| Records |
Author  |
Ahmed Nagy; Jeannie Stamberger |
| Title |
Crowd sentiment detection during disasters and crises |
Type |
Conference Article |
| Year |
2012 |
Publication |
ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2012 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Bayesian networks; Emergency services; Information systems; Risk management; Social networking (online); Crisis management; Disaster response; Emergency management; Short message; Twitter; Disasters |
| Abstract |
Microblogs are an opportunity for scavenging critical information such as sentiments. This information can be used to detect rapidly the sentiment of the crowd towards crises or disasters. It can be used as an effective tool to inform humanitarian efforts, and improve the ways in which informative messages are crafted for the crowd regarding an event. Unique characteristics of microblogs (lack of context, use of jargon etc) in Tweets expressed by a message-sharing social network during a disaster response require special handling to identify sentiment. We present a systematic evaluation of approaches to accurately and precisely identify sentiment in these Tweets. This paper describes sentiment detection expressed in 3698 Tweets, collected during the September 2010, San Bruno, California gas explosion and resulting fires. The data collected was manually coded to benchmark our techniques. We start by using a library of words with annotated sentiment, SentiWordNet 3.0, to detect the basic sentiment of each Tweet. We complemented that technique by adding a comprehensive list of emoticons, a sentiment based dictionary and a list of out-of-vocabulary words that are popular in brief, online text communications such as lol, wow, etc. Our technique performed 27% better than Bayesian Networks alone, and the combination of Bayesian networks with annotated lists provided marginal improvements in sentiment detection than various combinations of lists. © 2012 ISCRAM. |
| Address |
Carnegie Mellon Silicon Valley, IMT Lucca Institute of Advanced Studies, United States; Disaster Management Initiative, Carnegie Mellon Silicon Valley, United States |
| Corporate Author |
|
Thesis |
|
| Publisher |
Simon Fraser University |
Place of Publication |
Vancouver, BC |
Editor |
L. Rothkrantz, J. Ristvej, Z.Franco |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
9780864913326 |
Medium |
|
| Track |
Social Media and Collaborative Systems |
Expedition |
|
Conference |
9th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
173 |
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| |
| Author |
Kate Starbird; Jeannie Stamberger |
| Title |
Tweak the tweet: Leveraging microblogging proliferation with a prescriptive syntax to support citizen reporting |
Type |
Conference Article |
| Year |
2010 |
Publication |
ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings |
Abbreviated Journal |
ISCRAM 2010 |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Disasters; Hazards; Information systems; Social networking (online); Syntactics; Collective intelligences; Crisis informatics; Emergency; Information convergence; Information diffusion; Microblogging; Technology diffusion; Electric grounding |
| Abstract |
In this paper, we propose a low-tech solution for use by microbloggers that could enhance their ability to rapidly produce parsable, crisis-relevant information in mass emergencies. We build upon existing research on the use of social media during mass emergencies and disasters. Our proposed intervention aims to leverage the affordances of mobile microblogging and the drive to support citizen reporting within current behavioral Twitter-based microblogging practice. We introduce a prescriptive, tweet-based syntax that could increase the utility of information generated during emergencies by gently reshaping current behavioral practice. This offering is grounded in an understanding of current trends in norm evolution of Twitter use, an evolution that has progressed quickly but appears to be stabilizing around specific textual conventions. |
| Address |
ConnectivIT Lab, ATLAS, University of Colorado, Boulder, United States; Disaster Management Initiative, Carnegie Mellon Silicon Valley, United States |
| Corporate Author |
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Thesis |
|
| Publisher |
Information Systems for Crisis Response and Management, ISCRAM |
Place of Publication |
Seattle, WA |
Editor |
S. French, B. Tomaszewski, C. Zobel |
| Language |
English |
Summary Language |
English |
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
2411-3387 |
ISBN |
|
Medium |
|
| Track |
Collaboration and Social Networking |
Expedition |
|
Conference |
7th International ISCRAM Conference on Information Systems for Crisis Response and Management |
| Notes |
|
Approved |
no |
| Call Number |
|
Serial |
971 |
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