Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/61104

Sociolect-based community detection

Authors Reynolds, William
Salter, William
Farber, Robert
Corley, Courtney
Dowling, Chase
Beeman, William
Smith-Lovin, Lynn
Choi, Joon Nak View this author's profile
Issue Date 2013
Source IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics , 4-7 June 2013, , p. 221-226
Summary 'Sociolects' are specialized vocabularies used by social subgroups defined by common interests or origins. We applied methods to retrieve large quantities of Twitter data based on expert-identified sociolects and then applied and developed network-analysis methods to relate sociolect use to network (sub-) structure. We show that novel methods including consideration of node populations, as well as edge counts, provide substantially enhanced performance compared to standard assortativity. We explain these methods, show their utility in analyzing large corpora of social media data, and d iscuss their further extensions and potential applications. © 2013 IEEE.
Subjects
ISBN 9781467362115
978-1-4673-6213-9
978-1-4673-6214-6
Language English
Format Conference paper
Access View full-text via DOI
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View full-text via Web of Science
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