NDLI: Sociolect-based community detection

Content Provider	IEEE Xplore Digital Library
Author	Reynolds, W.N. Salter, W.J. Farber, R.M. Corley, C. Dowling, C.P. Beeman, W.O. Smith-Lovin, L. Joon Nak Choih
Copyright Year	2013
Description	Author affiliation: BlackDog Endeavors, LLC, Gig Harbor, WA, USA (Farber, R.M.) \|\| Least Squares Software, Inc., Albuquerque, NM, USA (Reynolds, W.N.) \|\| Dept. of Manage., Hong Kong Univ. of Sci. & Technol., Hong Kong, China (Joon Nak Choih) \|\| Dept. of Sociology, Duke Univ., Durham, NC, USA (Smith-Lovin, L.) \|\| Dept. of Anthropology, Univ. of Minnesota, Minneapolis, MN, USA (Beeman, W.O.) \|\| Dept. of Energy, Pacific Northwest Nat. Labs., Richland, WA, USA (Corley, C.; Dowling, C.P.) \|\| Strategic Solutions Consulting, MA, USA (Salter, W.J.)
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.
Sponsorship	IEEE Intelligent Transp. Syst. Soc.
Starting Page	221
Ending Page	226
File Size	155279
Page Count	6
File Format	PDF
ISBN	9781467362146
e-ISBN	9781467362139
DOI	10.1109/ISI.2013.6578823
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	sociolect Communities Sociology Artificial neural networks Media assortativity Twitter Nickel network analysis Statistics community detection social media analysis
Content Type	Text
Resource Type	Article

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