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Author (down) Liuqing Li; Edward A. Fox pdf  isbn
openurl 
  Title Understanding patterns and mood changes through tweets about disasters Type Conference Article
  Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019  
  Volume Issue Pages  
  Keywords Disaster, Pattern, User Classification, Mood Detection, Twitter  
  Abstract We analyzed a sample of large tweet collections gathered since 2011, to expand understanding about tweeting

patterns and emotional responses of different types of tweeters regarding disasters. We selected three examples for

each of four disaster types: school shooting, bombing, earthquake, and hurricane. For each collection, we deployed

our novel model TwiRole for user classification, and an existing deep learning model for mood detection. We

found differences in the daily tweet count patterns, between the different types of events. Likewise, there were

different average scores and patterns of moods (fear, sadness, surprise), both between types of events, and between

events of the same type. Further, regarding surprise and fear, there were differences among roles of tweeters. These

results suggest the value of further exploration as well as hypothesis testing with our hundreds of event and trend

related tweet collections, considering indications in those that reflect emotional responses to disasters.
 
  Address Virginia Tech, United States of America  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium  
  Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)  
  Notes Approved no  
  Call Number Serial 1863  
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Author (down) Liuqing Li; Edward A. Fox pdf  isbn
openurl 
  Title Disaster Response Patterns across Different User Groups on Twitter: A Case Study during Hurricane Dorian Type Conference Article
  Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020  
  Volume Issue Pages 838-848  
  Keywords Hurricane, Response, Pattern, User Classification, Twitter  
  Abstract We conducted a case study analysis of disaster response patterns across different user groups during Hurricane Dorian in 2019. We built a tweet collection about the hurricane, covering a two week period. We divided Twitter users into two groups: brand/organization or individual. We found a significant difference in response patterns between the groups. Brand users increasingly participated as the disaster unfolded, and they posted more tweets than individual users on average. Regarding emotions, brand users posted more tweets with joy and surprise, while individual users posted more tweets with sadness. Fear was a common emotion between the two groups. Further, both groups used different types of hashtags and words in their tweets. Some distinct patterns were also discovered in their concerns on specific topics. These results suggest the value of further exploration with more tweet collections, considering the behavior of different user groups during disasters.  
  Address Department of Computer Science, Virginia Tech; Department of Computer Science, Virginia Tech;  
  Corporate Author Thesis  
  Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 978-1-949373-27-74 ISBN 2411-3460 Medium  
  Track Social Media for Disaster Response and Resilie Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management  
  Notes liuqing@vt.edu Approved no  
  Call Number Serial 2275  
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