“Je te RT et tu me follow back”: The influence of the oral code on French-speaking online social media
Document Type
Oral Presentation
Campus where you would like to present
SURC Ballroom C/D
Start Date
15-5-2014
End Date
15-5-2014
Keywords
Linguistics, Facebook, Twitter
Abstract
Given the omnipresence of technology and public fascination with social media, it comes as no surprise that Internet linguistics is a rapidly growing field. The language of French social media has not yet been investigated. This study examines the coexistence of written and oral codes in French language employed on Twitter and Facebook. Because French language users are notorious for their attention to quality and adherence to linguistic purity, the use of cyberlanguage has generated considerable debate in the French-speaking world. This study addresses: (1) Where does French cyberlanguage fall on a spoken, written, hybrid code continuum? (2) Which code is dominant in online social media? (3) What linguistic differences exist between Facebook and Twitter? (4) How widespread are English borrowings in French social media? To answer these questions, corpora of 2,000 Twitter postings and 500 Facebook postings were gathered. The data were analyzed according to criteria that differentiate spoken and written language established by Crystal (2001). For further analysis, specific elements of the written and oral codes were applied. In response to the first two questions, initial findings revealed that the written code is still robust, but strongly influenced by the oral code, thus creating a space for entirely novel registers (Crystal 2011). For the third question, Twitter and Facebook shared most linguistic processes, but Facebook exhibited a higher frequency of features characteristic of written register. Additionally, contrary to commonly held beliefs, English borrowings were not shown to be widespread in social media.
For his work on this project, Joseph O'Connor was nominated for the SOURCE 2014 Scholar of the Year Award.
Recommended Citation
O'Connor, Joseph, "“Je te RT et tu me follow back”: The influence of the oral code on French-speaking online social media" (2014). Symposium Of University Research and Creative Expression (SOURCE). 170.
https://digitalcommons.cwu.edu/source/2014/posters/170
Poster Number
60
Additional Mentoring Department
World Languages
“Je te RT et tu me follow back”: The influence of the oral code on French-speaking online social media
SURC Ballroom C/D
Given the omnipresence of technology and public fascination with social media, it comes as no surprise that Internet linguistics is a rapidly growing field. The language of French social media has not yet been investigated. This study examines the coexistence of written and oral codes in French language employed on Twitter and Facebook. Because French language users are notorious for their attention to quality and adherence to linguistic purity, the use of cyberlanguage has generated considerable debate in the French-speaking world. This study addresses: (1) Where does French cyberlanguage fall on a spoken, written, hybrid code continuum? (2) Which code is dominant in online social media? (3) What linguistic differences exist between Facebook and Twitter? (4) How widespread are English borrowings in French social media? To answer these questions, corpora of 2,000 Twitter postings and 500 Facebook postings were gathered. The data were analyzed according to criteria that differentiate spoken and written language established by Crystal (2001). For further analysis, specific elements of the written and oral codes were applied. In response to the first two questions, initial findings revealed that the written code is still robust, but strongly influenced by the oral code, thus creating a space for entirely novel registers (Crystal 2011). For the third question, Twitter and Facebook shared most linguistic processes, but Facebook exhibited a higher frequency of features characteristic of written register. Additionally, contrary to commonly held beliefs, English borrowings were not shown to be widespread in social media.
For his work on this project, Joseph O'Connor was nominated for the SOURCE 2014 Scholar of the Year Award.
Faculty Mentor(s)
Lefkowitz, Natalie