Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach

@inproceedings{Wang2011TopicSA,
  title={Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach},
  author={Xiaolong Wang and Furu Wei and Xiaohua Liu and Ming Zhou and Ming Zhang},
  booktitle={CIKM},
  year={2011}
}
Twitter is one of the biggest platforms where massive instant messages (i.e. tweets) are published every day. Users tend to express their real feelings freely in Twitter, which makes it an ideal source for capturing the opinions towards various interesting topics, such as brands, products or celebrities, etc. Naturally, people may anticipate an approach to receiving the common sentiment tendency towards these topics directly rather than through reading the huge amount of tweets about them. On… CONTINUE READING
Highly Influential
This paper has highly influenced 17 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 278 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 2 times over the past 90 days. VIEW TWEETS
159 Citations
7 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 159 extracted citations

278 Citations

050'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 278 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.

Similar Papers

Loading similar papers…