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11 Social Media: Use in Emergency Management Starr Roxanne Hiltz Copyright, 2012.

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Presentation on theme: "11 Social Media: Use in Emergency Management Starr Roxanne Hiltz Copyright, 2012."— Presentation transcript:

1 11 Social Media: Use in Emergency Management Starr Roxanne Hiltz Copyright, 2012

2 22 Studies of EMIS and Social Computing Under the leadership of Leysia Palen, a Crisis Informatics Group at the University of Colorado, Boulder, has been the most prominent in studying the use of social computing systems in emergency response in the U.S. As they point out, citizen-side information generation and dissemination activities are increasingly playing a critical role in disaster preparation, warning response and recovery (Liu et al, 2008). Liu, S.B.; Palen, L.; Sutton, J.; Hughes, A.L.; and Vieweg, S In search of the bigger picture: The emergent role of on-line photo sharing in times of disaster. In Proceedings, 5th International ISCRAM Conference. Washington, DC, F. Fiedrich and B. Van de Walle, eds., pp Available at

3 33 When crises occur, available social media are appropriated for the purpose of collecting and disseminating disaster- relevant information, and new disaster- related content is rapidly created and shared (Sutton, Palen and Shklovski, 2008).

4 44 Photo Sharing Liu et al (2008) described how online photo sharing through Flickr has been used in six notable disasters in the U.S., including Katrina, the Minneapolis Bridge Collapse, the Virginia Tech shooting incident, and the Southern California wildfires of 2007.

5 55 Photo sharing in disasters They describe the creation of shared tagging nomenclatures, to document not only the disaster in progress but also social convergence activities around the disaster. Not only photos are posted, but also other visuals, for instance, a screen shot of a Google map mash up of the locations of the wildfires as they were spreading.

6 66 Twitter: A favorite for Analysis Twitters interface allows users to post short messages (up to 140 characters, referred to as tweets) that can be read by any other Twitter user. One of the most useful of the conventions developed for information filtering and dissemination on Twitter is the hashtag, which takes the form of #[hashtag term], often appended at the end of the tweet. Another useful convention is the which indicates that a tweet is being passed on. Each Twitter account has a profile that contains a chosen name, (home) location, biographical profile and a list for both the followers and the accounts he or she is following. Unless set as private, this information is also available for analysis. The tweets, any hashtags, etc. are available for analysis- many datasets are hundreds of thousand or even millions of of tweets collected that have hashtags relevant to a specific disaster.

7 7 Issues… Validity, Info Overload, privacy/ civil liberties Fear of deliberate or accidental false rumors that may cause panic or wrong public behavior Several recent studies look at ways of measuring this, or filtering for validity Another study describes using remote digital volunteers to filter and summarize relevant Tweets

8 8 Trustworthiness in 2010 Chilean Earthquake Database of 4.7 million tweets; identified 7 cases of confirmed news and 7 false rumors Manually coded each tweet on each of these as : affirms (propagates information confirming the item), denies (refutes )the information item, questions (asks about the information item), and unrelated or unknown. Found that in the case of truths, approximately 95.5% of responding tweets affirmed the information, and only 0.3% denied it. For false rumors, about 50% of replies denied that they were true, and another approximately 6% questioned the veracity The authors conclude that the Twitter community works like a collaborative filter of information. Could lead to automated analyses that mark tweets as questionable through content analysis of replies. –Source: Mendoza, N,M Poblete, B. and Castillo, C. (2010). Twitter Under Crisis: Can we trust what we RT? Proceedings, 1st Workshop on Social Media Analytics (SOMA 10), July 25, 2010, Washington, DC, USA, ACM.

9 9 Automating Assessment of the Credibility of Twitter Messages In a follow up study, text analyzers were built, trained, and tested to first identify trending Twitter topics as news or just chat, and then secondly, to assess the credibility of the tweets. Best predictors of credibility included characteristics of users How long they had been Twitter users (more active users tend to spread more credible information); Number of prior tweets they had written as of the posting time; and the number of followers and friends that they had at the time (the higher, the better; these data can be obtained from online profiles for users). –Source: Castillo, C., Mendoza, M., and Poblete, B., (2011). Information Credibility on Twitter. Proceedings, WWW 2011, Hyderabad, India, pp

10 10 (Overload coping)- Trial by Fire: The Deployment of Trusted Digital Volunteers in the 2011 Shadow Lake Fire Reports on the use of a team of trusted digital volunteers during the 2011 Shadow Lake Fire that occurred in the US Pacific Northwest to extend the social media capacity of an incident management team. Describes the tools and processes used by this virtual team to coordinate their activities, monitor social media communication and to establish communications with the public around the event. St. Dennis, Hughes, Palen, U. of Colorado ISCRAM 2012

11 11 The future- expanding citizen roles in EMIS through social software In creating a bigger role for online citizen participation, we need to be concerned about problematic rumors; privacy protection of information and its source; difficulty of coordination with official civic agencies; and potential failure of Internet access. Information systems designers need to provide structures and features for collecting, validating, and transmitting such citizen-generated information (Palen et al, 2007). Palen, L.; Hiltz, S.R.; and Liu, S Citizen Participation in Emergency Preparedness and Response. Communications of the ACM special issue, 50, 3, Researchers need to summarize the lessons from research, for practitioners

12 12 I wonder if they are twittering?

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