The “RightNets” dataset presented in this paper was collected within the framework of the RightNets project, focusing on digital campaigning during the six months leading up to the 2024 European elections in Italy. It encompasses 10,000 tweets and 411 Facebook posts, systematically gathered to analyze online political dynamics. For each tweet, the dataset records its unique ID, engagement metrics—including retweet, reply, like, and quote counts—and timestamps, along with attributes identifying retweets, replies, or quotes. Similarly, the Facebook dataset includes post metadata such as unique ID and engagement metrics like likes, shares, and comments, as well as posting dates. The data was collected using automated tools that targeted specific election-related hashtags, ensuring a focus on relevant political content. The dataset is hosted in a GitHub repository, providing accessibility and fostering reproducibility. By emphasizing transparency, it allows researchers to study key dimensions of digital campaigning, such as engagement patterns, the spread of misinformation, and the potential for foreign interference. The granular details enable analysis of voter interaction trends and candidate accountability across platforms. Furthermore, its design supports interdisciplinary research, with applications in political science, law, and computational social science. The dataset holds significant potential for reuse, serving as a benchmark for longitudinal studies, a foundation for computational model development, and a resource for comparative analyses across elections and countries. It is a tool for exploring the complexities of modern digital political communication and for informing regulatory measures to enhance the fairness of online electoral processes.

Social media and electoral dynamics: A dataset of X and facebook activity during the 2024 European elections

Sernani, Paolo
2025-01-01

Abstract

The “RightNets” dataset presented in this paper was collected within the framework of the RightNets project, focusing on digital campaigning during the six months leading up to the 2024 European elections in Italy. It encompasses 10,000 tweets and 411 Facebook posts, systematically gathered to analyze online political dynamics. For each tweet, the dataset records its unique ID, engagement metrics—including retweet, reply, like, and quote counts—and timestamps, along with attributes identifying retweets, replies, or quotes. Similarly, the Facebook dataset includes post metadata such as unique ID and engagement metrics like likes, shares, and comments, as well as posting dates. The data was collected using automated tools that targeted specific election-related hashtags, ensuring a focus on relevant political content. The dataset is hosted in a GitHub repository, providing accessibility and fostering reproducibility. By emphasizing transparency, it allows researchers to study key dimensions of digital campaigning, such as engagement patterns, the spread of misinformation, and the potential for foreign interference. The granular details enable analysis of voter interaction trends and candidate accountability across platforms. Furthermore, its design supports interdisciplinary research, with applications in political science, law, and computational social science. The dataset holds significant potential for reuse, serving as a benchmark for longitudinal studies, a foundation for computational model development, and a resource for comparative analyses across elections and countries. It is a tool for exploring the complexities of modern digital political communication and for informing regulatory measures to enhance the fairness of online electoral processes.
2025
Elsevier
Internazionale
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11393/351730
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