Semantically Oriented Sentiment Mining in Location-Based Social Network Spaces

Date

2011-10-28

Author

Carlone, Domenico
Ortiz-Arroyo, Daniel

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper we describe a system that performs sentiment classification of reviews from social network sites using natural language techniques. The pattern-based method used in our system, applies classification rules for positive or negative sentiments depending on its overall score, calculated with the aid of SentiWordNet. We investigate several classifier models created from a combination of different methods applied at word and review levels. Our experimental results show that using part-of-speech helps to achieve better accuracy.

Subject Keywords

Opinion mining, Sentiment classification, SentiWordNet, Social networks

URI

https://hdl.handle.net/11511/64649

Collections

Department of Engineering Sciences, Conference / Seminar

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Citation Formats

D. Carlone and D. Ortiz-Arroyo, “Semantically Oriented Sentiment Mining in Location-Based Social Network Spaces,” 2011, vol. 7022, p. 234, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64649.