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Comput. Logic"],"published-print":{"date-parts":[[2022,1,31]]},"abstract":"<jats:p>\n            People are becoming increasingly more connected to each other as social networks continue to grow both in number and variety, and this is true for autonomous software agents as well. Taking them as a collection, such social platforms can be seen as one complex network with many different types of relations, different degrees of strength for each relation, and a wide range of information on each node. In this context, social media posts made by users are reflections of the content of their own individual (or local) knowledge bases; modeling how knowledge flows over the network\u2014or how this can possibly occur\u2014is therefore of great interest from a knowledge representation and reasoning perspective. In this article, we provide a formal introduction to the\n            <jats:italic>network knowledge base<\/jats:italic>\n            model, and then focus on the problem of how a single agent\u2019s knowledge base changes when exposed to a stream of news items coming from other members of the network. We do so by taking the classical belief revision approach of first proposing desirable properties for how such a local operation should be carried out (theoretical characterization), arriving at three different families of local operators, exploring concrete algorithms (algorithmic characterization) for two of the families, and proving properties about the relationship between the two characterizations (representation theorem). One of the most important differences between our approach and the classical models of belief revision is that in our case the input is more complex, containing additional information about each piece of information.\n          <\/jats:p>","DOI":"10.1145\/3477394","type":"journal-article","created":{"date-parts":[[2021,10,23]],"date-time":"2021-10-23T01:08:26Z","timestamp":1634951306000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Local Belief Dynamics in Network Knowledge Bases"],"prefix":"10.1145","volume":"23","author":[{"given":"Fabio R.","family":"Gallo","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Universidad Nacional del Sur (UNS) and Institute for Computer Science and Engineering (UNS-CONICET), Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3185-4992","authenticated-orcid":false,"given":"Gerardo I.","family":"Simari","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Universidad Nacional del Sur (UNS) and Institute for Computer Science and Engineering (UNS-CONICET), Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria Vanina","family":"Martinez","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Universidad de Buenos Aires (UBA) and Institute for Computer Science Research (UBA-CONICET), Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natalia Abad","family":"Santos","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Universidad Nacional del Sur (UNS), Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcelo A.","family":"Falappa","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Universidad Nacional del Sur (UNS) and Institute for Computer Science and Engineering (UNS-CONICET), Buenos Aires, Argentina"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,10,22]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.2307\/2274239"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1257\/jep.31.2.211"},{"issue":"3","key":"e_1_3_3_4_2","first-page":"87","article-title":"Main concepts, state of the art and future research questions in sentiment analysis","volume":"12","author":"Appel Orestes","year":"2015","unstructured":"Orestes Appel, Francisco Chiclana, and Jenny Carter. 2015. 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