{"title":"有顽固代理的舆论动态博弈中的堆栈伯格解决方案","authors":"Yulia Kareeva, Artem Sedakov, Mengke Zhen","doi":"10.1007/s10614-024-10601-9","DOIUrl":null,"url":null,"abstract":"<p>The paper examines an opinion dynamics game in a social group with two active agents (influencers) based on the Friedkin–Johnsen model. In the game, we assume sequential announcements of influence efforts by the active agents on the opinions of other (passive) agents of the group. We characterize the Stackelberg solutions as proper solution concepts under sequential play. We then analyze the solutions with a number of measures that quantify them in different aspects: (i) the role of the information structure, i.e., open-loop vs. feedback, (ii) the advantage of sequential over simultaneous moves, and (iii) whether being a leader in the game is more cost-effective than being a follower. Finally, we perform numerical simulations for Zachary’s karate club network to understand how the Stackelberg solutions are sensitive to a change in a parameter characterizing the stubbornness of agents to their initial opinions. The results indicate that the information structure has minimal effect; however, the greatest advantage of the open-loop policy could be achieved with a fully conforming society. In such a society, the efforts of influencers become more efficient, reducing the spread of opinions. Additionally, we observe that the follower has an advantage in the game, which forces each influencer to delay their action until the other one acts.</p>","PeriodicalId":50647,"journal":{"name":"Computational Economics","volume":"32 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stackelberg Solutions in an Opinion Dynamics Game with Stubborn Agents\",\"authors\":\"Yulia Kareeva, Artem Sedakov, Mengke Zhen\",\"doi\":\"10.1007/s10614-024-10601-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The paper examines an opinion dynamics game in a social group with two active agents (influencers) based on the Friedkin–Johnsen model. In the game, we assume sequential announcements of influence efforts by the active agents on the opinions of other (passive) agents of the group. We characterize the Stackelberg solutions as proper solution concepts under sequential play. We then analyze the solutions with a number of measures that quantify them in different aspects: (i) the role of the information structure, i.e., open-loop vs. feedback, (ii) the advantage of sequential over simultaneous moves, and (iii) whether being a leader in the game is more cost-effective than being a follower. Finally, we perform numerical simulations for Zachary’s karate club network to understand how the Stackelberg solutions are sensitive to a change in a parameter characterizing the stubbornness of agents to their initial opinions. The results indicate that the information structure has minimal effect; however, the greatest advantage of the open-loop policy could be achieved with a fully conforming society. In such a society, the efforts of influencers become more efficient, reducing the spread of opinions. Additionally, we observe that the follower has an advantage in the game, which forces each influencer to delay their action until the other one acts.</p>\",\"PeriodicalId\":50647,\"journal\":{\"name\":\"Computational Economics\",\"volume\":\"32 1\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1007/s10614-024-10601-9\",\"RegionNum\":4,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s10614-024-10601-9","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Stackelberg Solutions in an Opinion Dynamics Game with Stubborn Agents
The paper examines an opinion dynamics game in a social group with two active agents (influencers) based on the Friedkin–Johnsen model. In the game, we assume sequential announcements of influence efforts by the active agents on the opinions of other (passive) agents of the group. We characterize the Stackelberg solutions as proper solution concepts under sequential play. We then analyze the solutions with a number of measures that quantify them in different aspects: (i) the role of the information structure, i.e., open-loop vs. feedback, (ii) the advantage of sequential over simultaneous moves, and (iii) whether being a leader in the game is more cost-effective than being a follower. Finally, we perform numerical simulations for Zachary’s karate club network to understand how the Stackelberg solutions are sensitive to a change in a parameter characterizing the stubbornness of agents to their initial opinions. The results indicate that the information structure has minimal effect; however, the greatest advantage of the open-loop policy could be achieved with a fully conforming society. In such a society, the efforts of influencers become more efficient, reducing the spread of opinions. Additionally, we observe that the follower has an advantage in the game, which forces each influencer to delay their action until the other one acts.
期刊介绍:
Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing