Twitter Buzzer Detection for Indonesian Presidential Election

Andi Suciati, Ari Wibisono, Petrus Mursanto

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

3 Citations (Scopus)

Abstract

The campaign that was done in social media has high correlation to the supporters who disseminating the information deliberately, which called as buzzer. However, data that were generated by buzzer accounts can be considered as noise and need to be removed. In this research we performed task for detecting the buzzer accounts in Twitter by observing the impact of features we used which we selected based on their Mutual Information scores. We examined the performance of four machine learning algorithms which are Ada Boost (AB), Gradient Boosting (GB), Extreme Gradient Boosting (XGB), and Histogram-based Gradient Boosting (HGB). The algorithms were evaluated using 10 folds cross validation and the results show that the best accuracy and precision achieved by AB which are 62.3% and 61.3% respectively with 25 features while the recall attained by XGB (67.9%) which the score same with its recall result with 20 features.

Original languageEnglish
Title of host publicationICICOS 2019 - 3rd International Conference on Informatics and Computational Sciences
Subtitle of host publicationAccelerating Informatics and Computational Research for Smarter Society in The Era of Industry 4.0, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728146102
DOIs
Publication statusPublished - Oct 2019
Event3rd International Conference on Informatics and Computational Sciences, ICICOS 2019 - Semarang, Indonesia
Duration: 29 Oct 201930 Oct 2019

Publication series

NameICICOS 2019 - 3rd International Conference on Informatics and Computational Sciences: Accelerating Informatics and Computational Research for Smarter Society in The Era of Industry 4.0, Proceedings

Conference

Conference3rd International Conference on Informatics and Computational Sciences, ICICOS 2019
Country/TerritoryIndonesia
CitySemarang
Period29/10/1930/10/19

Keywords

  • buzzer detection
  • mutual information
  • social media
  • twitter

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