Fem-Scale: A Data-Driven Approach for Quantifying Degree of Individual Feminism Perspective

Abuse of women is widespread in underdeveloped nations like Bangladesh, where women are still afraid to assert their rights, and this trend persists. Even though significant changes are apparent, they have not entirely disappeared from society. On the other hand, there are some negative notions of feminism prevailing in our community. The lack of proper classification of the individual feminism perspective in relevant degrees is a significant concern while developing effective policies against this phenomenon. In this work, we develop a data-driven approach to quantify the degree of the individual feminist standpoint. We collected data from a selected crowd using survey questionnaires and analyzed the responses to segregate the participants into a Fem-Scale with five distinct classes: Sexist, Partial Sexist, Moderate, Feminist, and Radical feminist. We also validated the proposed Fem-Scale with real-life data generating an accuracy of 97.67% and highlighted the critical insights of the qualitative analysis of the collected data. To the best of the authors’ knowledge, this is the first attempt to introduce the degree of individual feminism standpoint. The proposed method can be beneficial in future research, including justifying the standpoint regarding feminism using public data from an individual’s social networking site (SNS).