TY - GEN
T1 - Topic Model Based Opinion Mining and Sentiment Analysis
AU - Vamshi, Krishna B.
AU - Pandey, Ajeet Kumar
AU - Siva, Kumar A.P.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/20
Y1 - 2018/8/20
N2 - This paper discusses a new topic model based approach for opinion mining and sentiment analysis of text reviews posted in web forums or social media site which are mostly in unstructured in nature. In recent years, opinions are exchanged in clouds about any product, person, event or any interested topic. These opinions help in decision making for choosing a product or getting feedback about any topic. Opinion mining and sentiment analysis are related in a sense that opining mining deals with analyzing and summarizing expressed opinions whereas sentiment analysis classifies opinionated text into positive and negative. Aspect extraction is a crucial problem in sentiment analysis. Model proposed in the paper utilizes topic model for aspect extraction and support vector machine learning technique for sentiment classification of textual reviews. The goal is to automate the process of mining attitudes, opinions and hidden emotions from text.
AB - This paper discusses a new topic model based approach for opinion mining and sentiment analysis of text reviews posted in web forums or social media site which are mostly in unstructured in nature. In recent years, opinions are exchanged in clouds about any product, person, event or any interested topic. These opinions help in decision making for choosing a product or getting feedback about any topic. Opinion mining and sentiment analysis are related in a sense that opining mining deals with analyzing and summarizing expressed opinions whereas sentiment analysis classifies opinionated text into positive and negative. Aspect extraction is a crucial problem in sentiment analysis. Model proposed in the paper utilizes topic model for aspect extraction and support vector machine learning technique for sentiment classification of textual reviews. The goal is to automate the process of mining attitudes, opinions and hidden emotions from text.
UR - https://www.scopus.com/pages/publications/85053488992
UR - https://www.scopus.com/inward/citedby.url?scp=85053488992&partnerID=8YFLogxK
U2 - 10.1109/ICCCI.2018.8441220
DO - 10.1109/ICCCI.2018.8441220
M3 - Conference contribution
AN - SCOPUS:85053488992
SN - 9781538622384
T3 - 2018 International Conference on Computer Communication and Informatics, ICCCI 2018
BT - 2018 International Conference on Computer Communication and Informatics, ICCCI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Computer Communication and Informatics, ICCCI 2018
Y2 - 4 January 2018 through 6 January 2018
ER -