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Exploring the surveillance technology discourse: a bibliometric analysis and topic modeling approach

Authors :
Kalle Karlsson
Fisnik Dalipi
Source :
Frontiers in Artificial Intelligence, Vol 7 (2024)
Publication Year :
2024
Publisher :
Frontiers Media S.A., 2024.

Abstract

The prevention of crime is a multifaceted challenge with legal, political, and cultural implications. Surveillance technologies play a crucial role in assisting law enforcement and other relevant parties in this mission. Drones, cameras, and wiretaps are examples of such devices. As their use increases, it becomes essential to address related challenges involving various stakeholders and consider cultural, political, and legal aspects. The objective of this study was to analyze the impact of surveillance technologies and identify commonalities and differences in perspectives among social media users and researchers. Data extraction was performed from two platforms: Scopus (for academic research papers) and platform X (formerly known as Twitter). The dataset included 88,989 tweets and 4,874 research papers. Topic modeling, an unsupervised machine learning approach, was applied to analyze the content. The research results revealed that privacy received little attention across the datasets, indicating its relatively low prominence. The military applications and their usage have been documented in academic research articles as well as tweets. Based on the empirical evidence, it seems that contemporary surveillance technology may be accurately described as possessing a bi-directional nature, including both sousveillance and surveillance, which aligns with Deleuzian ideas on the Panopticon. The study’s findings also indicate that there was a greater level of interest in actual applications of surveillance technologies as opposed to more abstract concepts like ethics and privacy.

Details

Language :
English
ISSN :
26248212
Volume :
7
Database :
Directory of Open Access Journals
Journal :
Frontiers in Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
edsdoj.21269ba35148490f87eb8ac378bb056e
Document Type :
article
Full Text :
https://doi.org/10.3389/frai.2024.1406361