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Author  |
Cornelia Caragea; Anna Squicciarini; Sam Stehle; Kishore Neppalli; Andrea H. Tapia |
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Title |
Mapping moods: Geo-mapped sentiment analysis during hurricane sandy |
Type |
Conference Article |
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Year |
2014 |
Publication |
ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2014 |
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Volume |
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Issue |
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Pages |
642-651 |
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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) |
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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. |
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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 |
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Publisher |
The Pennsylvania State University |
Place of Publication |
University Park, PA |
Editor |
S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih. |
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Language |
English |
Summary Language |
English |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9780692211946 |
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Track |
Social Media in Crisis Response and Management |
Expedition |
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Conference |
11th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
372 |
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Author |
Hongmin Li; Nicolais Guevara; Nic Herndon; Doina Caragea; Kishore Neppalli; Cornelia Caragea; Anna Squicciarini; Andrea H. Tapia |
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Title |
Twitter Mining for Disaster Response: A Domain Adaptation Approach |
Type |
Conference Article |
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Year |
2015 |
Publication |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2015 |
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Volume |
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Issue |
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Pages |
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Keywords |
Disaster Response; domain adaptation; tweet classification |
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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. |
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Publisher |
University of Agder (UiA) |
Place of Publication |
Kristiansand, Norway |
Editor |
L. Palen; M. Buscher; T. Comes; A. Hughes |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Volume |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9788271177881 |
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Track |
Social Media Studies |
Expedition |
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Conference |
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
yes |
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Call Number |
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Serial |
1234 |
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Author |
Shane Errol Halse; Andrea Tapia; Anna Squicciarini; Cornelia Caragea |
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Title |
Tweet Factors Influencing Trust and Usefulness During Both Man-Made and Natural Disasters |
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Conference Article |
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Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
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Volume |
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Issue |
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Pages |
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Keywords |
Twitter; Sandy; Hurricane; Boston Bombing; Trust; Usefulness |
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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. |
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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 |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3388 |
ISBN |
978-84-608-7984-9 |
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Track |
Social Media Studies |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1403 |
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Author |
Shane Errol Halse; Andrea Tapia; Anna Squicciarini; Cornelia Caragea |
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Title |
An Emotional Step Towards Automated Trust Detection in Crisis Social Media |
Type |
Conference Article |
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Year |
2016 |
Publication |
ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2016 |
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Volume |
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Issue |
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Pages |
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Keywords |
Twitter; Sandy; Hurricane; Boston; Bombing; Trust; Usefulness; Sentiment. Emotion |
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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. |
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Corporate Author |
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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 |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3388 |
ISBN |
978-84-608-7984-9 |
Medium |
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Track |
Emerging Topics |
Expedition |
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Conference |
13th International Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1414 |
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