Evolvement and use of stigmatized expressions in computer-mediated communication.
Published In: Journal of Asian Pacific Communication (John Benjamins Publishing Co.), 2024, v. 34, n. 2. P. 180 1 of 3
Database: Communication Source 2 of 3
Authored By: Geng, Wenwen 3 of 3
Abstract
A stigmatized expression is featured by its potentially discrediting attributes unwanted by community members. It is heavily context-dependent, especially in computer-mediated communication (CMC), which is text-based and features abbreviations, acronyms, and creative use of punctuation. The paper discusses the perception, judgment, and use of stigmatized expressions from the socio-cognitive approach (SCA) perspective. Our theory- and data-based analysis leads to the following conclusions. First, stigmatized expressions are considered pervasive and generally detrimental, thus worthy of continuous attention. Second, their emergence and recognition arise from the mutual effort of societal and individual factors, making them dynamic, ambiguous, context-dependent, and culture-specific. Third, the mechanism of generating stigmatized expression turns out to be spiral, while the circulation seems scarcely affected by its divergent interpretations. The sociocultural context serves as a trigger and an outcome in that it facilitates the processing of stigmatized expressions and is simultaneously modified. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Asian Pacific Communication (John Benjamins Publishing Co.). 2024/07, Vol. 34, Issue 2, p180
- Document Type:Article
- Subject Area:Communication and Mass Media
- Publication Date:2024
- ISSN:0957-6851
- DOI:10.1075/japc.00111.gen
- Accession Number:181232484
- Copyright Statement:Copyright of Journal of Asian Pacific Communication (John Benjamins Publishing Co.) is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.