Political Opinion Mining from Twitter

被引:1
|
作者
Sharma, Yashvardhan [1 ]
Mittal, Ekansh [1 ]
Garg, Mayank [2 ]
机构
[1] Birla Inst Technol & Sci, Dept Comp Sci, Pilani, Rajasthan, India
[2] Birla Inst Technol & Sci, Elect & Elect Dept, Pilani, Rajasthan, India
关键词
Linguistics; Natural Language Processing; Opinion Mining; Phonetics; Sentimental Analysis;
D O I
10.4018/IJISSS.2016100104
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Twitter is one of the most popular micro-blogging platform for people to express their political views in and around the elections. Hence during pre-elections twitter becomes a rich resource of data to understand the changing tenor of political leaders with time. During this time, when views, opinions and judgments are shared so prolifically through online media, tools which can provide the crux of this content are paramount. In this paper the authors have developed one such sentiment analysis tool to analyze the changing political views of persons with time. Using the tool they classify the tweets as positive, negative or neutral and studying it over time the authors successfully estimate the mood of the person. The authors have also developed a specialized phonetic dictionary to provide better approximation for most commonly used slangs and abbreviations.
引用
收藏
页码:47 / 56
页数:10
相关论文
共 50 条
  • [41] Using Twitter to Characterize Public Opinion in Brazil During Political Events
    Nobre, Gabriel Peres
    Marques Ferreira, Kecia Aline
    Silva, Ismael Santana
    Rodrigues Barbosa, Glivia Angelica
    [J]. INTERNATIONAL JOURNAL OF E-COLLABORATION, 2019, 15 (03) : 49 - 61
  • [42] The Multiple Facets of Influence: Identifying Political Influentials and Opinion Leaders on Twitter
    Dubois, Elizabeth
    Gaffney, Devin
    [J]. AMERICAN BEHAVIORAL SCIENTIST, 2014, 58 (10) : 1260 - 1277
  • [43] Characterization of Public Opinion on Political Events in Brazil Based on Twitter Data
    Nobre, Gabriel Peres
    Marques Ferreira, Kecia Aline
    Silva, Ismael Santana
    Rodrigues Barbosa, Glivia Angelica
    [J]. COLLABORATION AND TECHNOLOGY (CRIWG 2018), 2018, 11001 : 105 - 116
  • [44] Opinion Mining in Twitter How to Make Use of Sarcasm to Enhance Sentiment Analysis
    Bouazizi, Mondher
    Ohtsuki, Tomoaki
    [J]. PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015), 2015, : 1594 - 1597
  • [45] A Twitter Based Opinion Mining to Perform Analysis on Network Issues of Telecommunication Companies
    Zala, Dhruvi K.
    [J]. PROCEEDINGS OF THE 2018 3RD INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2018), 2018, : 437 - 441
  • [46] NLP-based Sentiment Analysis for Twitter's Opinion Mining and Visualization
    Al-Ghalibi, Maha
    Al-Azzawi, Adil
    Lawonn, Kai
    [J]. ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2018), 2019, 11041
  • [47] Twitter Opinion Mining on COVID-19 Vaccinations by Machine Learning Presence
    Islam, Md Babul
    Hasibunnahar, Swarna
    Shukla, Piyush Kumar
    Shukla, Prashant Kumar
    Rawat, Paresh
    Dange, Jyoti
    [J]. PROCEEDINGS OF THIRD DOCTORAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE, DOSCI 2022, 2023, 479 : 37 - 55
  • [48] OpinionMine: A Bayesian-based framework for opinion mining using Twitter Data
    Zervoudakis, Stefanos
    Marakakis, Emmanouil
    Kondylakis, Haridimos
    Goumas, Stefanos
    [J]. MACHINE LEARNING WITH APPLICATIONS, 2021, 3
  • [49] Investigating Temporal and Spatial Trends of Brand Images using Twitter Opinion Mining
    Cho, Seung Woo
    Cha, Moon Soo
    Kim, So Yeon
    Song, Joo Cheol
    Sohn, Kyung-Ah
    [J]. 2014 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND APPLICATIONS (ICISA), 2014,
  • [50] Twitter-based Opinion Mining for Flight Service Utilizing Machine Learning
    Tiwari, Prayag
    Pandey, Hari Mohan
    Khamparia, Aditya
    Kumar, Sachin
    [J]. INFORMATICA-JOURNAL OF COMPUTING AND INFORMATICS, 2019, 43 (03): : 381 - 386