Dr John Bryden, RHUL

Groups, words and how humans transmit language: insights in language dynamics from Twitter

Within a community, individuals tend to group together with those with which they share characteristics. At the same time, much of our characteristics and preferences are influenced by those that we interact with. These two processes create dynamics which give rise to clusters of individuals which share certain characteristics [1]. In human networks we have found evidence of such processes in the language that we use [2,3]. We have shown that on Twitter tribes of users tend to form, and the network emerging from user communication can be structured into a hierarchy of communities, and that the members of such tribes have similar word usage, and use specific words [2]. Consequently, communities can be characterised by their words. We can also show that word usage is passed on from speaker to speaker, demonstrating that language use spreads among those engaged in conversation [4] This suggests a mechanism for transmission whereby for each word someone encounters there is a chance they will use it more often. This mechanism for transmission can be used to study language patterns and evolution within populations.

References

[1] Bryden, J., Funk, S., Geard, N., Bullock, S. and Jansen, V.A.A., 2011. Stability in flux: community structure in dynamic networks. Journal of The Royal Society Interface, 8, 1031-1040. http://doi.org/10.1098/rsif.2010.0524

[2] Bryden, J., Funk, S. and Jansen, V.A.A., 2013. Word usage mirrors community structure in the online social network Twitter. EPJ Data Science, 2(1), 3. http://doi.org/10.1140/epjds15

[3] Tamburrini, N., Cinnirella, M., Jansen, V.A.A. and Bryden, J., 2015. Twitter users change word usage according to conversation-partner social identity. Social Networks, 40, pp.84-89. http://doi.org/10.1016/j.socnet.2014.07.004

[4] Bryden, J, Wright, S, and Jansen V.A.A. (2018) How humans transmit language: Horizontal transmission matches word frequencies amongst peers on Twitter. J. R. Soc. Interface. 15: 20170738. https://doi.org/10.1098/rsif.2017.0738

Keywords: language change, social networks, twitter, network homophily, alignment