Expressing Sentiments in Game Reviews

Anna Secui, Maria-Dorinela Sirbu, Mihai Dascalu, Scott Crossly, Stefan Ruseti, Stefan Trausan-Matu

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

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Opinion mining and sentiment analysis are important research areasof Natural Language Processing (NLP) tools and have become viable alternativesfor automatically extracting the affective information found in texts. Ouraim is to build an NLP model to analyze gamers’ sentiments and opinionsexpressed in a corpus of 9750 game reviews. A Principal Component Analysisusing sentiment analysis features explained 51.2 % of the variance of thereviews and provides an integrated view of the major sentiment and topic relateddimensions expressed in game reviews. A Discriminant Function Analysis basedon the emerging components classified game reviews into positive, neutral andnegative ratings with a 55 % accuracy.
Original languageEnglish
Title of host publicationArtificial Intelligence: Methodology, Systems, and Applications
Subtitle of host publication17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings
EditorsChristo Dichev, Gennady Agre
ISBN (Print)978-3-319-44748-3
Publication statusPublished - 27 Sept 2016
Externally publishedYes
EventInternational Conference on Artificial Intelligence: Methodology, Systems, and Applications: Artificial Intelligence: Methodology, Systems, and Applications - Varna, Bulgaria
Duration: 7 Sept 201610 Sept 2016

Publication series

SeriesLecture Notes in Artificial Intelligence (subseries)


ConferenceInternational Conference on Artificial Intelligence: Methodology, Systems, and Applications
Abbreviated titleAIMSA 2016
Internet address


  • natural language processing
  • sentiment analysis
  • opinion mining
  • lexical analysis


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