Opinion Mining using TRC Techniques

Nirach Romyen, Sureeporn Nualnim, Maleerat Maliyaem, Pudsadee Boonrawd, Kanchana Viriyapant, Tongpool Heeptaisong

Abstract

Sentiment analysis is a recent research field in Natural Language Processing (NLP). Text mining and computational techniques determine the sentiment discovered from text. This paper proposes a sentiment analysis using the Text-Representing Centroid (TRC). TRC is a method to determine minimum average distance to all words of the respective document, it also deploys a co-occurrence graph to represent existing relationships among terms in a customer’s reviews on particular products and services. A corpus that contains 800 randomly selected hotel reviews from TripAdvisor website is used to evaluate performance by comparison between TRC method and expert’s judgment review. The results show 75% accuracy over Thai customer’s reviews.

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Paper Citation


in Harvard Style

Romyen N., Nualnim S., Maliyaem M., Boonrawd P., Viriyapant K. and Heeptaisong T. (2021). Opinion Mining using TRC Techniques.In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-486-2, pages 321-326. DOI: 10.5220/0010315203210326


in Bibtex Style

@conference{icpram21,
author={Nirach Romyen and Sureeporn Nualnim and Maleerat Maliyaem and Pudsadee Boonrawd and Kanchana Viriyapant and Tongpool Heeptaisong},
title={Opinion Mining using TRC Techniques},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2021},
pages={321-326},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010315203210326},
isbn={978-989-758-486-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Opinion Mining using TRC Techniques
SN - 978-989-758-486-2
AU - Romyen N.
AU - Nualnim S.
AU - Maliyaem M.
AU - Boonrawd P.
AU - Viriyapant K.
AU - Heeptaisong T.
PY - 2021
SP - 321
EP - 326
DO - 10.5220/0010315203210326