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Twitter social bots: The 2019 Spanish general election data
The term social bots refer to software-controlled accounts that actively participate in the social platforms to influence public opinion toward desired directions. To this extent, this data descriptor presents a Twitter dataset collected from October 4th to November 11th, 2019, within the context of...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394856/ https://www.ncbi.nlm.nih.gov/pubmed/32775565 http://dx.doi.org/10.1016/j.dib.2020.106047 |
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author | Pastor-Galindo, Javier Zago, Mattia Nespoli, Pantaleone López Bernal, Sergio Huertas Celdrán, Alberto Gil Pérez, Manuel Ruipérez-Valiente, José A. Martínez Pérez, Gregorio Gómez Mármol, Félix |
author_facet | Pastor-Galindo, Javier Zago, Mattia Nespoli, Pantaleone López Bernal, Sergio Huertas Celdrán, Alberto Gil Pérez, Manuel Ruipérez-Valiente, José A. Martínez Pérez, Gregorio Gómez Mármol, Félix |
author_sort | Pastor-Galindo, Javier |
collection | PubMed |
description | The term social bots refer to software-controlled accounts that actively participate in the social platforms to influence public opinion toward desired directions. To this extent, this data descriptor presents a Twitter dataset collected from October 4th to November 11th, 2019, within the context of the Spanish general election. Starting from 46 hashtags, the collection contains almost eight hundred thousand users involved in political discussions, with a total of 5.8 million tweets. The proposed data descriptor is related to the research article available at [1]. Its main objectives are: i) to enable worldwide researchers to improve the data gathering, organization, and preprocessing phases; ii) to test machine-learning-powered proposals; and, finally, iii) to improve state-of-the-art solutions on social bots detection, analysis, and classification. Note that the data are anonymized to preserve the privacy of the users. Throughout our analysis, we enriched the collected data with meaningful features in addition to the ones provided by Twitter. In particular, the tweets collection presents the tweets’ topic mentions and keywords (in the form of political bag-of-words), and the sentiment score. The users’ collection includes one field indicating the likelihood of one account being a bot. Furthermore, for those accounts classified as bots, it also includes a score that indicates the affinity to a political party and the followers/followings list. |
format | Online Article Text |
id | pubmed-7394856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73948562020-08-06 Twitter social bots: The 2019 Spanish general election data Pastor-Galindo, Javier Zago, Mattia Nespoli, Pantaleone López Bernal, Sergio Huertas Celdrán, Alberto Gil Pérez, Manuel Ruipérez-Valiente, José A. Martínez Pérez, Gregorio Gómez Mármol, Félix Data Brief Computer Science The term social bots refer to software-controlled accounts that actively participate in the social platforms to influence public opinion toward desired directions. To this extent, this data descriptor presents a Twitter dataset collected from October 4th to November 11th, 2019, within the context of the Spanish general election. Starting from 46 hashtags, the collection contains almost eight hundred thousand users involved in political discussions, with a total of 5.8 million tweets. The proposed data descriptor is related to the research article available at [1]. Its main objectives are: i) to enable worldwide researchers to improve the data gathering, organization, and preprocessing phases; ii) to test machine-learning-powered proposals; and, finally, iii) to improve state-of-the-art solutions on social bots detection, analysis, and classification. Note that the data are anonymized to preserve the privacy of the users. Throughout our analysis, we enriched the collected data with meaningful features in addition to the ones provided by Twitter. In particular, the tweets collection presents the tweets’ topic mentions and keywords (in the form of political bag-of-words), and the sentiment score. The users’ collection includes one field indicating the likelihood of one account being a bot. Furthermore, for those accounts classified as bots, it also includes a score that indicates the affinity to a political party and the followers/followings list. Elsevier 2020-07-21 /pmc/articles/PMC7394856/ /pubmed/32775565 http://dx.doi.org/10.1016/j.dib.2020.106047 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Computer Science Pastor-Galindo, Javier Zago, Mattia Nespoli, Pantaleone López Bernal, Sergio Huertas Celdrán, Alberto Gil Pérez, Manuel Ruipérez-Valiente, José A. Martínez Pérez, Gregorio Gómez Mármol, Félix Twitter social bots: The 2019 Spanish general election data |
title | Twitter social bots: The 2019 Spanish general election data |
title_full | Twitter social bots: The 2019 Spanish general election data |
title_fullStr | Twitter social bots: The 2019 Spanish general election data |
title_full_unstemmed | Twitter social bots: The 2019 Spanish general election data |
title_short | Twitter social bots: The 2019 Spanish general election data |
title_sort | twitter social bots: the 2019 spanish general election data |
topic | Computer Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7394856/ https://www.ncbi.nlm.nih.gov/pubmed/32775565 http://dx.doi.org/10.1016/j.dib.2020.106047 |
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