Effect of Zealots on the Opinion Dynamics of Rational Agents with Bounded Confidence

Karan, Farshad Salimi Naneh; Chakraborty, Samarjit

doi:10.5506/aphyspolb.49.73

Cited by 10 publications

(6 citation statements)

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“…Zealots and automated bots (i.e. individuals who never change their opinions) can induce information gerrymandering [3] when strategically established in a network, thereby distorting the voter model dynamics [21][22][23][24][25]. In particular, a few zealots can prevent reaching a consensus or formation of a robust majority [26,27], indicating that voter model dynamics are easily distorted.…”

Section: Introductionmentioning

confidence: 99%

Mitigation of adversarial attacks on voter model dynamics by network heterogeneity

Chiyomaru

Takemoto

2023

J. Phys. Complex.

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Voter model dynamics in complex networks are vulnerable to adversarial attacks. In particular, the voting outcome can be inverted by adding extremely small perturbations that are strategically generated in social networks, even when one opinion is dominant over the other. However, the mitigation of adversarial attacks on the voter model dynamics in complex networks has not been thoroughly investigated. Thus, we examined network structures that could mitigate adversarial attacks using model networks and real-world networks, considering that the network structure affects the voter model dynamics. Numerical simulations demonstrated that the heterogeneity of node degrees in the networks (degree heterogeneity) significantly mitigates adversarial attacks. In particular, for complex networks with a power-law degree distribution $P(k)\sim k^{-\gamma}$, the mitigation effect is significant for $\gamma \leq 3$. However, the mitigation effect of the degree heterogeneity was relatively weak for large and dense networks. The degree correlation and clustering in the networks exhibited almost no mitigation effect. The results enhance our understanding of how opinion dynamics and collective decision-making are distorted in social networks and may be useful for considering defense strategies against adversarial attacks.

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Section: Introductionmentioning

confidence: 99%

Mitigation of adversarial attacks on voter model dynamics by network heterogeneity

Chiyomaru

Takemoto

2023

J. Phys. Complex.

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“…This study is a correlational research in terms of nature and an applied research [11][12][13][14], in terms of the purpose of the study. Data collection was done using library method and document mining method, which required data from reliable sources such as published forms and financial reports from the World Bank and Economic Atlas.…”

Section: Methodsmentioning

confidence: 99%

The study of Economic Complexity and GDP Effect on Inflation Rate and Income Inequality in Persian Gulf States 2002 -2015

Moghadasi¹

2018

MJMIE

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The purpose of this study was to examine the effect of economic complexity and gross domestic product (GDP) on inflation rate and income inequality between 2002 and 2015. The statistical population of this research is Persian Gulf states, and independent variables are economic complexity and GDP and dependent variables are inflation rate and income inequality. The present research is an applied research and is essentially a descriptive research, and also in terms of methodology, it is considered as a correlational research. The theoretical literature and subjective history and research data collection had been done using library method and document mining method, respectively. Descriptive and inferential statistics have been used to describe and summarize the collected data. Firstly, variance heterogeneity pre-tests, F lemmer test, Hausman test and Jarque-Bera test were used to for analyzing data and then multivariate regression test and Eviews software were used to confirm and reject the research hypotheses. The results of the research show that economic complexity and GDP have a positive and significant effect on inflation rate, while economic complexity and GDP have a negative effect on income inequality.

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“…The bot is represented as a stubborn agent that does not change its opinion but sticks to the same opinion throughout the simulation (Stewart et al 2019;Karan et al 2018;Yildiz et al 2013). In different conditions, we manipulate the degree to which this opinion is extreme (i.e., the distance from the mean opinion of the agents).…”

Section: Botmentioning

confidence: 99%

Bots influence opinion dynamics without direct human-bot interaction: the mediating role of recommender systems

2022

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Bots’ ability to influence public discourse is difficult to estimate. Recent studies found that hyperpartisan bots are unlikely to influence public opinion because bots often interact with already highly polarized users. However, previous studies focused on direct human-bot interactions (e.g., retweets, at-mentions, and likes). The present study suggests that political bots, zealots, and trolls may indirectly affect people’s views via a platform’s content recommendation system's mediating role, thus influencing opinions without direct human-bot interaction. Using an agent-based opinion dynamics simulation, we isolated the effect of a single bot—representing 1% of nodes in a network—on the opinion of rational Bayesian agents when a simple recommendation system mediates the agents’ content consumption. We compare this experimental condition with an identical baseline condition where such a bot is absent. Across conditions, we use the same random seed and a psychologically realistic Bayesian opinion update rule so that conditions remain identical except for the bot presence. Results show that, even with limited direct interactions, the mere presence of the bot is sufficient to shift the average population’s opinion. Virtually all nodes—not only nodes directly interacting with the bot—shifted towards more extreme opinions. Furthermore, the mere bot’s presence significantly affected the internal representation of the recommender system. Overall, these findings offer a proof of concept that bots and hyperpartisan accounts can influence population opinions not only by directly interacting with humans but also by secondary effects, such as shifting platforms’ recommendation engines’ internal representations. The mediating role of recommender systems creates indirect causal pathways of algorithmic opinion manipulation.

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Effect of Zealots on the Opinion Dynamics of Rational Agents with Bounded Confidence

Cited by 10 publications

References 0 publications

Mitigation of adversarial attacks on voter model dynamics by network heterogeneity

Mitigation of adversarial attacks on voter model dynamics by network heterogeneity

The study of Economic Complexity and GDP Effect on Inflation Rate and Income Inequality in Persian Gulf States 2002 -2015

Bots influence opinion dynamics without direct human-bot interaction: the mediating role of recommender systems

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