The Information ecology of social media and online communities

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dc.contributor.authorFinin, Tim
dc.contributor.authorJoshi, Anupam
dc.contributor.authorKolari, Pranam
dc.contributor.authorJava, Akshay
dc.contributor.authorKale, Anubhav
dc.contributor.authorKarandikar, Amit
dc.date.accessioned2018-11-29T17:17:49Z
dc.date.available2018-11-29T17:17:49Z
dc.date.issued2008-09-01
dc.description.abstractSocial media systems such as weblogs, photo- and linksharing sites, wikis and on-line forums are currently thought to produce up to one third of new Web content. One thing that sets these “Web 2.0” sites apart from traditional Web pages and resources is that they are intertwined with other forms of networked data. Their standard hyperlinks are enriched by social networks, comments, trackbacks, advertisements, tags, RDF data and metadata. We describe recent work on building systems that use models of the Blogosphere to recognize spam blogs, find opinions on topics, identify communities of interest, derive trust relationships, and detect influential bloggers.en
dc.description.sponsorshipWe thank Dr. James Mayfield, Justin Martineau and Sandeep Balijepalli for their contributions to the work on sentiment detection. Partial support for this research was provided by the National Science Foundation (awards ITR-IIS-0325172 and NSF-ITR-IDM- 0219649) and I.B.M.en
dc.description.urihttps://www.aaai.org/ojs/index.php/aimagazine/article/view/2158en
dc.format.extent12 pagesen
dc.genrejournal articles preprintsen
dc.identifierdoi:10.13016/M2HH6C95R
dc.identifier.citationTim Finin, Anupam Joshi, Pranam Kolari, Akshay Java, Anubhav Kale, and Amit Karandikar, The Information ecology of social media and online communities, AI Magazine, 2008, https://www.aaai.org/ojs/index.php/aimagazine/article/view/2158en
dc.identifier.urihttp://hdl.handle.net/11603/12123
dc.language.isoenen
dc.publisherAAAIen
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectecologyen
dc.subjectsocial mediaen
dc.subjectonline communitiesen
dc.subjectspamen
dc.subjectUMBC Ebiquity Research Groupen
dc.titleThe Information ecology of social media and online communitiesen
dc.typeTexten

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