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Chapter 6. Double trouble

Are 280-character tweets comparable to 140-character tweets?
  • Martin Eberl
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Corpus Approaches to Social Media
Ein Kapitel aus dem Buch Corpus Approaches to Social Media

Abstract

Linguistic data from social media is often discussed in the light of constraints, be it due to character limits or the putatively short attention span of users. In November 2017, Twitter eased one such constraint, increasing the maximum length of tweets from 140 to 280 characters. The present longitudinal study shows that this change has had an effect on the linguistic surface structure of tweets, especially in regard to optional syntactical and metatextual features. I discuss the origin and nature of these changes and their relation to hard constraints of social media platforms in addition to highlighting the impact on methodological aspects of future longitudinal studies of Twitter data which may cover periods both before and after the switch.

Abstract

Linguistic data from social media is often discussed in the light of constraints, be it due to character limits or the putatively short attention span of users. In November 2017, Twitter eased one such constraint, increasing the maximum length of tweets from 140 to 280 characters. The present longitudinal study shows that this change has had an effect on the linguistic surface structure of tweets, especially in regard to optional syntactical and metatextual features. I discuss the origin and nature of these changes and their relation to hard constraints of social media platforms in addition to highlighting the impact on methodological aspects of future longitudinal studies of Twitter data which may cover periods both before and after the switch.

Kapitel in diesem Buch

  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.98.06ebe

Kapitel in diesem Buch

  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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Heruntergeladen am 5.11.2025 von https://www.degruyterbrill.com/document/doi/10.1075/scl.98.06ebe/html
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