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

Derry Tanti Wijaya, Stéphane Bressan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

28 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM'08
Number of pages9
Publication statusPublished - 2008
Externally publishedYes
EventACM International Conference on Information and Knowledge Management 2008 - Napa Valley, United States of America
Duration: 26 Oct 200830 Oct 2008
Conference number: 17th


ConferenceACM International Conference on Information and Knowledge Management 2008
Abbreviated titleCIKM 2008
Country/TerritoryUnited States of America
CityNapa Valley
Internet address


  • Opinion mining
  • Pagerank
  • Ranking

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