Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques

Abstract

The motives and the causes behind the evolvement of the feminist thought have been in the spotlight for many researchers. This study aims to explore the evolution of the driving forces of the feminist thought using text mining and clustering techniques. To do this, first, 443 relevant literary works published in the progressive time span of three waves of feminism are explored through bag of words method. Then, to address the wide span of topics within the third wave, hierarchical clustering is used. Finally, sentiment analysis is implemented to gain insight on the emotional trends within three successive waves. Results reveal an increasing emphasis on collectivism and globalization.