Sentiment analysis on tweets for social events

Zhou, Xujuan and Tao, Xiaohui and Yong, Jianming and Yang, Zhenyu (2013) Sentiment analysis on tweets for social events. In: IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2013), 27-29 Jun 2013, Whistler, BC. Canada.

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Abstract

Sentiment analysis or opinion mining is an important type of text analysis that aims to support decision making by extracting and analyzing opinion oriented text, identifying positive and negative opinions, and measuring how positively or negatively an entity (i.e., people, organization, event, location, product, topic, etc.) is regarded. As more and more users express their political and religious views on Twitter, tweets become valuable sources of people's opinions. Tweets data can be efficiently used to infer people's opinions for marketing or social studies. This paper proposes a Tweets Sentiment Analysis Model (TSAM) that can spot the societal interest and general people's opinions in regard to a social event. In this paper, Australian federal election 2010 event was taken as an example for sentiment analysis experiments. We are primarily interested in the sentiment of the specific political candidates, i.e., two primary minister candidates - Julia Gillard and Tony Abbot. Our experimental results demonstrate the effectiveness of the system.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2013 IEEE. Published version deposited in accordance with the copyright policy of the publisher.
Faculty / Department / School: Historic - Faculty of Business and Law - School of Information Systems
Date Deposited: 01 Oct 2013 02:42
Last Modified: 13 Jan 2017 04:21
Uncontrolled Keywords: sentiment analysis; social network; text analysis; tweets
Fields of Research : 16 Studies in Human Society > 1608 Sociology > 160808 Sociology and Social Studies of Science and Technology
10 Technology > 1005 Communications Technologies > 100503 Computer Communications Networks
17 Psychology and Cognitive Sciences > 1701 Psychology > 170113 Social and Community Psychology
Socio-Economic Objective: C Society > 95 Cultural Understanding > 9502 Communication > 950205 Visual Communication
Identification Number or DOI: 10.1109/CSCWD.2013.6581022
URI: http://eprints.usq.edu.au/id/eprint/24099

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