The Genesis of Crisis Communication: from Witnesses to Gatewatchers

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During crisis events individuals look for information and try to share useful content or testify their own experience through social media sites. The research for valuable information is, usually, largely based on information provided - through social media as well as through more traditional media - by news agencies and official actors. This collective behavior leads, on a given amount of time, toward the emergence of gatewatching activities where digital media are usually used to reshare and to control information. But how does this phenomenon emerge? This paper will investigate this specific topic looking at the Twitter conversations produced during the first five hours after the earthquake that struck Emilia Romagna region in Italy on May 20th 2012.
By focusing on the first 5 hours of the Twitter stream we have been able to detect the early user-led phase of the phenomenon, showing which type of users has been the first to fill the information gap and, by then, what happened until the early morning when traditional media came on stage. The research has been based both on the a textual qualitative analysis of the tweets, aimed at investigating what kind of messages were produced and by what kind of users, and on a Social Network Analysis of the #terremoto hashtag that showed how user-produced communication results in different network structures than news agencies’ produced ones.

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The Genesis of Crisis Communication: from Witnesses to Gatewatchers

  1. 1. IR14: Resistance and Appropriation The genesis of Crisis Communication in Twitter: from Witnesses to Gatewatchers Luca Rossi, IT University of Copenhagen Elisabetta Zurovac, University of Urbino Carlo Bo Giovanni Boccia Artieri, University of Urbino Carlo Bo
  2. 2. Background and open research questions
  3. 3. RQ: How is Twitter used during the outbreak of a natural disaster?
  4. 4. Dataset & data acquisition Dataset: #terremoto hashtag May 20th from 4:00 am to 9:00 am 24121 tweets Data acquisition: YourTwapperkeeper
  5. 5. Data description Tweets: 24121 Unique users: 11219 Retweets: 13252 Reply messages: 1819 Link to external resources: 8067
  6. 6. What kind of activity? Ratio between RT and tweet increases form 0,45 during the first hour to 0,55 in the fifth hour.
  7. 7. Temporal perspective
  8. 8. The genesis of the gatewatchers
  9. 9. Textual analysis Coded Tweets 21937 Tweets Tell: tweets with narrative content tied to personal experience and thoughts; Information: tweets with different level of informative content; Ask: tweets containing requests for information; Tweet Consciousness, tweets with meta-comments on Twitter and its functions o usages; Explainations: tweets containing theories, hypothesis on the earthquake; Ironic, tweets making use of irony; Complaints, tweets complaining about the institutions and mainstream media.
  10. 10. Textual analysis Coded Tweets 21937 Tweets Tell: tweets with narrative content tied to personal experience and thoughts; Information: tweets with different level of informative content; Ask: tweets containing requests for information; Tweet Consciousness, tweets with meta-comments on Twitter and its functions o usages; Explainations: tweets containing theories, hypothesis on the earthquake; Ironic, tweets making use of irony; Complaints, tweets complaining about the institutions and mainstream media.
  11. 11. Textual analysis Coded Tweets 21937 Tweets Tell: tweets with narrative content tied to personal experience and thoughts; Information: tweets with different level of informative content; Ask: tweets containing requests for information; Tweet Consciousness, tweets with meta-comments on Twitter and its functions o usages; Assumptions: tweets containing theories, hypothesis on the earthquake; Ironic, tweets making use of irony; Complaints, tweets complaining about the institutions and mainstream media.
  12. 12. 41% 28% 23% 14% 3% 0% 1% 3% 4% 5% 9% 5% 4% 0% 3% 7% 8% 6% 2% 07:00 - 08:00 2% 73% 12% 56% 06:00 - 07:00 4% 11% 05:00 - 06:00 04:00 - 05:00 Textual analysis 54% 20% 1%
  13. 13. Textual analysis 80% 70% 1 2 3 4 5 60% 50% 40% 30% 20% 10% 0% prima ora seconda ora TELL terza ora INFORMATION quarta ora ASK COMPLAINTS quinta ora
  14. 14. Users analysis
  15. 15. Users analysis Degree Centrality Betweenness Centrality
  16. 16. Thank you http://www.snsitalia.it Luca Rossi – lucr@itu.dk Elisabetta Zurovac – elisabetta.zurovac@uniurb.it Giovanni Boccia Artieri – giovanni.bocciaartieri@uniurb.it

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