Text as social and cultural data: a computational perspective on variation in text

Dong-Phuong Nguyen

Research output: ThesisPhD Thesis - Research UT, graduation UTAcademic

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Abstract

Massive digital datasets, such as social media data, are a promising source to study social and cultural phenomena. They provide the opportunity to study language use and behavior in a variety of social situations on a large scale and often with the availability of detailed contextual information. However, to fully leverage their potential for research the social sciences and the humanities, new computational approaches are needed. This dissertation explores computational approaches to text analysis for studying cultural and social phenomena and focuses on two emerging areas: computational sociolinguistics and computational folkloristics. Both areas share the recognition that variation in text is often meaningful and may provide insights into social and cultural phenomena. This dissertation develops computational approaches to analyze and model variation in text.
Original languageEnglish
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • de Jong, Franciska M.G., Supervisor
  • Bosch, A.P.J., Supervisor
  • Theune, Mariet , Co-Supervisor
Award date10 Mar 2017
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-4300-2
DOIs
Publication statusPublished - 10 Mar 2017

Fingerprint

earning a doctorate
text analysis
social situation
social studies
sociolinguistics
cultural studies
social media
social science
language

Keywords

  • IR-103746
  • METIS-321634

Cite this

Nguyen, Dong-Phuong. / Text as social and cultural data : a computational perspective on variation in text. Enschede : Universiteit Twente, 2017. 240 p.
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Text as social and cultural data : a computational perspective on variation in text. / Nguyen, Dong-Phuong.

Enschede : Universiteit Twente, 2017. 240 p.

Research output: ThesisPhD Thesis - Research UT, graduation UTAcademic

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AB - Massive digital datasets, such as social media data, are a promising source to study social and cultural phenomena. They provide the opportunity to study language use and behavior in a variety of social situations on a large scale and often with the availability of detailed contextual information. However, to fully leverage their potential for research the social sciences and the humanities, new computational approaches are needed. This dissertation explores computational approaches to text analysis for studying cultural and social phenomena and focuses on two emerging areas: computational sociolinguistics and computational folkloristics. Both areas share the recognition that variation in text is often meaningful and may provide insights into social and cultural phenomena. This dissertation develops computational approaches to analyze and model variation in text.

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