{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T09:13:07Z","timestamp":1758273187903},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"abstract":"<jats:p>We investigate opinion dynamics in multi-agent networks when there\n\nexists a bias toward one of two possible opinions; for example, reflecting a status quo vs a\n\nsuperior alternative.\n\nStarting with all agents sharing an initial opinion representing the status\n\nquo, the system evolves in steps. In each step, one agent selected uniformly at\n\nrandom adopts with some probability a the superior opinion, and with\n\nprobability 1 - a it follows an underlying update rule to revise its\n\nopinion on the basis of those held by its neighbors.\n\nWe analyze the convergence of the resulting process under two well-known update \n\nrules, namely majority and voter.\n\nThe framework we propose exhibits a rich structure, with a nonobvious\n\ninterplay between topology and underlying update rule.\n\nFor example, for the voter rule we show that the speed of convergence \n\nbears no significant dependence on the underlying topology, \n\nwhereas the picture changes completely under the majority rule, \n\nwhere network density negatively affects convergence.\n\nWe believe that the model we propose is at the same time simple, rich, and modular,\n\naffording mathematical characterization of the interplay between bias,\n\nunderlying opinion dynamics, and social structure in a unified setting.<\/jats:p>","DOI":"10.24963\/ijcai.2020\/8","type":"proceedings-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T08:12:10Z","timestamp":1594195930000},"page":"53-59","source":"Crossref","is-referenced-by-count":5,"title":["Biased Opinion Dynamics: When the Devil is in the Details"],"prefix":"10.24963","author":[{"given":"Aris","family":"Anagnostopoulos","sequence":"first","affiliation":[{"name":"Sapienza University of Rome"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luca","family":"Becchetti","sequence":"additional","affiliation":[{"name":"Sapienza University of Rome"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emilio","family":"Cruciani","sequence":"additional","affiliation":[{"name":"I3S Lab, INRIA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Pasquale","sequence":"additional","affiliation":[{"name":"University of Rome Tor Vergata"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sara","family":"Rizzo","sequence":"additional","affiliation":[{"name":"Gran Sasso Science Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-PRICAI-2020","name":"Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}","start":{"date-parts":[[2020,7,11]]},"theme":"Artificial Intelligence","location":"Yokohama, Japan","end":{"date-parts":[[2020,7,17]]}},"container-title":["Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T22:12:52Z","timestamp":1594246372000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2020\/8"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2020\/8","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}