Bots' Activity on COVID-19 Pro and Anti-Vaccination Networks: Analysis of Spanish-Written Messages on Twitter

被引:10
|
作者
Ruiz-Nunez, Carlos [1 ]
Segado-Fernandez, Sergio [2 ]
Jimenez-Gomez, Beatriz [2 ]
Jimenez Hidalgo, Pedro Jesus [3 ]
Romero Magdalena, Carlos Santiago [4 ]
Aguila Pollo, Maria del Carmen [2 ]
Santillan-Garcia, Azucena [5 ]
Herrera-Peco, Ivan [2 ,4 ]
机构
[1] Univ Malaga, Sch Med, PhD Program Biomed Translat Res & New Hlth Techno, Blvr Louis Pasteur, Malaga 29010, Spain
[2] Univ Alfonso X El Sabio, Fac Med, Dept Nursing, Avda Univ 1, Madrid 28691, Spain
[3] Hosp Univ Mostoles, Traumatol & Orthped Surg Serv, C Dr Luis Montes S-N, Madrid 28935, Spain
[4] Univ Alfonso X El Sabio, Fac Hlth Sci, Avda Univ 1, Madrid 28691, Spain
[5] Valencia Int Univ, C Pintor Sorolla 21, Valencia 46002, Spain
关键词
bots; COVID-19; misinformation; public health; social media; vaccines; SPREAD; RISE;
D O I
10.3390/vaccines10081240
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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 (p < 0.000). With respect to the bots' influence, the pro-vaccination network did have a significant influence compared to the activity of human users (p < 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.
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页数:10
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