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Social Media Research Methods
The presentation by Dr. Katrin Weller discusses social media research methods, highlighting both new approaches and challenges faced by researchers in the field. It emphasizes the advantages of social media data, such as spontaneous interactions and rich multimedia content, while also addressing issues like lack of theoretical background and representativeness. Different research methods, including surveys, experiments, and content analysis, are mentioned as tools for studying user interactions and practices on platforms like Facebook and Twitter.
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Social Media Research Methods
- 1. Social Media ResearchMethods. New Approaches and Open Challenges Dr. Katrin Weller katrin.weller@gesis.org, @kwelle, http://katrinweller.net Presentation at Advanced Course “Uses and effects of social media” HHU Düsseldorf 26.11.2013
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- 3. Facebook vs. Twitter Scopus(26.11.2013) (TITLE-ABS-KEY(Twitter) AND PUBYEAR > 2006) (TITLE-ABS-KEY(Facebook) AND PUBYEAR > 2004)
- 4. Facebook AND Twitter 4975 2007-2013 Scopus:Facebook Scopus: Twitter scopus: Facebook AND Twitter 1274 4975 4136 1274 4136
- 5. Scopus: TITLE-ABS-KEY(facebook), searchedon 26.11.2013
- 6. Scopus: TITLE-ABS-KEY(twitter) ANDPUBYEAR > 2006 searched on 26.11.2013
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- 8. What is beingstudied? • • • • • • • • • • User groups Events Audiences Practices Information flow Influence Opinions and sentiments Networks Interactions …
- 9. How to studysocial media? „information disclosure and privacy on Facebook“ „Election prediction with Twitter data“
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- 12. Social Media Data • • • • • • • Texts Images Videos Mixedformats Connections I (friends, followers) Connections II (links/URLs) Connections/Actions (likes, favs, comments, downloads)
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- 15. Data Collection andAccess? API
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- 19. Approaches • • • • Surveys Experiments Interviews Web ethnography • Contentanalysis • Network analysis • Linguistic analyses (eg. sentiment analysis) Rather rarely used in combination
- 20. Content Analysis • E.g.with MAXQDA, QDAMiner, ATLAS.ti, Qualrus, Nvivo
- 21. Network Analysis • E.g.with R, NodeXL
- 22. Sentiment Analysis • Mainlybased on dictionaries such as ANEW http://link.springer.com/article/10.1007%2Fs 10902-009-9150-9/fulltext.html
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- 24. #1 Observing spontaneous interactions andephemeral communication
- 25. #2 Access to datafor a variety of contexts and questions
- 26. #3 Rich data: multimedia contentplus networks plus interactions
- 27. #4 Interdisciplinary field, option toexperiment with new and combined methods
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- 31. #2 data haves, datahave-nots boyd, danah and Kate Crawford. (2012). “Critical Questions for Big Data”
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- 34. Exciting work ahead! KatrinWeller @kwelle katrin.weller@gesis.org http://katrinweller.net www.gesis.org
- 35. References • • • • • • • Ackland, R. (2013).Web Social Science. Los Angeles et al: SAGE. Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication, & Society, 15(5), 662-679. Bruns, A. (2013). Faster than the speed of print: Reconciling ‘big data’ social media analysis and academic scholarship. First Monday 10(18). Available http://firstmonday.org/ojs/index.php/fm/article/view/4879 Giglietto, F., Rossi, L., & Bennato, D. (2012). The Open Laboratory: Limits and Possibilities of Using Facebook, Twitter, and YouTube as a Research Data Source. Journal of Technology in Human Services, 30(3-4), 145–159. Karpf, D. (2012). Social science research methods in internet time. Information, Communication & Society, 5(15), 639-661. Weller, K., Bruns, A., Burgess, J., Mahrt, M., & Puschmann, C. (2014). Twitter and Society. New York et al.: Peter Lang. Williams, S. A., Terras, M. M., Warwick, C. (2013). What do people study when they study Twitter? Classifying Twitter related academic papers. Journal of Documentation, 69(3), 384-410.