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11
Nov
2022

Doing Social Research with Reddit (Show & Tell IV)

Die Vortrags- und Diskussionsreihe: "Show & Tell – Social Media-Daten in der Forschungspraxis" ist eine Kooperationsveranstaltung von NFDI4Culture, KonsortSWD und Text+. Diese findet im Rahmen der Nationalen Forschungsdateninfrastruktur statt.

Am 11. November um 14:00 Uhr lädt der Arbeitskreis „Social Media-Daten“, der auf Initiative von NFDI4Culture gemeinsam mit BERD@NFDI, KonsortSWD und Text+ im Rahmen der Nationalen Forschungsdateninfrastruktur betrieben wird, zur ersten öffentlichen Veranstaltung der Reihe „Show & Tell – Social Media-Daten in der Forschungspraxis“ im Wintersemester ein.

Zum Auftakt wird es in zwei Beiträgen von Anna-Carolina Haensch (LMU München) sowie Ruben Bach und Alexander Wenz (MZES/Universität Mannheim) unter dem Titel „Doing Social Research with Reddit“ um die Herausforderungen und Möglichkeiten zweier APIs und im Speziellen um Genderrollen auf dieser Plattform gehen.

Die Reihe „Show & Tell – Social Media-Daten in der Forschungspraxis“ widmet sich in kurzen Inputs den Tools im Feld der Social Media-Forschung. In je einer guten Zoom-Stunde möchte sie Best Practices und ausgewählte Forschungsprojekte beleuchten. Im Fokus stehen neben pragmatischen Lösungen und technischen Möglichkeiten (Software, Schnittstellen, Repositorien, Metadatenstandards, Interoperabilität …) u. a. die ethischen und rechtlichen Schranken (Persönlichkeits- und Urheberrechte) bei der Anlage und Auswertung von Datensets und Korpora sowie der nachhaltige, sichere und kritische Umgang damit (Code and Data Literacy, FAIR & CARE). Nicht zuletzt wollen wir dazu einladen, interdisziplinäre Forschungsansätze und Lehrmethoden zu diskutieren, die tradierte wie fachspezifische Rahmen und Werkzeuge strapazieren. Die ersten Talks fanden im Sommersemester zu ‚Twitter Tools‘, ‚Social Media-Korpora‘ und ‚multimodalen Daten‘ statt.

Programm

11.11. Doing Social Research with Reddit (Show & Tell IV)

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.

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)

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)

(tbc – weitere Termine folgen)

Koordination: christoph.eggersgluess (at) uni-marburg.de