are our methods for dealing with language, images and printed text suitable for analysing the automatic modification of texts, images and videos by filter technologies? How do we deal with increasing competition in data analysis and evaluation? These are the questions that this special volume of the journal ‘Soziale Welt’ (ISSN 0038-6073) explores. With contributions by Dirk Baecker, Sascha Dickel, Tobias Wolbring, Barbara Sutter, Sabine Maasen, Elke Wagner, Niklas Barth, Katharina Kinder-Kurlanda, Roger Häußling, Udo Thiedeke, Josef Wehner, Nicole Zillien, Bernadette Kneidinger-Müller, Heike Greschke, Jagoda Motowidlo, René König, Patrik Sumpf, Christian Stegbauer, Alexander Mehler, Oliver Nachtwey, Philipp Staab, Andreas Boes, Tobias Kämpf, Alexander Zielger, Sabine Pfeiffer, Anne Suphan, Uli Meyer, Uwe Matzat, Erik van Ingen, Christian Papsdorf, Tanja Carstensen, Jeffrey Wimmer, John Postill, Victor Lasa, Ge Zhang, Evelyn Ruppert

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Challenging social media analytics

Cited by 6 publications

References 34 publications

‘Cambridge Moralica’ - Towards an Ethical Framework for Social Media Analytics

‘Cambridge Moralica’ - Towards an Ethical Framework for Social Media Analytics

UR: SMART–A tool for analyzing social media content

Soziologie des Digitalen - Digitale Soziologie?

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