Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter
This study aims to analyze the role of bots in the dissemination of health information, both in favor of and opposing vaccination against COVID-19. Study design: An observational, retrospective, time-limited study was proposed, in which activity on the social network Twitter was analyzed. Methods: D...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Vaccines |
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| Online Access: | https://www.mdpi.com/2076-393X/10/8/1240 |
| _version_ | 1797441504769212416 |
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| author | Carlos Ruiz-Núñez Sergio Segado-Fernández Beatriz Jiménez-Gómez Pedro Jesús Jiménez Hidalgo Carlos Santiago Romero Magdalena María del Carmen Águila Pollo Azucena Santillán-Garcia Ivan Herrera-Peco |
| author_facet | Carlos Ruiz-Núñez Sergio Segado-Fernández Beatriz Jiménez-Gómez Pedro Jesús Jiménez Hidalgo Carlos Santiago Romero Magdalena María del Carmen Águila Pollo Azucena Santillán-Garcia Ivan Herrera-Peco |
| author_sort | Carlos Ruiz-Núñez |
| collection | DOAJ |
| description | This study aims to analyze the role of bots in the dissemination of health information, both in favor of and opposing vaccination against COVID-19. Study design: An observational, retrospective, time-limited study was proposed, in which activity on the social network Twitter was analyzed. Methods: Data related to pro-vaccination and anti-vaccination networks were compiled from 24 December 2020 to 30 April 2021 and analyzed using the software NodeXL and Botometer. The analyzed tweets were written in Spanish, including keywords that allow identifying the message and focusing on bots’ activity and their influence on both networks. Results: In the pro-vaccination network, 404 bots were found (14.31% of the total number of users), located mainly in Chile (37.87%) and Spain (14.36%). The anti-vaccination network bots represented 16.19% of the total users and were mainly located in Spain (8.09%) and Argentina (6.25%). The pro-vaccination bots generated greater impact than bots in the anti-vaccination network (<i>p</i> < 0.000). With respect to the bots’ influence, the pro-vaccination network did have a significant influence compared to the activity of human users (<i>p</i> < 0.000). Conclusions: This study provides information on bots’ activity in pro- and anti-vaccination networks in Spanish, within the context of the COVID-19 pandemic on Twitter. It is found that bots in the pro-vaccination network influence the dissemination of the pro-vaccination message, as opposed to those in the anti-vaccination network. We consider that this information could provide guidance on how to enhance the dissemination of public health campaigns, but also to combat the spread of health misinformation on social media. |
| first_indexed | 2024-03-09T12:24:02Z |
| format | Article |
| id | doaj.art-b57288e457da43efaf553e7a1f4d9b8a |
| institution | Directory Open Access Journal |
| issn | 2076-393X |
| language | English |
| last_indexed | 2024-03-09T12:24:02Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Vaccines |
| spelling | doaj.art-b57288e457da43efaf553e7a1f4d9b8a2023-11-30T22:37:01ZengMDPI AGVaccines2076-393X2022-08-01108124010.3390/vaccines10081240Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on TwitterCarlos Ruiz-Núñez0Sergio Segado-Fernández1Beatriz Jiménez-Gómez2Pedro Jesús Jiménez Hidalgo3Carlos Santiago Romero Magdalena4María del Carmen Águila Pollo5Azucena Santillán-Garcia6Ivan Herrera-Peco7PhD Program in Biomedicine, Translational Research and New Health Technologies, School of Medicine, University of Malaga, Blvr. Louis Pasteur, 29010 Málaga, SpainNursing Department, Faculty of Medicine, Universidad Alfonso X el Sabio, Avda Universidad, 1, Villanueva de la Cañada, 28691 Madrid, SpainNursing Department, Faculty of Medicine, Universidad Alfonso X el Sabio, Avda Universidad, 1, Villanueva de la Cañada, 28691 Madrid, SpainTraumatology and Orthopedic Surgery Service, Hospital Universitario de Móstoles, C/Dr. Luis Montes s/n., 28935 Madrid, SpainFaculty of Health Sciences, Universidad Alfonso X el Sabio, Avda Universidad, 1, Villanueva de la Cañada, 28691 Madrid, SpainNursing Department, Faculty of Medicine, Universidad Alfonso X el Sabio, Avda Universidad, 1, Villanueva de la Cañada, 28691 Madrid, SpainValencia International University, C/Pintor Sorolla 21, 46002 Valencia, SpainNursing Department, Faculty of Medicine, Universidad Alfonso X el Sabio, Avda Universidad, 1, Villanueva de la Cañada, 28691 Madrid, SpainThis study aims to analyze the role of bots in the dissemination of health information, both in favor of and opposing vaccination against COVID-19. Study design: An observational, retrospective, time-limited study was proposed, in which activity on the social network Twitter was analyzed. Methods: Data related to pro-vaccination and anti-vaccination networks were compiled from 24 December 2020 to 30 April 2021 and analyzed using the software NodeXL and Botometer. The analyzed tweets were written in Spanish, including keywords that allow identifying the message and focusing on bots’ activity and their influence on both networks. Results: In the pro-vaccination network, 404 bots were found (14.31% of the total number of users), located mainly in Chile (37.87%) and Spain (14.36%). The anti-vaccination network bots represented 16.19% of the total users and were mainly located in Spain (8.09%) and Argentina (6.25%). The pro-vaccination bots generated greater impact than bots in the anti-vaccination network (<i>p</i> < 0.000). With respect to the bots’ influence, the pro-vaccination network did have a significant influence compared to the activity of human users (<i>p</i> < 0.000). Conclusions: This study provides information on bots’ activity in pro- and anti-vaccination networks in Spanish, within the context of the COVID-19 pandemic on Twitter. It is found that bots in the pro-vaccination network influence the dissemination of the pro-vaccination message, as opposed to those in the anti-vaccination network. We consider that this information could provide guidance on how to enhance the dissemination of public health campaigns, but also to combat the spread of health misinformation on social media.https://www.mdpi.com/2076-393X/10/8/1240botsCOVID-19misinformationpublic healthsocial mediavaccines |
| spellingShingle | Carlos Ruiz-Núñez Sergio Segado-Fernández Beatriz Jiménez-Gómez Pedro Jesús Jiménez Hidalgo Carlos Santiago Romero Magdalena María del Carmen Águila Pollo Azucena Santillán-Garcia Ivan Herrera-Peco Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter Vaccines bots COVID-19 misinformation public health social media vaccines |
| title | Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter |
| title_full | Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter |
| title_fullStr | Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter |
| title_full_unstemmed | Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter |
| title_short | Bots’ Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter |
| title_sort | bots activity on covid 19 pro and anti vaccination networks analysis of spanish written messages on twitter |
| topic | bots COVID-19 misinformation public health social media vaccines |
| url | https://www.mdpi.com/2076-393X/10/8/1240 |
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