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7 - ELF, Language Change, and Social Networks

Evidence from Real-Time Social Media Data

from Part II - Zooming in on ELF

Published online by Cambridge University Press:  17 December 2020

By
Mikko Laitinen  and
Jonas Lundberg
Edited by
Anna Mauranen  and
Svetlana Vetchinnikova
Anna Mauranen
Affiliation:
University of Helsinki
Svetlana Vetchinnikova
Affiliation:
University of Helsinki
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Summary

This article extends ELF studies towards variationist and computational sociolinguistics. It uses social network theory to explore how ELF is embedded in the social structures in which it is used, and it explores the size and nature of social networks in ELF. The empirical part investigates whether multilingual and often mobile ELF users have larger networks and more weak ties than others, and if they therefore could be more likely to act as innovators or early adopters of change than the other speaker groups. Our empirical material consists of real-time social media data from Twitter. The results show that, statistically speaking, social embedding of ELF creates conditions that favour change. ELF users have larger networks and more weak ties than the other groups examined here. With regard to methods, social embedding needs to be taken into account in future studies, and we illustrate that variationist and computational sociolinguistics offers a useful theoretical and methodological toolbox for this task.

Keywords

social embeddingsocial networksbig dataTwitter
Type
Chapter
Information
Language Change
The Impact of English as a Lingua Franca
 , pp. 179 - 204
Publisher: Cambridge University Press
Print publication year: 2020

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References

Bamman, David, Eisenstein, Jacob & Schnoebelen, Tyler. 2014. Gender identity and lexical variation in social media. Journal of Sociolinguistics 18, 135–160.CrossRefGoogle Scholar
Barbaresi, Adrian. 2016. Collection and indexation of Tweets with a geographical focus. Tenth International Conference on Language Resources and Evaluation (LREC 2016), May 2016. Proceedings of the 4th Workshop on Challenges in the Management of Large Corpora (CMLC), (2016), 24–27. <hal-01323274>>Google Scholar
Bergs, Alexander. 2005. Social Networks and Historical Sociolinguistics: Studies in Morphosyntactic Variation in the Paston Letters 1421–1503. Berlin & New York: Mouton de Gruyter.CrossRefGoogle Scholar
Blake, Norman. Introduction. 1992. In Blake, Norman (ed.), The Cambridge History of the English Language, Vol. II, 1066–1476, 1–22. Cambridge: Cambridge University Press.Google Scholar
Boyd, Danah & Crawford, Kate. 2012. Critical questions for big data. Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society 15(5), 662–679. doi: 10.1080/1369118X.2012.678878.CrossRefGoogle Scholar
Burger, John D., Henderson, John, Kim, George & Zarrella, Guido. 2011. Discriminating gender on Twitter. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 1301–1309. Stroudsburg, PA: Association for Computational Linguistics. www.aclweb.org/anthology/D11-1120.Google Scholar
Cheshire, Jenny, Kerswill, Paul, Fox, Sue & Torgersen, Eivind. 2011. Contact, the feature pool and the speech community: The emergence of Multicultural London English. Journal of Sociolinguistics 15(2), 151–196.Google Scholar
Coats, Steven. 2015. Non-standard lexical and grammatical resources in Finland Twitter English. A paper presented at Poznan Linguistics Meeting, 19 September 2015, Poznan, Poland. http://cc.oulu.fi/~scoats/poznan1handout.pdf (22.1.2018).Google Scholar
Coats, Steven. 2016. Grammatical frequencies and gender in Nordic Twitter Englishes. In Fišer, Darja and Beißwenger, Michael (eds.), Proceedings of the 4th Conference on CMC and Social Media Corpora for the Humanities, 12–16. Ljubljana: University of Ljubljana Academic Publishing.Google Scholar
Coats, Steven. 2017a. European language ecology and bilingualism with English on Twitter. In Wigham, Ciara & Stemle, Egon (eds.), Proceedings of the 5th Conference on CMC and Social Media Corpora for the Humanities, 35–38. Bozen/Bolzano: Eurac Research.Google Scholar
Coats, Steven. 2017b. Gender and lexical type frequencies in Finland Twitter English. In Hiltunen, Turo, McVeigh, Joe & Säily, Tanja (eds.), Studies in Variation, Contacts and Change in English 19: Big and Rich Data in English Corpus Linguistics: Methods and Explorations. Helsinki: VARIENG. www.helsinki.fi/varieng/series/volumes/19/coats/.Google Scholar
Dunbar, Robin. 1992. Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 22(6), 469–493.Google Scholar
Jacob, Eisenstein, O’Connor, Brendan, Smith, Noah A. & Xing, Eric P.. 2014. Diffusion of lexical change in social media. PLoS ONE 9(11), e113114. doi: 10.1371/journal.pone.0113114.Google Scholar
EJES. 2000. European Journal of English Studies 4(3).Google Scholar
Fitzmaurice, Susan. 2000. The spectator, the politics of social networks, and language standardization in eighteenth century England. In Wright, Laura (ed.), The Development of Standard English 1300–1800: Theories, Descriptions, Conflicts, 195–218. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Gonçalves, Bruno, Loureiro-Porto, Lucía, Ramasco, José & Sánchez, David. 2018. Mapping the Americanization of English in space and time. PLoS ONE 13(5), e0197741. https://doi.org/10.1371/journal.pone.0197741.Google Scholar
Graham, Mark, Hale, Scott A. & Gaffney, Devin. 2013. Where in the world are you? Geolocation and language identification in Twitter. The Professional Geographer 66, 568–578. doi: 10.1080/00330124.2014.907699.CrossRefGoogle Scholar
Granovetter, Mark. 1973. The strength of weak ties. American Journal of Sociology 78(6), 1360–1380.Google Scholar
Granovetter, Mark. 1983. The strength of weak ties: A network theory revisited. Sociological Theory 1, 201–233.CrossRefGoogle Scholar
Hiltunen, Turo, McVeigh, Joe & Säily, Tanja. 2017. How to turn linguistic data into evidence? In Hiltunen, Turo, McVeigh, Joe & Säily, Tanja (eds.), Big and Rich Data in English Corpus Linguistics: Methods and Explorations (Studies in Variation, Contacts and Change in English 1). Helsinki: VARIENG. www.helsinki.fi/varieng/series/volumes/19/.Google Scholar
Huang, Yuan, Guo, Diansheng, Kasakoff, Alice & Grieve, Jack. 2016. Understanding US regional linguistic variation with Twitter data analysis. Computers, Environment and Urban Systems 59, 244–255. doi: 10.1016/j.compenvurbsys.2015.12.003.CrossRefGoogle Scholar
Kirschenbaum, Matthew G. 2010. What is digital humanities and what’s it doing in English departments? ADA Bulletin 150, 55–61. doi: 10:1632/ade.150.55.Google Scholar
Krishnamurthy, Balachander, Gill, Phillipa & Arlitt, Martin. 2008. A few chirps about Twitter. In Faloutsos, Christos, Karagiannis, Thomas & Rodriguez, Pablo (eds.), Proceedings of the First Workshop on Online Social Networks (WOSN ’08), 19–24. New York: ACM. doi: 10.1145/1397735.1397741.Google Scholar
Laitinen, Mikko. 2016. Ongoing changes in English modals: On the developments in ELF. In Timofeeva, Olga, Chevalier, Sarah, Gardner, Anne-Christine & Honkapohja, Alpo (eds.), New Approaches in English Linguistics: Building Bridges, (Studies in Language Companion Series), 175–196. Amsterdam: John Benjamins. doi: 10.1075/slcs.177.07lai.Google Scholar
Laitinen, Mikko, Lundberg, Jonas, Levin, Magnus & Martins, Rafael. 2018. The Nordic tweet stream: A dynamic real-time monitor corpus of big and rich language data. Proc. of Digital Humanities in the Nordic Countries 3rd Conference, Helsinki, Finland, March 7–9, 2018. CEUR-WS.org/Vol-2084/short10.pdf.Google Scholar
Laitinen, Mikko, Lundberg, Jonas, Levin, Magnus & Lakaw, Alexander. 2017a. Utilizing multilingual language data in (nearly) real time: the case of the Nordic Tweet Stream. Journal of Universal Computer Science 23 (11), 1038–1056.Google Scholar
Laitinen, Mikko, Lundberg, Jonas, Levin, Magnus & Lakaw, Alexander. 2017b. Revisiting weak ties: using present-day social media data in variationist studies. In Säily, Tanja, Palander-Collin, Minna, Nurmi, Arja & Auer, Anita (eds.), Exploring Future Paths for Historical Sociolinguistics, 303–325. Amsterdam: John Benjamins. doi: 10.1075/ahs.7.12lai.CrossRefGoogle Scholar
Fabio, Lamanna, Lenormand, Maxime, Salas-Olmedo, María Henar, Romanillos, Gustavo, Gonçalves, Bruno & Ramasco, José J.. 2018. Immigrant community integration in world cities. PLoS ONE 13(3), e0191612. https://doi.org/10.1371/journal.pone.0191612.Google Scholar
Leetaru, Kalev H., Wang, Shaowen, Cao, Guofeng, Padmanabhan, Anand & Shook, Eric. 2013. Mapping the global Twitter heartbeat: The geography of Twitter. First Monday 18(5). http://firstmonday.org/ojs/index.php/fm/article/view/4366/3654.Google Scholar
Lundberg, Jones, Nordqvist, Jonas & Matosevic, Antonio. 2018. On-the-fly detection of autogenerated Tweets, arXiv preprint.Google Scholar
Lundberg, Jonas, Nordqvist, Jonas & Laitinen, Mikko. 2019. Towards a language independent Twitter bot detector. Proceedings of the Digital Humanities in the Nordic Region (DHN2019), University of Copenhagen, March 6–9, 2019.Google Scholar
Mauranen, Anna. 2018. Conceptualising ELF. In Jenkins, Jennifer, Baker, Will & Dewey, Martin (eds.), The Routledge Handbook of English as a Lingua Franca. London: Routledge.Google Scholar
Mauranen, Anna. 2012. Exploring ELF: Academic English Shaped by Non-Native Speakers. Cambridge: Cambridge University Press.Google Scholar
McCarty, Christopher, Peter, Killworth, Russell Bernard, H., Johnsen, Eugene & Shelley, Gene. 2001. Comparing two methods for estimating network size. Human Organization 60(1), 28–39.Google Scholar
Milroy, James. 1992. Linguistic Variation and Change. On the Historical Sociolinguistics of English. Oxford: Blackwell.Google Scholar
Milroy, Lesley. 2004. Social networks. In Chambers, J. K., Trudgill, Peter & Schilling-Estes, Natalie (eds.), The Handbook of Language Variation and Change, 549–570. Oxford: Blackwell.Google Scholar
Milroy, James & Milroy, Lesley. 1985. Linguistic change, social network and speaker innovation. Journal of Linguistics 21, 339–384. doi: 10.1017/S0022226700010306.CrossRefGoogle Scholar
Rao, Delip, Yarowsky, David, Shreevats, Abhishek & Gupta, Manaswi. 2010. Classifying latent user attributes in Twitter. Proceedings of the 2nd International Workshop on Search and Mining User-Generated Contents, 37–44. New York: Association for Computing Machinery. doi: 10.1145/1871985.1871993.CrossRefGoogle Scholar
Raumolin-Brunberg, Helena. 1998. Social factors and pronominal change in the seventeenth century: The civil-war effect? In Fisiak, Jacek & Krygier, Marcin (eds.), Advances in English Historical Linguistics, 361–388. Berlin: Mouton de Gruyter.Google Scholar
Sairio, Anni. 2009. Language and Letters of the Bluestocking Network: Sociolinguistic Issues in Eighteenth-century Epistolary English (Mémoires de la Société Néophilologique de Helsinki LXXV). Helsinki: Société Néophilologique.Google Scholar
Scheffler, Tatjana. 2014. A German Twitter Snapshot. Proceedings of LREC, (2014), 2284–2289.Google Scholar
Weinreich, Uriel, Labov, William & Herzog, Marvin. 1968. Empirical foundations for a theory of language change. In Lehmann, Winfred P. & Malkiel, Yakov (eds.), Directions for Historical Linguistics, 95–188. Austin: University of Texas Press.Google Scholar

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