Movie review mining and summarization

@inproceedings{Zhuang2006MovieRM,
  title={Movie review mining and summarization},
  author={Li Zhuang and Feng Jing and Xiaoyan Zhu},
  booktitle={CIKM '06},
  year={2006}
}
With the flourish of the Web, online review is becoming a more and more useful and important information resource for people. As a result, automatic review mining and summarization has become a hot research topic recently. Different from traditional text summarization, review mining and summarization aims at extracting the features on which the reviewers express their opinions and determining whether the opinions are positive or negative. In this paper, we focus on a specific domain - movie… Expand
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References

SHOWING 1-10 OF 23 REFERENCES
Movie Review Mining: a Comparison between Supervised and Unsupervised Classification Approaches
TLDR
The results show that the results are comparable to or even better than previous findings, and it is found that movie review mining is a more challenging application than many other types of review mining. Expand
Mining and summarizing customer reviews
TLDR
This research aims to mine and to summarize all the customer reviews of a product, and proposes several novel techniques to perform these tasks. Expand
Extracting Product Features and Opinions from Reviews
TLDR
Opine is introduced, an unsupervised information-extraction system which mines reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across products. Expand
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
TLDR
This work develops a method for automatically distinguishing between positive and negative reviews and draws on information retrieval techniques for feature extraction and scoring, and the results for various metrics and heuristics vary depending on the testing situation. Expand
Sentiment Analysis using Support Vector Machines with Diverse Information Sources
This paper introduces an approach to sentiment analysis which uses support vector machines (SVMs) to bring together diverse sources of potentially pertinent information, including severalExpand
An exploration of sentiment summarization
TLDR
The idea of a sentiment summary, a single passage from a document that captures an author’ s opinion about his or her subject, is introduced and features that appear to be helpful in locating a good summary sentence are examined. Expand
Pulse: Mining Customer Opinions from Free Text
TLDR
A simple but effective technique for clustering sentences, the application of a bootstrapping approach to sentiment classification, and a novel user-interface are described that enables the exploration of large quantities of customer free text. Expand
A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
TLDR
A novel machine-learning method is proposed that applies text-categorization techniques to just the subjective portions of the document, which greatly facilitates incorporation of cross-sentence contextual constraints. Expand
Thumbs up? Sentiment Classification using Machine Learning Techniques
TLDR
This work considers the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative, and concludes by examining factors that make the sentiment classification problem more challenging. Expand
Opinion observer: analyzing and comparing opinions on the Web
TLDR
A novel framework for analyzing and comparing consumer opinions of competing products is proposed, and a new technique based on language pattern mining is proposed to extract product features from Pros and Cons in a particular type of reviews. Expand
...
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