Expressing Sentiments in Game Reviews

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

doi:10.1007/978-3-319-44748-3_35

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 proceeding › Conference Article in proceeding › Academic › peer-review

65 Downloads (Pure)

Abstract

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 language	English
Title of host publication	Artificial Intelligence: Methodology, Systems, and Applications
Subtitle of host publication	17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings
Editors	Christo Dichev, Gennady Agre
Publisher	Springer
Pages	352-355
ISBN (Print)	978-3-319-44748-3
DOIs	https://doi.org/10.1007/978-3-319-44748-3_35
Publication status	Published - 27 Sept 2016
Externally published	Yes
Event	International Conference on Artificial Intelligence: Methodology, Systems, and Applications: Artificial Intelligence: Methodology, Systems, and Applications - Varna, Bulgaria Duration: 7 Sept 2016 → 10 Sept 2016 https://link.springer.com/book/10.1007/978-3-319-44748-3 https://www.springer.com/la/book/9783319447476

Publication series

Series	Lecture Notes in Artificial Intelligence (subseries)
Volume	9883

Conference

Conference	International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Abbreviated title	AIMSA 2016
Country/Territory	Bulgaria
City	Varna
Period	7/09/16 → 10/09/16
Internet address	https://link.springer.com/book/10.1007/978-3-319-44748-3 https://www.springer.com/la/book/9783319447476

Keywords

natural language processing
sentiment analysis
opinion mining
lexical analysis

Access to Document

10.1007/978-3-319-44748-3_35

secui2016Accepted author manuscript, 81.6 KBLicence: CC BY-NC-ND

Rage: Realising an Applied Gaming Eco-system
Westera, W. (PI), Georgiadis, K. (CoI), Saveski, G. (CoI), van Lankveld, G. (CoI), Bahreini, K. (CoI), van der Vegt, W. (CoI), Berkhout, J. (CoI), Nyamsuren, E. (CoI), Kluijfhout, E. (CoI) & Nadolski, R. (CoI)
European Union
1/02/15 → 31/07/19
Project: Research

Cite this

Secui, A., Sirbu, M.-D., Dascalu, M., Crossly, S., Ruseti, S., & Trausan-Matu, S. (2016). Expressing Sentiments in Game Reviews. In C. Dichev, & G. Agre (Eds.), Artificial Intelligence: Methodology, Systems, and Applications: 17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings (pp. 352-355). Springer. https://doi.org/10.1007/978-3-319-44748-3_35

Secui, Anna ; Sirbu, Maria-Dorinela ; Dascalu, Mihai et al. / Expressing Sentiments in Game Reviews. Artificial Intelligence: Methodology, Systems, and Applications: 17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings. editor / Christo Dichev ; Gennady Agre. Springer, 2016. pp. 352-355 (Lecture Notes in Artificial Intelligence (subseries), Vol. 9883).

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title = "Expressing Sentiments in Game Reviews",

abstract = "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{\textquoteright} 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.",

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author = "Anna Secui and Maria-Dorinela Sirbu and Mihai Dascalu and Scott Crossly and Stefan Ruseti and Stefan Trausan-Matu",

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booktitle = "Artificial Intelligence: Methodology, Systems, and Applications",

note = "International Conference on Artificial Intelligence: Methodology, Systems, and Applications : Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2016 ; Conference date: 07-09-2016 Through 10-09-2016",

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Secui, A, Sirbu, M-D, Dascalu, M, Crossly, S, Ruseti, S & Trausan-Matu, S 2016, Expressing Sentiments in Game Reviews. in C Dichev & G Agre (eds), Artificial Intelligence: Methodology, Systems, and Applications: 17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings. Springer, Lecture Notes in Artificial Intelligence (subseries), vol. 9883, pp. 352-355, International Conference on Artificial Intelligence: Methodology, Systems, and Applications, Varna, Bulgaria, 7/09/16. https://doi.org/10.1007/978-3-319-44748-3_35

Expressing Sentiments in Game Reviews. / Secui, Anna; Sirbu, Maria-Dorinela; Dascalu, Mihai et al.
Artificial Intelligence: Methodology, Systems, and Applications: 17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings. ed. / Christo Dichev; Gennady Agre. Springer, 2016. p. 352-355 (Lecture Notes in Artificial Intelligence (subseries), Vol. 9883).

Research output: Chapter in Book/Report/Conference proceeding › Conference Article in proceeding › Academic › peer-review

TY - GEN

T1 - Expressing Sentiments in Game Reviews

AU - Secui, Anna

AU - Sirbu, Maria-Dorinela

AU - Dascalu, Mihai

AU - Crossly, Scott

AU - Ruseti, Stefan

AU - Trausan-Matu, Stefan

PY - 2016/9/27

Y1 - 2016/9/27

N2 - 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.

AB - 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.

KW - natural language processing

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KW - opinion mining

KW - lexical analysis

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DO - 10.1007/978-3-319-44748-3_35

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BT - Artificial Intelligence: Methodology, Systems, and Applications

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Secui A, Sirbu MD, Dascalu M, Crossly S, Ruseti S, Trausan-Matu S. Expressing Sentiments in Game Reviews. In Dichev C, Agre G, editors, Artificial Intelligence: Methodology, Systems, and Applications: 17th International Conference, AIMSA 2016, Varna, Bulgaria, September 7-10, 2016, Proceedings. Springer. 2016. p. 352-355. (Lecture Notes in Artificial Intelligence (subseries), Vol. 9883). doi: 10.1007/978-3-319-44748-3_35

Expressing Sentiments in Game Reviews

Abstract

Publication series

Conference

Keywords

Access to Document

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Projects

Rage: Realising an Applied Gaming Eco-system

Cite this