Abstract
Social media has been playing a huge role towards the society nowadays, mainly because of the community express their opinions and thoughts mostly on their own social media. Therefore, it is difficult to figure out the emotion of each sentences on social media as the words used carries different meaning individually, and when used in a sentence. A method has been created from existing static lexicon (staticLex) to improve the performance of determining the emotion on message-level sentiment analysis, called adaptive lexicon (adaLex) [2]. Data source is from Plutchik’s emotion annotated data.
Keywords: sentiment analysis, adaptive lexicon, static lexicon
Authors
Kong Yong Jin [1] ; Yu Yong Poh [2] ; Lim Tong Ming [3] ; Lim Kong Hua [4]
[1][2][3][4] Faculty of Computing and Information Technology, Tunku Abdul Rahman University of Management and Technology, Kuala Lumpur, Malaysia
[1]kongyj-wa15@student.tarc.edu.my ; [2] yuyp@tarc.edu.my ; [3] limtm@tarc.edu.my ; [4] limkh@tarc.edu.my
Cite Me
Plain Text:
Y.J.Kong, Y.P.Yu, T.M.Lim, K.H.Lim, "Sentiment Analysis on Adaptive Lexicon-Based Approach and Statistical Lexicon-Based Approach," International Conference on Digital Transformation and Applications (ICDXA) 2020, 2020, pp. 82-86, doi: https://doi.org/10.56453/icdxa.2020.1007.
BibTex:
@INPROCEEDINGS{ICDXA2020T107,
author={Kong, Yong Jin and Yu, Yong Poh and Lim, Tong Ming and Lim, Kong Hua},
booktitle={International Conference on Digital Transformation and Applications (ICDXA) 2020},
title={Sentiment Analysis on Adaptive Lexicon-Based Approach and Statistical Lexicon-Based Approach},
year={2020},
volume={},
number={},
pages={82-86},
doi={https://doi.org/10.56453/icdxa.2020.1007}}
