The Interfaces Twitter Elections Dataset: Construction process and characteristics of big social data during the 2022 presidential elections in Brazil. - Sylvia Iasulaitis; Alan Demétrius Baria Valejo; Bruno Cardoso Greco; Vinicius Gonçalves Perillo; Guilherme Henrique Messias; Isabella Vicari; with the Interfaces—Center for Sociopolitical Studies of Algorithms and Artificial Intelligence (PLoS ONE)
The main objective of this study is to describe the process of collecting data extracted from Twitter (X) during the Brazilian presidential elections in 2022, encompassing the post-election period and the event of the attack on the buildings of the executive, legislative, and judiciary branches in January 2023. The work of collecting data took one year. Additionally, the study provides an overview of the general characteristics of the dataset created from 282 million tweets, named "The Interfaces Twitter Elections Dataset" (ITED-Br), the third most extensive dataset of tweets with political purposes. The process of collecting and creating the database for this study went through three major stages, subdivided into several processes: (1) A preliminary analysis of the platform and its operation; (2) Contextual analysis, creation of the conceptual model, and definition of Keywords and (3) Implementation of the Data Collection Strategy. Python algorithms were developed to model each primary collection type. The "token farm" algorithm, was employed to iterate over available API keys. While Twitter is generally a "public" access platform and fits into big data standards, extracting valuable information is not trivial due to the volume, speed, and heterogeneity of data. This study concludes that acquiring informational value requires expertise not only in sociopolitical areas but also in computational and informational studies, highlighting the interdisciplinary nature of such research.