Detecting online expressional anomie and its evolutions in social media
ISSN: 0264-0473
Article publication date: 6 September 2019
Issue publication date: 6 September 2019
Abstract
Purpose
Expressional anomie (e.g. obscene words) can hinder communications and even obstruct improvements of national literacy. Meanwhile, the borderless and rapid transmission of the internet has exacerbated the influences. Hence, the purpose of this paper is detecting online anomic expression automatically and analyzing dynamic evolution processes of expressional anomie, so as to reveal multidimensional status of expressional anomie.
Design/methodology/approach
This paper conducted expressional anomie analysis via fine-grained microblog mining. Specifically, anomic microblogs and their anomic types were identified via a supervised classification method. Then, the evolutions of expressional anomie were analyzed, and impacts of users’ characteristics on the evolution process were mined. Finally, expressional anomie characteristics and evolution trends were obtained.
Findings
Empirical results on microblogs indicate that more effective and diversified measures need to be used to address the current large-scale anomie in expression. Moreover, measures should be tailored to individuals and local conditions.
Originality/value
To the best of the authors’ knowledge, it is the first research to mine evolutions of expressional anomie automatically in social media. It may discover more continuous and universal rules of expressional anomie, so as to optimize the online expression environment.
Keywords
Acknowledgements
This work is supported by the National Social Science Fund Project (No. 14BXW029) and the National Social Science Fund Project (No. 19CTQ031).
Citation
Zhou, Q. and Jing, M. (2019), "Detecting online expressional anomie and its evolutions in social media", The Electronic Library, Vol. 37 No. 4, pp. 703-721. https://doi.org/10.1108/EL-02-2019-0021
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited