Forecasting the Chilean electoral year: Using twitter to predict the presidential elections of 2017

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

4 Scopus citations

Abstract

Failures of traditional survey methods for measuring political climate and forecasting high impact events such as elections, offers opportunities to seek alternative methods. The analysis of social networks with computational linguistic methods have been proved to be useful as an alternative, but several studies related to these areas were conducted after the event (post hoc). Since 2017 was the election year for the 2018–2022 period for Chile and, moreover, there were three instances of elections in this year. This condition makes a good environment to conduct a case study for forecasting these elections with the use of social media as the main source of Data. This paper describes the implementation of multiple algorithms of supervised machine learning to do political sentiment analysis to predict the outcome of each election with Twitter data. These algorithms are Decision Trees, AdaBoost, Random Forest, Linear Support Vector Machines and ensemble voting classifiers. Manual annotations of a training set are conducted by experts to label pragmatic sentiment over the tweets mentioning an account or the name of a candidate to train the algorithms. Then a predictive set is collected days before the election and an automatic classification is performed. Finally the distribution of votes for each candidate is obtained from this classified set on the positive sentiment of the tweets. Ultimately, an accurate prediction was achieved using an ensemble voting classifier with a Mean Absolute Error of 0.51 % for the second round.

Original languageEnglish
Title of host publicationSocial Computing and Social Media. Technologies and Analytics - 10th International Conference, SCSM 2018, Held as Part of HCI International 2018, Proceedings
EditorsGabriele Meiselwitz
PublisherSpringer Verlag
Pages298-314
Number of pages17
ISBN (Print)9783319914848
DOIs
StatePublished - 2018
Externally publishedYes
Event10th International Conference on Social Computing and Social Media, SCSM 2018 Held as Part of HCI International 2018 - Las Vegas, United States
Duration: 15 Jul 201820 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10914 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Social Computing and Social Media, SCSM 2018 Held as Part of HCI International 2018
Country/TerritoryUnited States
CityLas Vegas
Period15/07/1820/07/18

Keywords

  • Election forecasting
  • Ex ante forecasting
  • Machine learning
  • Sentiment analysis

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