Abstract
BACKGROUND
Increasingly, social media spaces are understood by researchers to be a valuable site of everyday politically-relevant discussions. However, qualitative usages of social media data are typically undertaken with existing tools and methods developed for more ‘traditional’ tools and methods (i.e. thematic analysis and content analysis and so on). This, we argue, misses an opportunity to develop new methods which may be more tightly attuned to the idiosyncrasies of such data. Accordingly this paper aims to provide a means of drawing on and working with such idiosyncrasies, demonstrating the value of doing with reference to an empirical case.
OBJECTIVE
Building on previous work looking at how everyday discussions around social welfare issues arise on Twitter around the broadcast of a TV show (Benefits Street) (Brooker et al, 2015), we seek to explore the possibilities arising from capturing an atypical slice of Twitter data (i.e. whole timelines) and treating those data with an atypical analytic approach (i.e. investigating timeline narratives longitudinally). Hence, this paper will dually comment on both the empirical case at hand, and the methods requirements worked out through the course of undertaking this work.
METHODS
We captured timeline data of 2581 Twitter users tweeting using the ‘official’ #BenefitsStreet hashtag during the broadcasts of both series of the programme (January 2014 and May 2015), amounting to 6,260,444 tweets in total. We undertake an exploratory analysis of an arbitrarily selected subset of user timelines within the master dataset, concentrating on the pervasion of welfare discussion throughout these users’ timelines between the two series’ of Benefits Street, as well as drawing out other themes and topics that motivate these tweeters to tweet.
RESULTS
The study elaborates on how socio-political talk on Twitter fits in with tweeters’ everyday talk around a range of different interests and topics. This study also demonstrates the potential for longitudinal analysis of timeline narratives as an innovative qualitative approach to social media data, which can tap into the depth of meaning that such data may hold for those who produce it.
FUTURE WORK
The present study stands as a first exploratory step in the analysis of the full dataset of 6,260,444 tweets, also providing more generalizable methodological grounding on which to base the idea of longitudinal research with social media timeline data. However, the complexity of applying this approach to data of this kind also requires further thought and discussion around the development of scalable computational tools for assisting qualitative researchers in the handling of such large-scale data. The present paper points the way towards solutions for both of these problems.
REFERENCES
Brooker, P., Vines, J., Sutton, S., Barnett, J., Feltwell, T. and Lawson, S. (2015). Debating poverty porn on Twitter: Social media as a place for everyday socio-political talk. CHI ’15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 3177-3186. http://dx.doi.org/10.1145/2702123.2702291
Increasingly, social media spaces are understood by researchers to be a valuable site of everyday politically-relevant discussions. However, qualitative usages of social media data are typically undertaken with existing tools and methods developed for more ‘traditional’ tools and methods (i.e. thematic analysis and content analysis and so on). This, we argue, misses an opportunity to develop new methods which may be more tightly attuned to the idiosyncrasies of such data. Accordingly this paper aims to provide a means of drawing on and working with such idiosyncrasies, demonstrating the value of doing with reference to an empirical case.
OBJECTIVE
Building on previous work looking at how everyday discussions around social welfare issues arise on Twitter around the broadcast of a TV show (Benefits Street) (Brooker et al, 2015), we seek to explore the possibilities arising from capturing an atypical slice of Twitter data (i.e. whole timelines) and treating those data with an atypical analytic approach (i.e. investigating timeline narratives longitudinally). Hence, this paper will dually comment on both the empirical case at hand, and the methods requirements worked out through the course of undertaking this work.
METHODS
We captured timeline data of 2581 Twitter users tweeting using the ‘official’ #BenefitsStreet hashtag during the broadcasts of both series of the programme (January 2014 and May 2015), amounting to 6,260,444 tweets in total. We undertake an exploratory analysis of an arbitrarily selected subset of user timelines within the master dataset, concentrating on the pervasion of welfare discussion throughout these users’ timelines between the two series’ of Benefits Street, as well as drawing out other themes and topics that motivate these tweeters to tweet.
RESULTS
The study elaborates on how socio-political talk on Twitter fits in with tweeters’ everyday talk around a range of different interests and topics. This study also demonstrates the potential for longitudinal analysis of timeline narratives as an innovative qualitative approach to social media data, which can tap into the depth of meaning that such data may hold for those who produce it.
FUTURE WORK
The present study stands as a first exploratory step in the analysis of the full dataset of 6,260,444 tweets, also providing more generalizable methodological grounding on which to base the idea of longitudinal research with social media timeline data. However, the complexity of applying this approach to data of this kind also requires further thought and discussion around the development of scalable computational tools for assisting qualitative researchers in the handling of such large-scale data. The present paper points the way towards solutions for both of these problems.
REFERENCES
Brooker, P., Vines, J., Sutton, S., Barnett, J., Feltwell, T. and Lawson, S. (2015). Debating poverty porn on Twitter: Social media as a place for everyday socio-political talk. CHI ’15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 3177-3186. http://dx.doi.org/10.1145/2702123.2702291
| Original language | English |
|---|---|
| Title of host publication | 2016 International Conference on Social Media & Society |
| Subtitle of host publication | #SMSociety |
| Publication status | Published - 12 Jul 2016 |
| Event | 2016 International Conference on Social Media & Society: #SMSociety - Goldsmiths University of London, London, UK United Kingdom Duration: 11 Jul 2016 → 13 Jul 2016 https://smsociety16.sched.com/ |
Conference
| Conference | 2016 International Conference on Social Media & Society |
|---|---|
| Abbreviated title | SM+S |
| Country/Territory | UK United Kingdom |
| City | London |
| Period | 11/07/16 → 13/07/16 |
| Internet address |