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Show & Tell – Social Media-Data in Research Practice II (fall/winter 2022/23)
Show & Tell – Social Media-Data in Research Practice II (fall/winter 2022/23)
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Lecture Series: "Show & Tell – Social Media Data in Research Practice II" (online) The working group "Social Media-Daten", initiated by NFDI4Culture in cooperation with BERD@NFDI, KonsortSWD and Text+ as part of the National Research Data Infrastructure Germany (NFDI), hosted three instalments of its lecture series during the fall/winter term 2022/23. The lecture series "Show & Tell – Social Media Data in Research Practice" is dedicated to the tools in the field of social media research. In each zoom hour short input talks should aim to highlight best practices and selected research projects. In addition to pragmatic solutions and technical features (software, interfaces, repositories, metadata standards, interoperability ...), points of focus lie on ethical and legal barriers (personal and individual rights, copyrights) in the creation and evaluation of data sets and corpora, as well as the sustainable, secure and critical handling of them (code and data literacy, FAIR & CARE). Last but not least, we would like to invite scholars to discuss interdisciplinary research approaches and teaching methods that stress both traditional and subject-specific frameworks and tools. We met for a first round of three talks on the topic of 'Twitter Tools', 'Social Media-Corpora' and 'multimodal data' during the summer term. This fall/winter we dealt with 'Reddit Data', 'Memes, Platform Data, and Computer Vision' as well as 'Social Bots' and their detection with an overall focus on available APIs as well as custom built tools. Please find abstracts as well as links to slides and articles below. PROGRAMME of the lecture series: "Show & Tell – Social Media-Daten in der Forschungspraxis II" (in cooperation with BERD@NFDI, KonsortSWD, NFDI4Culture and Text+ as part of the National Research Data Infrastructure Germany (NFDI)) 11.11. Doing Social Research with Reddit (Show & Tell IV) Anna-Carolina Haensch (LMU München): Things to know when working with reddit data (slides) Social media are becoming more popular as a source of data for researchers in many disciplines. These data are plentiful and offer the potential to answer new research questions at smaller geographies and for rarer subpopulations. When deciding whether to use data from social media, it is useful to learn as much as possible about the data and its source. Social media data have properties quite different from those with which many researchers are used to working, so the assumptions often used to plan and manage a project may no longer hold. For example, social media data are so large that they may not be able to be processed on a single machine; they are in file formats with which many researchers are unfamiliar, and they require a level of data transformation and processing that has rarely been required when using more traditional data sources (e.g. survey data). Unfortunately, this type of information is often not obvious ahead of time as much of this knowledge is gained through word-of-mouth and experience. In this talk, we attempt to document several challenges and opportunities encountered when working with Reddit, the self-proclaimed “front page of the Internet” and popular social media site. In addition, we introduce two APIs that researchers can use to compile reddit data corpora tailored to their specific research needs in short time. Ruben Bach, Alexander Wenz (MZES/Universität Mannheim): Gender roles in parenting discussions during the Covid-19 pandemic on reddit (slides) We study gendered effects of the COVID-19 pandemic on parenting. Measures to prevent the spread of the virus, such as lockdowns and school closures, may have forced mothers to take over more domestic work than fathers, thereby reinforcing traditional gender norms. To detect gendered effects on parenting, we analyze the posting behavior of parents on reddit, a popular social media platform. We collected data from the mother-centered subreddit r/mommit and the father-centered subreddit r/daddit, covering the time before the pandemic (January-November 2019) and during the pandemic (January-November 2020). Overall, our data include 17,902 textual posts by 12,400 Reddit users. Using Latent Dirichlet Allocation topic modeling, we find evidence for gendered patterns in parenting during the COVID-19 pandemic: While mothers are more involved in discussing different aspects of daily life, such as the preparation of food, housekeeping, and school issues, fathers are rather concerned with special occasion events, such as becoming a father. Moreover, mothers are more likely to manage the pandemic life of their families and to cope with upcoming problems related to school closures and lockdown-activities with their children. We conclude that the unpaid labor of mothers seems to be of great importance in coping with the effects of this public health crisis. 16.12. Memespector (Show & Tell V) Elena Pilipets, Jason Chao (Universität Siegen): Memespector – Memes, Platform Data, and Computer Vision (slides)(slides) Memespector GUI is an open-source tool that aims to support investigations both with and about computer vision Application Programming Interfaces (APIs) by enabling users to repurpose, audit, and critically examine their outputs in the context of image research. The first part of the session provides a technical definition of computer vision and focuses on what kinds of outputs computer vision APIs produce (Jason Chao). The second part of the session focuses on using Memespector GUI to analyze larger online image collections with particular attention to their memetic potential and contextual specificity. Drawing on a series of case studies, we will discuss different platform-mediated characteristics (imitation, resonance, multi-situatedness) that constitute memes as networked media objects and data multiplicities (Elena Pilipets). 20.01. Social Bots (Show & Tell VI) Franziska Martini (FU Berlin / Weizenbaum Institut): Bot, oder nicht? – Erkennungsmethoden für Social Bots auf Twitter aus sozialwissenschaftlicher Perspektive (article) Die sozialwissenschaftliche Forschung zu Social Bots interessiert sich vor allem für Fragen nach ihrem Einfluss auf die (politische) Online-Kommunikation, wie etwa die Beeinflussung von Diskursdynamiken, die Manipulation der Meinungsbildung oder die Verbreitung von Desinformation. Bevor jedoch der Einfluss von Social Bots empirisch untersucht werden kann, müssen die automatisierten Accounts zunächst einmal erkannt werden – ein Problem, welchem zwar in Disziplinen wie der Informatik viel Aufmerksamkeit geschenkt wird, das aber in sozialwissenschaftlichen Studien nur selten explizit thematisiert wird. Es sollen daher zunächst praktische Einblicke in die Forschung mit frei zugänglichen Social-Bot-Erkennungsmethoden für Twitter gegeben werden. Anschließend werden die grundlegenden Probleme bei der Verwendung solcher Tools diskutiert, unter anderem in Bezug auf die Validität und Replizierbarkeit der Ergebnisse, die oft mangelnde Transparenz bezüglich Trainingsdaten und Kriterien von Machine-Learning-Klassifikatoren sowie die schwierige Vergleichbarkeit früherer, auf unterschiedlichen Methoden basierender Studien. Dennis Assenmacher (GESIS Köln), Christian Grimme (Westfälische Wilhelms-Universität Münster): Social Bot – Entwicklung einer Technologie und eines Kampfbegriffs (slides) Der Begriff 'Social Bot' wird landläufig genutzt, um unterschiedlich weit entwickelte oder auch nur vorgestellte Automatisierung in sozialen Netzwerken durch Dritte zu beschreiben. Wurde das Phänomen Social Bot 2016 und 2017 noch genutzt, um Manipulation im Kontext des Brexit-Referendums oder die Wahl von Donald Trump zu erklären, hat sich der Begriff inzwischen auch zu einem Kampfbegriff zur Diskreditierung von Gesprächspartnern in öffentlichen Diskussionen entwickelt. Dieser Vortrag versucht eine differenzierte Betrachtung des Begriffes, indem auf die Evolution der technischen Eigenschaften und Fähigkeiten von Social Bots eingegangen wird. Dies zeigt sowohl die Spannbreite der zugrundeliegenden Logik, als auch die zukünftigen Potenziale, offenbart jedoch auch die Schwierigkeiten in der eindeutigen Detektion von Automatisierung. Zugleich wagen wir einen datengetriebenen Blick auf die Verwendung des Begriffes 'Social Bot' und auf die Polarisierung, die von diesem Begriff in Wissenschaft und Gesellschaft ausgeht. contact: christoph.eggersgluess (at) uni-marburg.de
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https://nfdi4culture.de/news/show-tell-social-media-data-in-research-practice-ii.html
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Show & Tell – Social Media-Data in Research Practice II (fall/winter 2022/23)
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Show & Tell – Social Media-Data in Research Practice II (fall/winter 2022/23)
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Art History
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Media Studies
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Qualification & Reuse
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Digital Humanities
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Brief Report
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https://nfdi4culture.de//fileadmin/user_upload/stock-images/Alina_Grubnyak_Web.jpeg
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Christoph Eggersglüß
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Lecture and discussion series "Show & Tell – Social Media Data in Research Practice"
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Show & Tell – Social Media-Data in Research Practice II (fall/winter 2022/23)
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2023-02-16T16:57:07+01:00
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https://nfdi4culture.de/resource/E3609.json
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