| Full text | |
| Author(s): |
Vega-Oliveros, Didier A.
[1, 2]
;
Grande, Helder L. C.
[3]
;
Iannelli, Flavio
[4]
;
Vazquez, Federico
[5, 6]
Total Authors: 4
|
| Affiliation: | [1] Univ Campinas UNICAMP, Inst Comp, Campinas, SP - Brazil
[2] Indiana Univ, Luddy Sch Informat Comp & Engn, Ctr Complex Networks & Syst Res, Bloomington, IN - USA
[3] Natl Inst Space Res INPE, Sao Jose Dos Campos, SP - Brazil
[4] Univ Zurich, URPP Social Networks, Andreasstr 15, CH-8050 Zurich - Switzerland
[5] Consejo Nacl Invest Cient & Tecn, Buenos Aires, DF - Argentina
[6] Univ Buenos Aires, Inst Calculo, FCEN, Buenos Aires, DF - Argentina
Total Affiliations: 6
|
| Document type: | Journal article |
| Source: | European Physical Journal-Special Topics; v. 230, n. 14-15, p. 2875-2886, OCT 2021. |
| Web of Science Citations: | 1 |
| Abstract | |
The diffusion of opinions in social networks is a relevant process for adopting positions and attracting potential voters in political campaigns. Opinion polarization, bias, targeted diffusion, and the radicalization of postures are key elements for understanding the voting dynamics' challenges. In particular, social bots are currently a new element that can have a pronounced effect on the formation of opinions during electoral processes by, for instance, creating fake accounts in social networks to manipulate elections. Here, we propose a voter model incorporating bots and radical or intolerant individuals in the decision-making process. The dynamics of the system occur in a multiplex network of interacting agents composed of two layers, one for the dynamics of opinions where agents choose between two possible alternatives, and the other for the tolerance dynamics, in which agents adopt one of the two tolerance levels. The tolerance accounts for the likelihood to change opinion in an interaction, with tolerant (intolerant) agents switching opinion with probability 1.0 (gamma <= 1). We find that intolerance leads to a consensus of tolerant agents during an initial stage that scales as tau(+)similar to gamma(-1) In N, who then reach an opinion consensus during the second stage in a time that scales as tau similar to N, where N is the number of agents. Therefore, very intolerant agents (gamma << 1) could considerably slow down dynamics towards the final consensus state. We also find that the inclusion of a fraction sigma(-)(B) of bots breaks the symmetry between both opinions, driving the system to a consensus of intolerant agents with the bots' opinion. Thus, bots eventually impose their opinion to the entire population, in a time that scales as tau(-)(B) similar to gamma(-1) for gamma << sigma(-)(B) and tau(-)(B) similar to 1/sigma(-)(B) ( )for sigma(-)(B) << gamma. (AU) | |
| FAPESP's process: | 18/24260-5 - Spatiotemporal Data Analytics based on Complex Networks |
| Grantee: | Didier Augusto Vega Oliveros |
| Support Opportunities: | Scholarships abroad - Research Internship - Post-doctor |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 19/26283-5 - Learning visual clues of the passage of time |
| Grantee: | Didier Augusto Vega Oliveros |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 16/23698-1 - Dynamical Processes in Complex Network based on Machine Learning |
| Grantee: | Didier Augusto Vega Oliveros |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 15/50122-0 - Dynamic phenomena in complex networks: basics and applications |
| Grantee: | Elbert Einstein Nehrer Macau |
| Support Opportunities: | Research Projects - Thematic Grants |