Unwanted advances in higher education:Uncovering sexual harassment experiences in academia with text mining
作者：
Highlights：
• This paper provides a dataset containing more than 2000 sexual harassment experiences in academia.
• A computational approach was utilized to overcome the time–‐consuming and labor–‐intensive process of traditional methods.
• This research detected, analyzed, and categorized the topics of the sexual harassment experiences in academia.
• Results are beneficial to researchers interested in further investigation of this paper's dataset.
• Findings have utility for policymakers in improving existing policies to create a safe and supportive environment in academia.
摘要
•This paper provides a dataset containing more than 2000 sexual harassment experiences in academia.•A computational approach was utilized to overcome the time–‐consuming and labor–‐intensive process of traditional methods.•This research detected, analyzed, and categorized the topics of the sexual harassment experiences in academia.•Results are beneficial to researchers interested in further investigation of this paper's dataset.•Findings have utility for policymakers in improving existing policies to create a safe and supportive environment in academia.
论文关键词：Sexual harassment,Web survey,Text mining,Academia,Topic modeling
论文评审过程：Received 2 August 2019, Revised 3 November 2019, Accepted 6 November 2019, Available online 10 December 2019, Version of Record 10 December 2019.
论文官网地址：https://doi.org/10.1016/j.ipm.2019.102167
