DocumentCode
630128
Title
Sociolect-based community detection
Author
Reynolds, W.N. ; Salter, William J. ; Farber, Robert M. ; Corley, Courtney ; Dowling, Chase P. ; Beeman, William O. ; Smith-Lovin, Lynn ; Joon Nak Choih
Author_Institution
Least Squares Software, Inc., Albuquerque, NM, USA
fYear
2013
fDate
4-7 June 2013
Firstpage
221
Lastpage
226
Abstract
“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.
Keywords
information retrieval; social networking (online); vocabulary; Sociolect-based community detection; Twitter data retrieval; edge counts; expert-identified sociolects; large social media data corpora; network structure; network substructure; network-analysis methods; node populations; social subgroups; vocabularies; Artificial neural networks; Communities; Media; Nickel; Sociology; Statistics; Twitter; assortativity; community detection; network analysis; social media analysis; sociolect;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligence and Security Informatics (ISI), 2013 IEEE International Conference on
Conference_Location
Seattle, WA
Print_ISBN
978-1-4673-6214-6
Type
conf
DOI
10.1109/ISI.2013.6578823
Filename
6578823
Link To Document