Perspectives on virtual intercultural communication in the Irish-based technology sector: A corpus-based analysis of linguistic clusters.
Published In: International Journal of Corpus Linguistics, 2024, v. 29, n. 3. P. 417 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Flanagan, Gail; Farr, Fiona 3 of 3
Abstract
This mixed-methods study investigates English-medium oral online intercultural communication within the Irish-based international technology sector. The initial phase of the research consisted of a survey investigating participants' (N = 113) experiences of virtual communication. Following the survey, to linguistically investigate such interactions, the International Virtual Team Corpus (IVT Corpus) was created. This corpus consists of approximately 80,000 words of transcribed speech gathered from 30 web-based recordings of meetings, which include both Irish and international colleagues speaking in English. This paper reports on some of the relevant quantitative and qualitative survey results, uncovering both preconceptions and embodied experiences of international virtual meetings. Following this, it presents corpus-based results of significant frequent and keyword clusters that provide a window into the discourse patterns of international virtual team meetings in this sector. Some tentative implications and applications for work-based virtual communication are explored in the closing discussion. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Corpus Linguistics. 2024/07, Vol. 29, Issue 3, p417
- Document Type:Article
- Subject Area:Communication and Mass Media
- Publication Date:2024
- ISSN:1384-6655
- DOI:10.1075/ijcl.24062.fla
- Accession Number:180922157
- Copyright Statement:Copyright of International Journal of Corpus Linguistics 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.