Vocabulary Circulation in French-speaking Video Game Streaming on Twitch.tv: How to Model and Make Interpretable the Intersection between Network Analysis and NLP?

Video game live-streaming is a form of performance that continues to grow in popularity and that exerts considerable influence not only on the ways in which video game culture is consumed, but also on the forms of participation in that culture, particularly through the various forms of “secondary play” (Delbouille 2018). While it uses video game as a medium, this cultural practice also relies heavily on the production of spoken and written discourses. On the one hand, the streamers’ utterances federate their communities through the construction of an idiolect (using slogans, running gags, catchphrases), more or less fed and crossed by other lexical fields (coming from the games played or the streaming platform, in particular). On the other hand, the chat’s written interventions repeat, appropriate and make these language elements evolve.
This presentation proposes to study the circulation of vocabulary between several communities of French-speaking streaming viewers on Twitch.tv, by combining (following the model of the work of Bouveyron, Latouche & Zreik, 2016) network analysis and natural language processing of messages posted in the chat. Two corpora of chatlogs will be precisely studied: the chats of the top 15 French-language streaming channels that aired during the r/place event (aka “PixelWar”), the week of April 1 to 5, 2022, and the chats of the top 27 French-language streaming channels that aired during the week of April 11 to 17, 2022.
By exploiting these corpora with the help of natural language processing tools, this paper will aim at answering two questions in parallel. On the one hand, we will try to determine to what extent communities defined by the network analysis can also be identified by the sharing of the same vocabulary: how do discursive communities form on Twitch.tv? Around what type of vocabulary do they form or break down? What are the elements that determine the appearance of one lexical field rather than another? What is the share of influence of the streamer or of the game played, and that of the platform Twitch.tv?
On the other hand, we will try to answer a more methodological question related to digital humanities (which can to some extent be transposed to the topic of character networks): how to represent such a large number of superimposed data in an interpretable and efficient model? The representation will require a semiotic reflection, since it will be necessary to make visible the exchanges and evolution of the vocabulary used by the audience in addition to the particularly dense network of actors. Through this case study, we thus wish to shed light on the modes of operation of linguistic exchanges specific to video game streaming on Twitch.tv, but also to propose methods facilitating the study of the circulation of vocabulary between multiple entities.