Lexicon A Linguistic Approach for Sentiment Classification

被引:3
|
作者
Sharma, Ankita [1 ]
Ghose, Udayan [1 ]
机构
[1] Guru Gobind Singh Indraprastha Univ, USICT, New Delhi, India
关键词
sentiment analysis; lexicons; social media; natural language processing; text mining;
D O I
10.1109/Confluence51648.2021.9377057
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
It is known that social media has become a part and parcel in everyone's life. Human emotions are constantly being expressed in real time on various social networking sites. The availability of an enormous amount of opinion rich data from various social networking sites has fueled interest in opinion mining and sentiment analysis. There are mainly two approaches for performing sentiment analysis that is a lexicon-based approach and a machine learning based approach. In this paper, we chose to limit our study to just the lexicon-based approach of sentiment analysis. Lexicon based approach relies on the lexicons for classifying input data. Lexicon is a set of words, idioms, phrases, etc. having a semantic meaning. In this paper, prior research done in lexicon-based sentiment analysis has been studied; Also, a review of some state-of-the-art lexicon-based solutions have been presented for polarity classification of Sentiment Analysis. This paper is mainly oriented towards the various lexicons used fur polarity classification.
引用
收藏
页码:887 / 893
页数:7
相关论文
共 50 条
  • [1] Sentiment Lexicon Enhanced Neural Sentiment Classification
    Wu, Chuhan
    Wu, Fangzhao
    Liu, Junxin
    Huang, Yongfeng
    Xie, Xing
    [J]. PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM '19), 2019, : 1091 - 1100
  • [2] Sentiment Groups as Features of a Classification Model Using a Spanish Sentiment Lexicon: A Hybrid Approach
    Gutierrez, Ernesto
    Cervantes, Ofelia
    Baez-Lopez, David
    Alfredo Sanchez, J.
    [J]. PATTERN RECOGNITION (MCPR 2015), 2015, 9116 : 258 - 268
  • [3] The Lexicon and Linguistic Genealogical Classification
    del Olmo Lete, Gregorio
    [J]. AULA ORIENTALIS, 2016, 34 (02): : 359 - 369
  • [4] Combine Sentiment Lexicon and Dependency Parsing for Sentiment Classification
    Quan, Changqin
    Wei, Xiquan
    Ren, Fuji
    [J]. 2013 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII), 2013, : 100 - 104
  • [5] Building Thesaurus Lexicon using Dictionary-Based Approach for Sentiment Classification
    Park, Seongik
    Kim, Yanggon
    [J]. 2016 IEEE/ACIS 14TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS (SERA), 2016, : 39 - 44
  • [6] An Approach to Sentiment Analysis of Movie Reviews: Lexicon Based vs. Classification
    Augustyniak, Lukasz
    Kajdanowicz, Tomasz
    Kazienko, Przemyslaw
    Kulisiewicz, Marcin
    Tuliglowicz, Wlodzimierz
    [J]. HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS, HAIS 2014, 2014, 8480 : 168 - 178
  • [7] Sentence-Level Sentiment Polarity Classification Using a Linguistic Approach
    Tan, Luke Kien-Weng
    Na, Jin-Cheon
    Theng, Yin-Leng
    Chang, Kuiyu
    [J]. DIGITAL LIBRARIES: FOR CULTURAL HERITAGE, KNOWLEDGE DISSEMINATION, AND FUTURE CREATION: ICADL 2011, 2011, 7008 : 77 - +
  • [8] A sentiment analysis approach based on exploiting Chinese linguistic features and classification
    Gao, Kai
    Su, Shu
    Li, Dan-Yang
    Zhang, S-S.
    Wang, J-S.
    [J]. INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL, 2018, 29 (03) : 226 - 232
  • [9] Sentiment Lexicon Enhanced Attention-Based LSTM for Sentiment Classification
    Lei, Zeyang
    Yang, Yujiu
    Yang, Min
    [J]. THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2018, : 8105 - 8106
  • [10] A Lexicon-based Approach for Sentiment Classification of Amazon Books Reviews in Italian Language
    Chiavetta, Franco
    Lo Bosco, Giosue
    Pilato, Giovanni
    [J]. PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON WEB INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2 (WEBIST), 2016, : 159 - 170