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Social Event Detection with Interaction Graph Modeling

Wang, Yanxiang; Sundaram, Hari; Xie, Lexing

Description

This paper focuses on detecting social, physical-world events from photos posted on social media sites. The problem is important: cheap media capture devices have significantly increased the number of photos shared on these sites. The main contribution of this paper is to incorporate online social interaction features in the detection of physical events. We believe that online social interaction reflect important signals among the participants on the "social affinity" of two photos, thereby...[Show more]

dc.contributor.authorWang, Yanxiang
dc.contributor.authorSundaram, Hari
dc.contributor.authorXie, Lexing
dc.coverage.spatialNara Japan
dc.date.accessioned2015-12-10T23:17:44Z
dc.date.createdOctober 29-November 2 2012
dc.identifier.isbn9781450310895
dc.identifier.urihttp://hdl.handle.net/1885/65335
dc.description.abstractThis paper focuses on detecting social, physical-world events from photos posted on social media sites. The problem is important: cheap media capture devices have significantly increased the number of photos shared on these sites. The main contribution of this paper is to incorporate online social interaction features in the detection of physical events. We believe that online social interaction reflect important signals among the participants on the "social affinity" of two photos, thereby helping event detection. We compute social affinity via a random-walk on a social interaction graph to determine similarity between two photos on the graph. We train a support vector machine classifier to combine the social affinity between photos and photo-centric metadata including time, location, tags and description. Incremental clustering is then used to group photos to event clusters. We have very good results on two large scale real-world datasets: Upcoming and MediaEval. We show an improvement between 0.06-0.10 in F1 on these datasets.
dc.publisherAssociation for Computing Machinery Inc (ACM)
dc.relation.ispartofseriesACM International Conference on Multimedia 2012
dc.sourceMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
dc.subjectKeywords: Data sets; Event detection; Incremental clustering; Interaction graphs; Media capture; Real-world datasets; Similarity metrics; Social events; Social interactions; Social media; Metadata; Social networking (online); Social sciences; Image retrieval event detection; similarity metric; social media
dc.titleSocial Event Detection with Interaction Graph Modeling
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2012
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.ariespublicationu4334215xPUB1090
local.type.statusPublished Version
local.contributor.affiliationWang, Yanxiang, College of Engineering and Computer Science, ANU
local.contributor.affiliationSundaram, Hari, Arizona State University
local.contributor.affiliationXie, Lexing, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage4
local.identifier.doi10.1145/2393347.2396332
local.identifier.absseo890301 - Electronic Information Storage and Retrieval Services
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2016-02-24T10:57:25Z
local.identifier.scopusID2-s2.0-84871381737
CollectionsANU Research Publications

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