A Systematic Literature Review of Sexual Harassment Studies with Text Mining

Amir Karami, Melek Yildiz Spinel, C. Nicole White, Kayla Ford and Suzanne Swan
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Amir Karami: School of Information Science, University of South Carolina, Columbia, SC 29208, USA
Melek Yildiz Spinel: Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
C. Nicole White: Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
Kayla Ford: Department of Psychology, University of Arkansas, Fayetteville, AR 72701, USA
Suzanne Swan: Department of Psychology and Women’s & Gender Studies Program, University of South Carolina, Columbia, SC 29208, USA

Sustainability, 2021, vol. 13, issue 12, 1-24

Abstract: Sexual harassment has been the topic of thousands of research articles in the 20th and 21st centuries. Several review papers have been developed to synthesize the literature about sexual harassment. While traditional literature review studies provide valuable insights, these studies have some limitations including analyzing a limited number of papers, being time-consuming and labor-intensive, focusing on a few topics, and lacking temporal trend analysis. To address these limitations, this paper employs both computational and qualitative approaches to identify major research topics, explore temporal trends of sexual harassment topics over the past few decades, and point to future possible directions in sexual harassment studies. We collected 5320 research papers published between 1977 and 2020, identified and analyzed sexual harassment topics, and explored the temporal trend of topics. Our findings indicate that sexual harassment in the workplace was the most popular research theme, and sexual harassment was investigated in a wide range of spaces ranging from school to military settings. Our analysis shows that 62.5% of the topics having a significant trend had an increasing (hot) temporal trend that is expected to be studied more in the coming years. This study offers a bird’s eye view to better understand sexual harassment literature with text mining, qualitative, and temporal trend analysis methods. This research could be beneficial to researchers, educators, publishers, and policymakers by providing a broad overview of the sexual harassment field.

Keywords: sexual harassment; text mining; temporal trend analysis; topic model; literature review (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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