How do we study misogyny in the digital age? A systematic literature review using a computational linguistic approach
Humanities and Social Sciences Communications, ISSN: 2662-9992, Vol: 11, Issue: 1
2024
- 6Citations
- 31Captures
- 1Mentions
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Review Description
Nowadays, despite centuries of striving for equality, women still face higher levels of discrimination compared to men in nearly every aspect of life. Recently, this systemic inequality has manifested in cyberspace through the proliferation of abusive content that is even more aggressive than what one would expect in the 21st century. Various research disciplines are now attempting to characterise this new manifestation of misogyny. The endeavour to comprehend this phenomenon has resulted in a significant increase in publications from several fields, including Social Sciences, Arts and Humanities, Psychology, and Computer Science. This paper presents a systematic review of multidisciplinary research on misogyny from the years 1990 to 2022, encompassing a total of 2830 articles retrieved from the Scopus database as of December 31, 2022. The literature is thoroughly analysed using three approaches: bibliometric analysis, topic detection, and qualitative analysis of the documents. The findings suggest that the analysis of online misogyny has been the primary driver behind the exponential growth in publications in this field. Additionally, the results of the topic analysis and topic interaction reveal a limited connection between the areas of knowledge that are necessary to fully grasp this complex phenomenon.
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