Volume 9 Number 9 (Sep. 2014)
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JSW 2014 Vol.9(9): 2348-2352 ISSN: 1796-217X
doi: 10.4304/jsw.9.9.2348-2352

Sentiment Visualization on Tweet Stream

Hua Jin1, Yatao Zhu1, 2, Zhiqiang Jin1, Sandhya Arora3
1College of Information Science & Technology, Agricultural University of Hebei, China
2Institute of Computing Technology, Chinese Academy of Sciences, China
3Meghnad Saha Institute of Technology, Kolkata, India


Abstract—Sentiment visualization on tweet topics has recently gained attentions due to its ability to efficiently analyze and understand the people’s feelings for individuals and companies. In this paper, we propose a chart, SentimentRiver, which effectively demonstrates the dynamics of sentiment evolvement on a topic of tweets. The gradient colors of the river flow indicate the variation of topical sentiments, via introducing the membership weight to a sentiment class in a fuzzy mathematical view. Besides, with the value of the point-wise mutual information and information retrieval (PMI-IR), representative sentiment words are extracted and labeled in each time slot of the river flow. In the experiments, we compare SentimentRiver on the topic of Obama election, with other statistic charts, which demonstrates its effectiveness for visualizing and analyzing the topical sentiments on tweet stream.

Index Terms—Sentiment visualization, PMI-IR, WEKA, SentimentRiver

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Cite: Hua Jin, Yatao Zhu, Zhiqiang Jin, Sandhya Arora, "Sentiment Visualization on Tweet Stream," Journal of Software vol. 9, no. 9, pp. 2348-2352, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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