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A random walk on the red carpet: rating movies with user reviews and pagerank

Published: 26 October 2008 Publication History

Abstract

Although PageRank has been designed to estimate the popularity of Web pages, it is a general algorithm that can be applied to the analysis of other graphs other than one of hypertext documents. In this paper, we explore its application to sentiment analysis and opinion mining: i.e. the ranking of items based on user textual reviews. We first propose various techniques using collocation and pivot words to extract a weighted graph of terms from user reviews and to account for positive and negative opinions. We refer to this graph as the sentiment graph. Using PageRank and a very small set of adjectives (such as 'good', 'excellent', etc.) we rank the different items. We illustrate and evaluate our approach using reviews of box office movies by users of a popular movie review site. The results show that our approach is very effective and that the ranking it computes is comparable to the ranking obtained from the box office figures. The results also show that our approach is able to compute context-dependent ratings.

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cover image ACM Conferences
CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge management
October 2008
1562 pages
ISBN:9781595939913
DOI:10.1145/1458082
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 26 October 2008

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Author Tags

  1. opinion mining
  2. pagerank
  3. ranking

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  • Research-article

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CIKM08
CIKM08: Conference on Information and Knowledge Management
October 26 - 30, 2008
California, Napa Valley, USA

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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  • (2019)Fatten Features and Drop WastesProceedings of the 21st International Conference on Information Integration and Web-based Applications & Services10.1145/3366030.3366133(161-165)Online publication date: 2-Dec-2019
  • (2018)Design and Application of a Multi-Variant Expert System Using Apache Hadoop FrameworkSustainability10.3390/su1011428010:11(4280)Online publication date: 19-Nov-2018
  • (2018)Clustering halal food consumers: A Twitter sentiment analysisInternational Journal of Market Research10.1177/147078531877145161:3(320-337)Online publication date: 24-Apr-2018
  • (2018)A Contextual Random Walk Model for Automated Playlist Generation2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2018.00-66(367-374)Online publication date: Dec-2018
  • (2017)Exploiting Guest Preferences with Aspect-Based Sentiment Analysis for Hotel RecommendationKnowledge Discovery, Knowledge Engineering and Knowledge Management10.1007/978-3-319-52758-1_3(31-46)Online publication date: 22-Jan-2017
  • (2015)Exploiting Guest Preferences with Aspect-based Sentiment Analysis for Hotel RecommendationKnowledge Discovery, Knowledge Engineering and Knowledge Management10.1007/978-3-319-25840-9_3(34-49)Online publication date: 28-Oct-2015
  • (2014)Walking on a User Similarity Network towards Personalized RecommendationsPLoS ONE10.1371/journal.pone.01146629:12(e114662)Online publication date: 9-Dec-2014
  • (2014)Predicting the popularity of web 2.0 items based on user commentsProceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval10.1145/2600428.2609558(233-242)Online publication date: 3-Jul-2014
  • (2014)Modeling and broadening temporal user interest in personalized news recommendationExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.11.02041:7(3168-3177)Online publication date: 1-Jun-2014
  • (2014)A knowledge-based approach for polarity classification in TwitterJournal of the Association for Information Science and Technology10.1002/asi.2298465:2(414-425)Online publication date: 1-Feb-2014
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