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Beyond Hashtags: Collecting and Analysing Conversations on Twitter

Paper by Brenda Moon, Nicolas Suzor & Ariadna Matamoros-Fernández presented at the Association of Internet Researchers conference, Berlin, 6 Oct. 2016.

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Beyond Hashtags: Collecting and Analysing Conversations on Twitter

  1. 1. BEYOND HASHTAGS: COLLECTING AND ANALYSING CONVERSATIONS ON TWITTER Brenda Moon, Nicolas Suzor & Ariadna Matamoros-Fernández Digital Media Research Centre Queensland University of Technology
  2. 2. Previous research • Twitter – Keywords/hashtags (Rambukkana, 2015; Bruns & Burgess, 2015) •Network analysis •Content analysis – Approaching completeness (Lorentzen & Nolin, 2015) • We want to catch more of the conversation
  3. 3. Methodology • Rationale – Computational analysis (quantitative) + Ethnography / Visualisation / observation/ description (Qualitative) • What are these extra tweets telling us? – Where is the conversation happening? (reply-chains) – Can we discover new themes? (hashtags) – Can we discover new actors? (@mentions) Are they relevant to the issue/controversy/event we are examining?
  4. 4. Data collection & Uber as a case study Seed tweet in_reply_to tweet_id in_reply_to tweet_id follow reply chain back in time using ‘in_reply_to’ field which contains the tweet_id of the replied to tweet searching for tweet_id in ‘in_reply_to’ field
  5. 5. Timeline of Uber Tweets Case Study: New Year 2015
  6. 6. New Years Eve 2015 - price surge controversy Seed Supplement % of total 1. Tweets 256,682 53,111 17.1 2. Retweets 84,502 142 0.2 3. Tweeting users 70,584 3,379 4.6 4. Replied to users (by to_user_id) 21,113 6,470 23.5 5a. Replies (by to_user_id) 42,143 46,449 52.4 6a. Mentioned users including RTs 57,151 5,396 8.6 6b. Mentioned users excluding RTs 33,667 6,194 15.5 7a. Mentioned users who sent tweets 9,587 5,099 34.7 7b. Mentioned users who didn't send any tweets 47,564 297 0.6 8. Hashtags (unique hashtags) 21,338 1,773 7.7
  7. 7. New Years Eve 2015 - network metrics - mention network Seed Supp % of total contributed by Supplement 1. Nodes 2,276.00 312 12.06 2. Edges 2,527.00 713 22.01 3. Average weighted degree 2.22 0.28 11.31 4. Max in-degree 295 0 0 5. Max out-degree 27 12 30.77 6. Average path length 2.9 2.36 44.89
  8. 8. Reply chains: conversation network nodes: 2,345 extra tweets: 70% seed tweets: 30%
  9. 9. Reply chains: selected chain nodes: 2,345 extra tweets: 70% seed tweets: 30%
  10. 10. Original Tweet: Some of the replies in the reply chain:
  11. 11. @mentions @Bencubby
  12. 12. Hashtags
  13. 13. Preliminary Conclusions • Importance of qualitative observation and exploration to make sense of complex conversations on social media • The method is more useful to identify conversations and understand context rather than discover new themes via hashtags (e.g. central issues vs annotations) • Visualization helps identify points of interest
  14. 14. Future outlook • Additional case studies to identify which types of events reply chain supplementation is useful for. • Identifying ‘key media objects’ (e.g. highly posted images, videos, or arguments) and tracing the conversation specifically around them, rather than our keyword datasets. •Evolution over time - looking at how these conversations evolve and change over time
  15. 15. Thank you :) Brenda Moon @brendam Nicolas Suzor @nicsuzor Ariadna Matamoros-Fernández @andairamf Digital Media Research Centre Queensland University of Technology

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