BOUNCE: sentiment classification in Twitter using rich feature sets
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| Conference paper (help) | |
|---|---|
| BOUNCE: sentiment classification in Twitter using rich feature sets | |
| Authors: | Nadin Kökciyan, Arda Celebi†, Arzucan Özgur, Suzan Üskudarlı |
| Citation: | missing booktitle : 2013 |
| Editors: | |
| Publisher: | Define publisher |
| Meeting: | Define meeting |
| Database(s): | Google Scholar cites |
| DOI: | Define doi. |
| Link(s): | http://www.cmpe.boun.edu.tr/~ozgur/papers/bounce.pdf |
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| Web: | DuckDuckGo Bing Google Yahoo! — Google PDF |
| Article: | Google Scholar PubMed |
| Restricted: | DTU Digital Library |
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| Format: | BibTeX |
BOUNCE: sentiment classification in Twitter using rich feature sets reports on a system for sentiment analysis of posts from Twitter for the SemEval competition.
[edit] Method
Features included (see Table 1):
- Single-word features.
- Match to slang dictionary
- Emoticons
- Sentiment analysis using AFINN and SentiWordNet word lists.
- ...
