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Author (up) Cornelia Caragea; Anna Squicciarini; Sam Stehle; Kishore Neppalli; Andrea H. Tapia pdf  isbn
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  Title Mapping moods: Geo-mapped sentiment analysis during hurricane sandy Type Conference Article
  Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014  
  Volume Issue Pages 642-651  
  Keywords Data mining; Disasters; Hurricanes; Information systems; Disaster-related geo-tagged tweets; Online reviews; Online social networkings; Sentiment analysis; Sentiment classification; Social networking sites; Social networking (online)  
  Abstract Sentiment analysis has been widely researched in the domain of online review sites with the aim of generating summarized opinions of product users about different aspects of the products. However, there has been little work focusing on identifying the polarity of sentiments expressed by users during disaster events. Identifying sentiments expressed by users in an online social networking site can help understand the dynamics of the network, e.g., the main users' concerns, panics, and the emotional impacts of interactions among members. Data produced through social networking sites is seen as ubiquitous, rapid and accessible, and it is believed to empower average citizens to become more situationally aware during disasters and coordinate to help themselves. In this work, we perform sentiment classification of user posts in Twitter during the Hurricane Sandy and visualize these sentiments on a geographical map centered around the hurricane. We show how users' sentiments change according not only to users' locations, but also based on the distance from the disaster.  
  Address Computer Science and Engineering, University of North Texas, Denton, TX-76203, United States; Information Sciences and Technology, Pennsylvania State University, University Park, PA-16801, United States  
  Corporate Author Thesis  
  Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9780692211946 Medium  
  Track Social Media in Crisis Response and Management Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 372  
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Author (up) Hongmin Li; Nicolais Guevara; Nic Herndon; Doina Caragea; Kishore Neppalli; Cornelia Caragea; Anna Squicciarini; Andrea H. Tapia pdf  isbn
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  Title Twitter Mining for Disaster Response: A Domain Adaptation Approach Type Conference Article
  Year 2015 Publication ISCRAM 2015 Conference Proceedings 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015  
  Volume Issue Pages  
  Keywords Disaster Response; domain adaptation; tweet classification  
  Abstract Microblogging data such as Twitter data contains valuable information that has the potential to help improve the speed, quality, and efficiency of disaster response. Machine learning can help with this by prioritizing the tweets with respect to various classification criteria. However, supervised learning algorithms require labeled data to learn accurate classifiers. Unfortunately, for a new disaster, labeled tweets are not easily available, while they are usually available for previous disasters. Furthermore, unlabeled tweets from the current disaster are accumulating fast. We study the usefulness of labeled data from a prior source disaster, together with unlabeled data from the current target disaster to learn domain adaptation classifiers for the target. Experimental results suggest that, for some tasks, source data itself can be useful for classifying target data. However, for tasks specific to a particular disaster, domain adaptation approaches that use target unlabeled data in addition to source labeled data are superior.  
  Address  
  Corporate Author Thesis  
  Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 9788271177881 Medium  
  Track Social Media Studies Expedition Conference ISCRAM 2015 Conference Proceedings 12th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved yes  
  Call Number Serial 1234  
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Author (up) Shane Errol Halse; Andrea Tapia; Anna Squicciarini; Cornelia Caragea pdf  isbn
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  Title Tweet Factors Influencing Trust and Usefulness During Both Man-Made and Natural Disasters Type Conference Article
  Year 2016 Publication ISCRAM 2016 Conference Proceedings 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016  
  Volume Issue Pages  
  Keywords Twitter; Sandy; Hurricane; Boston Bombing; Trust; Usefulness  
  Abstract To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the usefulness of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, in this paper, we characterize tweets, which are perceived useful or trustworthy, and determine their main features. Our analysis is carried out on two datasets (one natural and one man made) gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a high correlation and similar factors (support for the victims, informational data, use of humor and type of emotion used) influencing trustworthiness and usefulness for both disaster types. This could have impacts on how messages from social media data are analyzed for use in crisis response.  
  Address  
  Corporate Author Thesis  
  Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3388 ISBN 978-84-608-7984-9 Medium  
  Track Social Media Studies Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1403  
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Author (up) Shane Errol Halse; Andrea Tapia; Anna Squicciarini; Cornelia Caragea pdf  isbn
openurl 
  Title An Emotional Step Towards Automated Trust Detection in Crisis Social Media Type Conference Article
  Year 2016 Publication ISCRAM 2016 Conference Proceedings 13th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2016  
  Volume Issue Pages  
  Keywords Twitter; Sandy; Hurricane; Boston; Bombing; Trust; Usefulness; Sentiment. Emotion  
  Abstract To this date, research on crisis informatics has focused on the detection of trust in Twitter data through the use of message structure, sentiment, propagation and author. Little research has examined the effects of perceived emotion of these messages in the crisis response domain. Toward detecting useful messages in case of crisis, we examine perceived emotions of these messages and how the different emotions affect the perceived usefulness and trustworthiness. Our analysis is carried out on two datasets gathered from Twitter concerning hurricane Sandy in 2012 and the Boston Bombing 2013. The results indicate that there is a significant difference in the perceived emotions that contribute towards the perceived trustworthiness and usefulness. This could have impacts on how messages from social media data are analyzed for use in crisis response.  
  Address  
  Corporate Author Thesis  
  Publisher Federal University of Rio de Janeiro Place of Publication Rio de Janeiro, Brasil Editor A. Tapia; P. Antunes; V.A. Bañuls; K. Moore; J. Porto  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3388 ISBN 978-84-608-7984-9 Medium  
  Track Emerging Topics Expedition Conference 13th International Conference on Information Systems for Crisis Response and Management  
  Notes Approved no  
  Call Number Serial 1414  
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