Buzzer Detection and Sentiment Analysis for Predicting Presidential Election Results in a Twitter Nation

Mochamad Ibrahim, Omar Abdillah, Alfan Farizki Wicaksono, Mirna Adriani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

31 Citations (Scopus)

Abstract

In this paper, we present our approach for predicting the results of Indonesian Presidential Election using Twitter as our main resource. We explore the possibility of easy-togather Twitter data to be utilized as a survey supporting tool to understand public opinion. First, we collected Twitter data during the campaign period. Second, we performed automatic buzzer detection on our Twitter data to remove those tweets generated by computer bots, paid users, and fanatic users that usually become noise in our data. Third, we performed a fine-grained political sentiment analysis to partition each tweet into several sub-tweets and subsequently assigned each sub-tweet with one of the candidates and its sentiment polarity. Finally, to predict the election results, we leveraged the number of positive sub-tweets for each candidate. Our experiment shows that the mean absolute error (MAE) of our Twitter-based prediction is 0.61%, which is surprisingly better than the prediction results published by several independent survey institutions (offline polls). Our study suggests that Twitter can serve as an important resource for any political activity, specifically for predicting the final outcomes of the election itself.

Original languageEnglish
Title of host publicationProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
EditorsXindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1348-1353
Number of pages6
ISBN (Electronic)9781467384926
DOIs
Publication statusPublished - 29 Jan 2016
Event15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States
Duration: 14 Nov 201517 Nov 2015

Publication series

NameProceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Conference

Conference15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/TerritoryUnited States
CityAtlantic City
Period14/11/1517/11/15

Keywords

  • Buzzer Detection
  • Election Prediction
  • Sentiment Analysis
  • Twitter
  • Twitter Based Election Prediction
  • Twitter Data Analysis

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