Automating the Detection of Linguistic Intergroup Bias Through Computerized Language Analysis.
Linguistic bias is the differential use of abstraction, or other linguistic mechanisms, for the same behavior by members of different groups. Abstraction is defined by the Linguistic Category Model (LCM), which defines a continuum of words from concrete to abstract. Linguistic Intergroup Bias (LIB)...
| Publicado en: | Journal of Language & Social Psychology Vol. 44; no. 3/4; pp. 343 - 367 |
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| Autores principales: | , |
| Formato: | Artículo |
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Sage Publications Inc.
Jun-Sep2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=184747660&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 184747660 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 0261927X JLS jtl: Journal of Language & Social Psychology issn: 0261927X maglogo: Y pubinfo: dt: Jun-Sep2025 vid: 44 iid: 3/4 pid: 344 pub: Sage Publications Inc. artinfo: ui: 184747660 10.1177/0261927X251318887 ppf: 343 ppct: 24 formats: tig: atl: Automating the Detection of Linguistic Intergroup Bias Through Computerized Language Analysis. aug: au: Collins, Katherine A. Boyd, Ryan L. affil: 7235University of Saskatchewan, Saskatoon, SK, Canada 12335University of Texas at Dallas, Richardson, TX, USA su: Abstraction (Computer science) Sentiment analysis Computer programming Linguistic models Discriminatory language Implicit attitudes Ingroups (Social groups) Computational linguistics sug: subj: Abstraction (Computer science) Sentiment analysis Computer programming Linguistic models Discriminatory language Implicit attitudes Ingroups (Social groups) Computational linguistics keyword: biased language implicit bias language linguistic category model linguistic intergroup bias LIWC natural language processing social bias text analysis ab: Linguistic bias is the differential use of abstraction, or other linguistic mechanisms, for the same behavior by members of different groups. Abstraction is defined by the Linguistic Category Model (LCM), which defines a continuum of words from concrete to abstract. Linguistic Intergroup Bias (LIB) characterizes the tendency for people to use abstract words for undesirable outgroup and desirable ingroup behavior and concrete words for desirable outgroup and undesirable ingroup behavior. Thus, by examining abstraction in a text, we can understand the implicit attitudes of the author. Yet, research is currently stifled by the time-consuming and resource-intensive method of manual coding. In this study, we aim to develop an automated method to code for LIB. We compiled various techniques, including forms of sentence tokenization, sentiment analysis, and abstraction coding. All methods provided scores that were a good approximation of manually coded scores, which is promising and suggests that more complex methods for LIB coding may be unnecessary. We recommend automated approaches using CoreNLP sentiment analysis and LCM Dictionary abstraction coding. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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