What people study when they study Twitter
Start: Feb 28, 2013 05:30 PM
Location: G31, Foster Court
Professor Shirley Williams from the University of Reading will be visiting UCLDH to give an informal talk. All are welcome and there will be a drinks reception in the Arts and Humanities Common room afterwards.
Registration is required for this event: http://www.eventbrite.co.uk/event/5560547748
The microblogging system Twitter was introduced in 2006, and since then over a thousand academic papers have appeared across a range of journals and conferences reporting on studies of Twitter and its use. Twitter’s open interface means that researchers are able to collect vast quantities of data and we are seeing studies undertaken by large teams in which billions of tweets are collected and reviewed with the help of automated tools, alongside smaller studies undertaken by individual or small groups of researchers (Williams, Terras, & Warwick, in press). For example:
- Dodds, Harris, Kloumann, Bliss, and Danforth (2011) in their paper “Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter” describe the collection of 46 billion words over 33 months, and their methodological approach which includes language assessment using Amazon’s Mechanical Turk.
- Lindgren and Lundstrom (2011) in the paper “Pirate culture and hacktivist mobilization: The cultural and social protocols of #Wikileaks on Twitter” include detailed study of 1029 tweets collected from 439 Twitter accounts over a two month period, using the #Wikileaks hashtag, they include in their methodological approach the use of relational text analysis to produce a network from their text corpus describing the linguistic space.
- Kierkegaard (2010) in her paper “Twitter thou doeth?” considers the potential litigation minefield related to Twitter, citing cases with legal implications, the paper is not related to a collection of Twitter data.
In this presentation we identify the basic data used within Twitter studies, leading to a categorization of the data set size. Additionally using open coded content analysis other important categories are also identified, relating to the primary methodology, domain and aspect of the study.
Dodds, P. S., Harris, K. D., Kloumann, I. M., Bliss, C. A., & Danforth, C. M. (2011). Temporal patterns of happiness and information in a global social network: hedonometrics and twitter. PLoS One, 6(12), e26752. Retrieved from http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0026752 doi:10.1371/journal.pone.0026752
Kierkegaard, S. (2010). Twitter thou doeth? Computer Law & Security Review, 26(6), 577-594. doi: 10.1016/j.clsr.2010.09.002
Lindgren, S., & Lundstrom, R. (2011). Pirate culture and hacktivist mobilization: The cultural and social protocols of #WikiLeaks on Twitter. New Media & Society, 13(6), 999-1018. doi: 10.1177/1461444811414833
Williams, S., Terras, M., & Warwick, C. (in press). What people study when they study Twitter: Classifying Twitter related academic papers. Journal of Documentation.