An emotional step toward automated trust detection in crisis social media

References

• Adler, B. T., & de Alfaro, L. (2007). A content-driven reputation system for the Wikipedia. In Proceedings of the 16th international conference on World Wide Web (WWW) (pp. 261–270). New York, NY: ACM Press.
   Google Scholar
• Castillo, C., Mendoza, M., & Poblete, B. (2011). Information credibility on Twitter. WWW ‘11 Proceedings of the 20th international conference on World Wide Web (pp. 675–684). ACM. doi: 10.1145/1963405.1963500
   Google Scholar
• Cheong, M., & Lee, V. C. S. (2011). A microblogging-based approach to terrorism informatics: Exploration and chronicling civilian sentiment and response to terrorism events via Twitter. Information Systems Frontiers, 13(1), 45–59. doi: 10.1007/s10796-010-9273-x
   Web of Science ®Google Scholar
• Croissant, Y. (2013). mlogit: Multinomial logit model. R package version 0.2-4. Retrieved from http://CRAN.R-project.org/package = mlogit
   Google Scholar
• Dailey, D., & Starbird, K. (2014, May). Visible skepticism: Community vetting after Hurricane Irene. In Proceedings of the 11th international ISCRAM conference – University Park, Pennsylvania, USA, (pp. 777–781).
   Google Scholar
• Denef, S., Bayerl, P. S., & Kaptein, N. (2013). Social media and the police – Tweeting practices of British Police forces during the August 2011 Riots. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems (CHI13), Paris, France, May 2013.
   Google Scholar
• Diakopoulos, N. a., & Shamma, D. a. (2010). Characterizing debate performance via aggregated twitter sentiment. CHI ‘10: Proceedings of the SIGCHI conference on Human Factors in Computing Systems, (p.1195). doi: 10.1145/1753326.1753504
   Google Scholar
• Drake, B. (2013). Twitter served as a lifeline of information during Hurricane Sandy. Retrieved from http://www.pewresearch.org/fact-tank/2013/10/28/twitter-served-as-a-lifeline-of-information-during-hurricane-sandy/
   Google Scholar
• Dunn, J. R., & Schweitzer, M. E. (2005). Feeling and believing: The influence of emotion on trust. Journal of Personality and Social Psychology, 88(5), 736–748. doi: 10.1037/0022-3514.88.5.736
   PubMed Web of Science ®Google Scholar
• Edwards, J. (2016). Leaked Twitter API data shows the number of tweets is in serious decline. Retrieved from http://www.businessinsider.com/tweets-on-twitter-is-in-serious-decline-2016-2?r = UK&IR = T
   Google Scholar
• Field, C. A. P. (2007). Analysis of Variance (ANOVA). In N. J. Salkind & K. Rasmussen (Eds.). Thousand Oaks, CA: Sage. doi: 10.4135/9781412952644.n19
   Google Scholar
• Galland, A., Abiteboul, S., Marian, A., & Senellart, P. (2010). Corroborating information from disagreeing views. WSDM, 131–140. Retrieved from http://portal.acm.org/citation.cfm?id = 1718504
   Google Scholar
• Giacobe, N. A., Kim, H.-W., & Faraz, A. (2010). Mining social media in extreme events : Lessons learned from the DARPA network challenge. In 2010 IEEE International Conference on Technologies for Homeland Security (HST) (pp. 165–171). Waltham, MA: IEEE. doi: 10.1109/THS.2010.5655067
   Google Scholar
• Grabner-Kräuter, S., Kaluscha, E. A., & Fladnitzer, M. (2006). Perspectives of online trust and similar constructs. In Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: Innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet – ICEC ‘06 (p. 235). New York, USA: ACM Press. doi: 10.1145/1151454.1151496
   Google Scholar
• Gupta, A., Kumaraguru, P., Castillo, C., & Meier, P. (2014). TweetCred: Real-Time credibility assessment of content on Twitter. Social Informatics Lecture Notes in Computer Science, 8851, 228–243. doi: 10.1007/978-3-319-13734-6_16
   Google Scholar
• Gupta, A., Lamba, H., Kumaraguru, P., & Joshi, A. (2013). Faking Sandy: Characterizing and identifying fake images on Twitter during Hurricane Sandy. In Proceedings of the 22nd international conference on World Wide Web companion (WWW ‘13 Companion) (pp. 729–736). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland.
   Google Scholar
• Hughes, A. L., & Palen, L. (2009). Twitter adoption and use in mass convergence and emergency events. International Journal of Emergency Management, 6(3/4), 248–260. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/summary?doi = 10.1.1.156.8385 doi: 10.1504/IJEM.2009.031564
   Google Scholar
• Hughes, A. L., & Palen, L. (2012). The evolving role of the public information officer: An examination of social media in emergency management. Journal of Homeland Security and Emergency Management, 9(1). Retrieved from http://www.degruyter.com/view/j/jhsem.2012.9.issue-1/1547-7355.1976/1547-7355.1976.xml doi: 10.1515/1547-7355.1976
   Web of Science ®Google Scholar
• Hyun, W., & Ditton, R. (2006). Using multinomial logistic regression analysis to understand anglers willingness to substitute other fishing locations. In R. Burns & K. Robinson (Eds.), Proceedings of the 2006 Northeastern Recreation Research Symposium (pp. 248–255). Retrieved from http://www.nrs.fs.fed.us/pubs/gtr/gtr_nrs-P-14.pdf#page = 257
   Google Scholar
• Jung, J., & Moro, M. (2014). Multi-level functionality of social media in the aftermath of the Great East Japan Earthquake. Disasters, 38(March 2011), 123–143. doi: 10.1111/disa.12071
   Web of Science ®Google Scholar
• Latonero, M., & Shklovski, I. (2011). Emergency management, Twitter, and social media evangelism. InternationalJournal of Information Systems for Crisis Response and Management, 3(4), 1–16. doi: 10.4018/jiscrm.2011100101
   Google Scholar
• McClendon, S., & Robinson, A. C. (2012). Leveraging geospatially-oriented social media communications in disaster response. Iscram, (April), 2–11. doi: 10.4018/jiscrm.2013010102
   Google Scholar
• Mccormick, S. (2016). New tools for emergency managers : An assessment of obstacles to use and implementation. Disasters, 40(2), 207–225. doi: 10.1111/disa.12141
   PubMed Web of Science ®Google Scholar
• Mendoza, M., Poblete, B., & Castillo, C. (2010). Twitter under crisis: Can we trust what we RT? Workshop on Social Media Analytics (p. 9). doi: 10.1145/1964858.1964869
   Google Scholar
• Munro, R. (2011, June). Subword and spatiotemporal models for identifying actionable information in Haitian Kreyol. In Proceedings of the fifteenth conference on computational natural language learning (pp. 68–77). Stroudsburg, PA: Association for Computational Linguistics.
   Google Scholar
• Myers, D., & Tingley, D. (2011). The influence of emotion on trust. Cambridge, MA: Harvard University. Retrieved from http://scholar.harvard.edu/files/dtingley/files/emotionmanipulationm11.pdf?m = 1360041342
   Google Scholar
• Qu, Y., Huang, C., Zhang, P., & Zhang, J. (2011). Microblogging after a major disaster in China: A case study of the 2010 Yushu earthquake. CSCW '11 Proceedings of the ACM 2011 conference on Computer supported cooperative work (pp. 25–34). doi: 10.1145/1958824.1958830
   Google Scholar
• Roberts, K., Roach, M. A., Johnson, J., Guthrie, J., & Harabagiu, S. M. (2012). EmpaTweet: Annotating and detecting emotions on Twitter. In Proceedings of the eight international conference on language resources and evaluation (LREC’12) (pp. 3806–3813). Retrieved from http://www.lrec-conf.org/proceedings/lrec2012/pdf/201_Paper.pdf
   Google Scholar
• Sakaki, T., Okazaki, M., & Matsuo, Y. (2010). Earthquake shakes Twitter users: Real-time event detection by social sensors. WWW 2010, April 26–30 (pp. 851–860). Raleigh, NC: ACM.
   Google Scholar
• Shen, Y., Li, S., Zheng, L., Ren, X., & Cheng, X. (2009). Emotion mining research on micro-blog. In 2009 1st IEEE symposium on web society (pp. 71–75). IEEE. Retrieved from http://ieeexplore.ieee.org/document/5271711/
   Google Scholar
• Shklovski, I., Palen, L., & Sutton, J. (2008). Finding community through information and communication technology in disaster response. Proceedings of the 2008 ACM conference on Computer Supported Cooperative Work. ACM (pp.127–136). doi: 10.1145/1460563.1460584
   Google Scholar
• St. Denis, L. A., Hughes, A. L., & Palen, L. (2012). Trial by fire: The deployment of trusted digital volunteers in the 2011 shadow lake fire. In L. Rothkrantz, J. Ristvej, & Z. Franco (Eds.), 9th International ISCRAM conference (pp. 1–10). Retrieved from https://www.nifc.gov/PIO_bb/sm/TrustedDigitalVolStDHPalen.pdf
   Google Scholar
• Starbird, K., & Palen, L. (2013). Working & sustaining the virtual ‘disaster desk. In Proceedings of the 2013 conference on Computer Supported Cooperative Work (CSCW 2013), (pp. 491–502). New York, NY: ACM Press.
   Google Scholar
• Starbird, K., Palen, L., Hughes, A. L., & Vieweg, S. (2010). Chatter on the red: What hazards threat reveals about the social life of microblogged information. In Proceedings of the 2010 ACM conference on Computer supported cooperative work – CSCW ‘10 (pp. 241–250). New York: ACM Press. doi: 10.1145/1718918.1718965
   Google Scholar
• Stephenson, M. J. (2005). Making humanitarian relief networks more effective: Operational coordination, trust and sense making. Disasters, 29(4), 337–350. doi: 10.1111/j.0361-3666.2005.00296.x
   PubMed Web of Science ®Google Scholar
• Stokes, C., & Senkbeil, J. C. (2016). Facebook and Twitter, communication and shelter, and the 2011 Tuscaloosa tornado. Disasters, 41(1), 194–208. doi: 10.1111/disa.12192
   PubMed Web of Science ®Google Scholar
• Sutton, J. N., Emma, S., Sean, F., Britta, J., Ben, G., & Butts, C. T. (2014). Online message amplification in the Boston bombing response. In Proceedings of the Information Systems for Crisis Response and Management conference (ISCRAM 20014). Retrieved from http://iscram2014.org/sites/default/files/misc/proceedings/p15.pdf
   Google Scholar
• Tapia, A. H., Bajpai, K., Jansen, J., Yen, J., & Giles, L. (2011). Seeking the trustworthy tweet: Can Microblogged data fit the information needs of disaster response and humanitarian relief organizations. Proceedings of the 8th international ISCRAM conference, May 1–10. Retrieved from http://irevolution.files.wordpress.com/2011/06/tapia-seeking_the_trustworthy_tweet-161_a.pdf
   Google Scholar
• Tapia, A. H., Moore, K. a., & Johnson, N. (2013, May). Beyond the trustworthy tweet: A deeper understanding of microblogged data use by disaster response and humanitarian relief organizations. Proceedings of the 10th international ISCRAM conference (pp. 770–779). Retrieved from http://star-tides.net/sites/default/files/documents/files/Beyond the Trustworthy Tweet - A Deeper Understanding of Microblogged Data Use by Disaster Response and Humanitarian Relief Organizations.pdf
   Google Scholar
• Vieweg, S. (2010). Microblogged contributions to the emergency arena: Discovery, interpretation and implications. CSCW, February 6–10 (pp. 515–516). Savanah, GA: ACM. Retrieved from http://www.citeulike.org/user/ChaTo/article/6761693
   Google Scholar
• Vieweg, S., Hughes, A. L., Starbird, K., & Palen, L. (2010). Microblogging during two natural hazards events. Proceedings of the 28th International conference on Human Factors in Computing Systems – CHI ‘10, 1079. doi: 10.1145/1753326.1753486
   Google Scholar
• Yin, X., Han, J., & Yu, P. S.-L. (2007). Truth discovery with multiple conflicting information providers on the web. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining KDD 07, (pp. 1048–1052). New York, NY: ACM Press. doi: 10.1145/1281192.1281309
   Google Scholar
• Yin, X., & Tan, W. (2011). Semi-supervised truth discovery. Proceedings of the 20th international conference on World Wide Web – WWW ‘11 (p. 217). New York, NY: ACM Press. doi: 10.1145/1963405.1963439
   Google Scholar
• Zhang, L., Jia, Y., Zhou, B., & Han, Y. (2012). Microblogging sentiment analysis using emotional vector. In 2012 Second international conference on cloud and green computing (pp. 430–433). doi: 10.1109/CGC.2012.29
   Google Scholar