Target-dependent Twitter Sentiment Classification
Microsoft Research Asia (China) · Harbin Institute of Technology
Abstract
Sentiment analysis on Twitter data has attracted much attention recently. In this paper, we focus on target-dependent Twitter sentiment classification; namely, given a query, we classify the sentiments of the tweets as positive, negative or neutral according to whether they contain positive, negative or neutral sentiments about that query. Here the query serves as the target of the sentiments. The state-ofthe-art approaches for solving this problem always adopt the target-independent strategy, which may assign irrelevant sentiments to the given target. Moreover, the state-of-the-art approaches only take the tweet to be classified into consideration when classifying the sentiment; they ignore its context (i.e.,…
Citation impact
- FWCI
- 79.80
- Percentile
- 100%
- References
- 32
Authors
5Topics & keywords
- Sentiment analysis
- Computer science
- Focus (optics)
- Context (archaeology)
- State (computer science)
- Artificial intelligence
- Information retrieval
- Algorithm