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

Dong-Phuong Nguyen

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    193 Downloads (Pure)

    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.
    @phdthesis{653bf4f833ae424fbf55031cf040f013,
    title = "Text as social and cultural data: a computational perspective on variation in text",
    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.",
    keywords = "IR-103746, METIS-321634",
    author = "Dong-Phuong Nguyen",
    note = "SIKS dissertation series no. 2017-09",
    year = "2017",
    month = "3",
    day = "10",
    doi = "10.3990/1.9789036543002",
    language = "English",
    isbn = "978-90-365-4300-2",
    publisher = "Universiteit Twente",
    school = "University of Twente",

    }

    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 UT

    TY - THES

    T1 - Text as social and cultural data

    T2 - a computational perspective on variation in text

    AU - Nguyen, Dong-Phuong

    N1 - SIKS dissertation series no. 2017-09

    PY - 2017/3/10

    Y1 - 2017/3/10

    N2 - 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.

    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.

    KW - IR-103746

    KW - METIS-321634

    U2 - 10.3990/1.9789036543002

    DO - 10.3990/1.9789036543002

    M3 - PhD Thesis - Research UT, graduation UT

    SN - 978-90-365-4300-2

    PB - Universiteit Twente

    CY - Enschede

    ER -