Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm

@inproceedings{Liu2009ReviewSS,
  title={Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm},
  author={Jingjing Liu and Stephanie Seneff},
  booktitle={EMNLP},
  year={2009}
}
This paper presents a parse-and-paraphrase paradigm to assess the degrees of sentiment for product reviews. Sentiment identification has been well studied; however, most previous work provides binary polarities only (positive and negative), and the polarity of sentiment is simply reversed when a negation is detected. The extraction of lexical features such as unigram/bigram also complicates the sentiment classification task, as linguistic structure such as implicit long-distance dependency is… CONTINUE READING
Highly Cited
This paper has 102 citations. REVIEW CITATIONS

From This Paper

Figures, tables, results, and topics from this paper.

Key Quantitative Results

  • In an application involving extracting aspect-based pros and cons from restaurant reviews, we obtained a 45% relative improvement in recall through the use of parsing methods, while also improving precision.

Citations

Publications citing this paper.
Showing 1-10 of 69 extracted citations

102 Citations

01020'11'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 102 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…