Design and analysis of tweet-based election models for the 2021 Mexican legislative election

TL;DR

This study demonstrates that analyzing geolocated Twitter data related to the 2021 Mexican election can predict election outcomes more accurately than traditional polls, highlighting the potential of social media for social behavior modeling.

Contribution

The paper introduces election models based on geolocated Twitter data that outperform conventional polling methods in predicting election results.

Findings

Geolocated Twitter data improves election prediction accuracy.

Online social media data correlates with census data on population and internet usage.

Social media analysis can effectively reflect offline human behavior.

Abstract

Modelling and forecasting real-life human behaviour using online social media is an active endeavour of interest in politics, government, academia, and industry. Since its creation in 2006, Twitter has been proposed as a potential laboratory that could be used to gauge and predict social behaviour. During the last decade, the user base of Twitter has been growing and becoming more representative of the general population. Here we analyse this user base in the context of the 2021 Mexican Legislative Election. To do so, we use a dataset of 15 million election-related tweets in the six months preceding election day. We explore different election models that assign political preference to either the ruling parties or the opposition. We find that models using data with geographical attributes determine the results of the election with better precision and accuracy than conventional polling methods. These results demonstrate that analysis of public online data can outperform conventional polling methods, and that political analysis and general forecasting would likely benefit from incorporating such data in the immediate future. Moreover, the same Twitter dataset with geographical attributes is positively correlated with results from official census data on population and internet usage in Mexico. These findings suggest that we have reached a period in time when online activity, appropriately curated, can provide an accurate representation of offline behaviour.