Social Media Research Methods. 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

Background

Facebook vs. Twitter

Scopus (26.11.2013) (TITLE-ABS-KEY(Twitter) AND PUBYEAR > 2006) (TITLE-ABS-KEY(Facebook) AND PUBYEAR > 2004)

4136 4975

1274

Facebook AND Twitter

2007-2013

Scopus: Facebook 4975

Scopus: Twitter 4136

scopus: Facebook AND Twitter 1274

Scopus: TITLE-ABS-KEY(facebook), searched on 26.11.2013

Scopus: TITLE-ABS-KEY(twitter) AND PUBYEAR > 2006 searched on 26.11.2013

Researching Social Media?

What is being studied?

• User groups • Events • Audiences • Practices • Information flow • Influence • Opinions and sentiments • Networks • Interactions • …

How to study social media?

„information disclosure and privacy on Facebook“

„Election prediction with Twitter

data“

Social Media Data?

Social Media Data

• Texts

• Images

• Videos

• Mixed formats

• Connections I (friends, followers)

• Connections II (links/URLs)

• Connections/Actions (likes, favs, comments, downloads)

Example: Twitter Data

Example: Twitter Data

Data Collection and Access?

API

https://dev.twitter.com/console

Research Methods

Approaches

• Surveys • Experiments • Interviews • Web ethnography

• Content analysis

• Network analysis • Linguistic analyses (eg. sentiment analysis)

Rather rarely used in combination

Content Analysis

• E.g. with MAXQDA, QDAMiner, ATLAS.ti, Qualrus, Nvivo

Network Analysis

• E.g. with R, NodeXL

Sentiment Analysis

• Mainly based on dictionaries such as ANEW

http://link.springer.com/article/10.1007%2Fs10902-009-9150-9/fulltext.html

Top 4 Chances

#1

Observing spontaneous interactions and ephemeral

communication

#2

Access to data for a variety of contexts and questions

#3

Rich data: multimedia content plus networks plus

interactions

#4

Interdisciplinary field, option to experiment with new and combined methods

Top 4 Challenges

#1

Lack of theoretical background

#2

data haves, data have-nots

boyd, danah and Kate Crawford. (2012).

“Critical Questions for Big Data”

#3

Representativeness?

#4

Missing standards (on different levels)

Exciting work ahead!

Katrin Weller

@kwelle

katrin.weller@gesis.org

http://katrinweller.net

www.gesis.org

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.