Show simple item record

dc.contributor.authorAlsinet, Teresa
dc.contributor.authorArgelich Romà, Josep
dc.contributor.authorBéjar Torres, Ramón
dc.contributor.authorCemeli Sánchez, Joel
dc.date.accessioned2019-12-05T13:28:14Z
dc.date.available2019-12-05T13:28:14Z
dc.date.issued2019
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.urihttp://hdl.handle.net/10459.1/67673
dc.description.abstractTwitter is one of the most powerful social media platforms, reflecting both support and contrary opinions among people who use it. In a recent work, we developed an argumentative approach for analyzing the major opinions accepted and rejected in Twitter discussions. A Twitter discussion is modeled as a weighted argumentation graph where each node denotes a tweet, each edge denotes a relationship between a pair of tweets of the discussion and each node is attached to a weight that denotes the social relevance of the corresponding tweet in the discussion. In the social network Twitter, a tweet always refers to previous tweets in the discussion, and therefore the underlying argument graph obtained is acyclic. However, when in a discussion we group the tweets by author, the graph that we obtain can contain cycles. Based on the structure of graphs, in this work we introduce a distributed algorithm to compute the set of globally accepted opinions of a Twitter discussion based on valued argumentation. To understand the usefulness of our distributed algorithm, we study cases of argumentation graphs that can be solved efficiently with it. Finally, we present an experimental investigation that shows that when solving acyclic argumentation graphs associated with Twitter discussions our algorithm scales at most with linear time with respect to the size of the discussion. For argumentation graphs with cycles, we study tractable cases and we analyze how frequent are these cases in Twitter. Moreover, for the non-tractable cases we analyze how close is the solution of the distributed algorithm with respect to the one computed with the general sequential algorithm, that we have previously developed, that solves any argumentation graph.ca_ES
dc.description.sponsorshipThis work was partially funded by Spanish Project TIN2015-71799-C2-2-P (MINECO/FEDER).ca_ES
dc.language.isoengca_ES
dc.publisherSpringerca_ES
dc.relationMINECO/PN2013-2016/TIN2015-71799-C2-2-Pca_ES
dc.relation.isformatofReproducció del document publicat a https://doi.org/10.1007/s00500-018-3380-xca_ES
dc.relation.ispartofSoft Computing, 2019, vol. 23, núm,. 7, p. 2147–2166ca_ES
dc.rights(c) Springer-Verlag GmbH Germany, part of Springer Nature, 2018ca_ES
dc.subjectTwitter discussionsca_ES
dc.subjectValued argumentationca_ES
dc.subjectProbability valuesca_ES
dc.subjectDistributed algorithmca_ES
dc.subjectTractable casesca_ES
dc.titleA distributed argumentation algorithm for mining consistent opinions in weighted Twitter discussionsca_ES
dc.typeinfo:eu-repo/semantics/articleca_ES
dc.identifier.idgrec028712
dc.type.versioninfo:eu-repo/semantics/acceptedVersionca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES
dc.identifier.doihttps://doi.org/10.1007/s00500-018-3380-x


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record