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Chapter 4. Patterns of intra-individual variation in a Swiss WhatsApp corpus

Analysing real-time change and long-term accommodation
  • Samuel Felder
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Corpus Approaches to Social Media
This chapter is in the book Corpus Approaches to Social Media

Abstract

Analysing written data from a large WhatsApp corpus, which was collected in Switzerland in 2014, this study examines how individuals may change their linguistic behaviour over time and how such changes are connected to the language use of the interlocutor. Therefore, this is one of the very first studies analysing intra-individual real-time change and long-term accommodation processes in written digital data. Focussing on WhatsApp chats that are primarily written in Swiss German, evidence for the possibility of rapid changes within the language use of individuals on several linguistic levels is presented: dialectal variation, phoneme-grapheme correspondence, punctuation, lexis, and use of emojis/emoticons. Furthermore, based on multiple examples from the corpus, several different types of long-term accommodation processes in two-person chats are distinguished.

Abstract

Analysing written data from a large WhatsApp corpus, which was collected in Switzerland in 2014, this study examines how individuals may change their linguistic behaviour over time and how such changes are connected to the language use of the interlocutor. Therefore, this is one of the very first studies analysing intra-individual real-time change and long-term accommodation processes in written digital data. Focussing on WhatsApp chats that are primarily written in Swiss German, evidence for the possibility of rapid changes within the language use of individuals on several linguistic levels is presented: dialectal variation, phoneme-grapheme correspondence, punctuation, lexis, and use of emojis/emoticons. Furthermore, based on multiple examples from the corpus, several different types of long-term accommodation processes in two-person chats are distinguished.

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Introduction. The expanding landscape of corpus-based studies of social media language 1
  4. Part 1. Using corpus methods to investigate communities on social media
  5. Chapter 1. Towards a digital sociolinguistics 15
  6. Chapter 2. The control and censorship of linguistic resources in an online Community of Practice 41
  7. Chapter 3. Talking about women 63
  8. Part II. Linguistic variation in short social media texts
  9. Chapter 4. Patterns of intra-individual variation in a Swiss WhatsApp corpus 89
  10. Chapter 5. Using lengthwise scaling to compare feature frequencies across text lengths on Reddit 111
  11. Chapter 6. Double trouble 131
  12. Part III. The role of images
  13. Chapter 7. Constructing corpora from images and text 149
  14. Chapter 8. Working with images and emoji in the 🦆 Dukki Facebook Corpus 175
  15. Part IV. Discussion
  16. Chapter 9. New developments in corpus approaches to social media 199
  17. Index 209
https://doi.org/10.1075/scl.98.04fel

Chapters in this book

  1. Prelim pages i
  2. Table of contents v
  3. Introduction. The expanding landscape of corpus-based studies of social media language 1
  4. Part 1. Using corpus methods to investigate communities on social media
  5. Chapter 1. Towards a digital sociolinguistics 15
  6. Chapter 2. The control and censorship of linguistic resources in an online Community of Practice 41
  7. Chapter 3. Talking about women 63
  8. Part II. Linguistic variation in short social media texts
  9. Chapter 4. Patterns of intra-individual variation in a Swiss WhatsApp corpus 89
  10. Chapter 5. Using lengthwise scaling to compare feature frequencies across text lengths on Reddit 111
  11. Chapter 6. Double trouble 131
  12. Part III. The role of images
  13. Chapter 7. Constructing corpora from images and text 149
  14. Chapter 8. Working with images and emoji in the 🦆 Dukki Facebook Corpus 175
  15. Part IV. Discussion
  16. Chapter 9. New developments in corpus approaches to social media 199
  17. Index 209
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