{"type":"ScholarlyArticle","title":"Maximizing the Spread of an Opinion in Few Steps: Opinion Diffusion in Non-Binary Networks","authors":[{"name":"Robert Bredereck","slug":"robert-bredereck","given":"Robert","family":"Bredereck","affiliation":"Technische Universität Berlin , Chair of Algorithmics and Computational Complexity"},{"name":"Lilian Jacobs","slug":"lilian-jacobs","given":"Lilian","family":"Jacobs","affiliation":"Technische Universität Berlin , Chair of Algorithmics and Computational Complexity"},{"name":"Leon Kellerhals","slug":"leon-kellerhals","given":"Leon","family":"Kellerhals","affiliation":"Technische Universität Berlin , Chair of Algorithmics and Computational Complexity"}],"abstract":"We consider the setting of asynchronous opinion diffusion with majority threshold: given a social network with each agent assigned to one opinion, an agent will update its opinion if more than half of its neighbors agree on a different opinion. The stabilized final outcome highly depends on the sequence in which agents update their opinion. We are interested in optimistic sequences---sequences that maximize the spread of a chosen opinion. We complement known results for two opinions where optimistic sequences can be computed in time and length linear in the number of agents. We analyze upper and lower bounds on the length of optimistic sequences, showing quadratic bounds in the general and linear bounds in the acyclic case. Moreover, we show that in networks with more than two opinions determining a spread-maximizing sequence becomes intractable; surprisingly, already with three opinions the intractability results hold in highly restricted cases, e.g., when each agent has at most three neighbors, when looking for a short sequence, or when we aim for approximate solutions.","doi":"10.24963/ijcai.2020/225","url":"https://ijcai.org/proceedings/2020/225","pdf":"https://ijcai.org/proceedings/2020/0225.pdf","markdown":"https://ijcai.org/proceedings/2020/225.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/225","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":225,"pages":{"first":1622,"last":1628},"keywords":["Agent-based and Multi-agent Systems: Algorithmic Game Theory","Agent-based and Multi-agent Systems: Computational Social Choice","Knowledge Representation and Reasoning: Knowledge Representation and  Game Theory; Social Choice"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/25213/file_25213.m3u8","length_sec":296,"provider":"hls"}],"references":[{"position":1,"raw":"[Auletta et al., 2019] Vincenzo Auletta, Diodato Ferraioli, Valeria Fionda, and Gianluigi Greco. 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