The language of conversation is just as dependent upon word choice as it is on who is taking part. Twitter provides an excellent test-bed in which to conduct experiments not only on language usage but on who is using what language with whom. To this end, we combine large scale graph analytical techniques with known socio-linguistic methods. In this article we leverage both expert curated vocabularies and naive mathematical graph analyses to determine if network behavior on Twitter corroborates with the current understanding of language usage. The results reported indicate that, based on networks constructed from user to user communication and communities identified using the Clauset- Newman greedy modularity algorithm we find that more prolific users of these curated vocabularies are concentrated in distinct network communities.
Revised: February 4, 2016 |
Published: September 1, 2013
Citation
Dowling C.P., C.D. Corley, R.M. Farber, and W. Reynolds. 2013.Jargon and Graph Modularity on Twitter. In IEEE International Conference on Intelligence and Security Informatics (ISI 2013), June 4-7, 2013, Seattle, Washington, 381-383. Piscataway, New Jersey:IEEE.PNNL-SA-94196.doi:10.1109/ISI.2013.6578833