Abstract
Although much had changed throughout the feminist movement during the first wave (the 1800s–1960s) and second wave (1960s–1980s), with the inclusion of distinct minority groups into the idea, most of the contemporary approaches had been developed within the third wave. The purpose of this study is twofold: First, to investigate the works published during the third wave of feminism through unsupervised clustering methods. Second, to determine the driving emotional structures for each of these consequent clusters using sentiment analysis. To conduct the analyses, sizeable data is gathered using the literature published after the mid-1990s. The data is then cleaned and prepared according to the bag of words methodology before the usage of the hierarchical clustering technique. As a final step, sentiment analysis based on Plutchik’s Wheel of Emotion has been used to illustrate the magnitudes of eight distinct emotions. Results demonstrate that there are clear points of distinction between the 3 waves’ sentiment analysis and main ideas. One of the significant findings was the 3rd wave’s feminism understanding being not only about women but all types of disadvantaged minority groups. Another important finding is that the aggression level of the ideas that do not change during the 3 waves increases significantly over time. This research contributes to the literature by providing an objective framework to analyze how the feminism ideology is evolved.
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References
Annapurany, K. (2016). A prospective study of feminism waves, phases, issues and critical analysis. International Journal of Applied Research, 2(5), 424–426. ISSN Print: 2394-7500, ISSN Online: 2394-5869.
Burdett, C. (2001). Olive Schreiner and the progress of feminism evolution, gender, empire. Palgrave. isbn:978-1-349-39260-5.. https://doi.org/10.1057/9780230598973
Cobble, D. S., Gordon, L., & Henry, A. (2014). Feminism unfinished: A short, surprising history of American Women’s movements. WW Norton & Co. isbn:0871406764. https://doi.org/10.1111/j.2050-5876.2014.00812.x.
Correia, A., Filomena, T., & Lobo, V. (2018). Statistical Methods for Word Association in Text Mining, Recent Studies in Risk Analysis and Statistical Modeling. Contributions to Statistics, Springer, Cham, 375–384
David, C. (1992). An Encyclopedic Dictionary of Language and Languages. Oxford:Blackwell.
Desagulier, G. (2014). Visualizing distances in a set of near synonyms: rather, quite, fairly, and pretty. Corpus Methods for Semantics: Quantitative Studies in Polysemy and Synonymy, 145–178
Dyhouse, C. (2010). Glamour - women, history, feminism. Palgrave Macmillan. isbn:9781848134072.
Feinerer, I., Hornik, K., & Meyer, D. (2008). Text mining infrastructure in R. Journal of Statistical Software, 25(5), 1–54. https://www.jstatsoft.org/v25/i05/.
Freedman, E. B. (2002). No turning back -the history of feminism and the future of women. The Random House Publishing Group. eISBN 9780307416247.
Jacob, K., & Licona, A. C. (2005, Spring). Writing the waves: A dialogue on the tools, tactics, and tensions of feminisms and feminist practices over time and place. NWSA Journal, 17(1), 197–205, The Johns Hopkins University Press. https://www.jstor.org/stable/4317111.
Loomba, A., & Sanchez, M. E. (2016). Rethinking feminism in early modern studies gender, race, and sexuality. Routledge. isbn:9781472421753.
McNamee, P., & Mayfield, J. (2004). Character N-gram tokenization for European language text retrieval. Information Retrieval, 7(1/2), 73–97. https://doi.org/10.1023/b:inrt.0000009441.78971.be
Mohammad, S. M., & Turney, P. D. (2010). Emotions evoked by common words and phrases: Using Mechanical Turk to create an emotion lexicon. In Proceeding of workshop on computational approaches to analysis and generation of emotion in text, 26–34.
Murtagh, F., Legendre, & P. (2014). Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion?. Journal of Classification 31, 274–295
Offen, K. (1988, Autumn). Defining feminism: A comparative historical approach. The University of Chicago Press Journals, 14(1), 119–157. https://www.jstor.org/stable/3174664
Rampton, M. (2008). Four waves of feminism. Pacific Magazine, Pacific University, Oregon. https://www.pacificu.edu/magazine/four-waves-feminism
Riley, D. (1995). “Am I that name?” Feminism and the category of “women” in history. University of Minnesota Press. isbn:0816617309.
Roseneil, S. (2013). Beyond citizenship? Feminism and the transformation of belonging - citizenship, gender and diversity. Palgrave Macmillan. isbn:9781349340255. https://doi.org/10.1057/9781137311351.
Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513–552.
Savigny, H., & Warner, H. (2015). The politics of being a woman feminism, media and 21st century popular culture. Palgrave Macmillan. isbn:9781137384652.
Silge, J., & Robinson, D. (2017). Text mining with R: A tidy approach. O’Reilly Media.
Suttles, J., & Ide, N. (2013). Distant supervision for emotion classification with discrete binary values. Computational Linguistics and Intelligent Text Processing, 121–136. https://doi.org/10.1007/978-3-642-37256-8_11
Teays, W. (2019). Analyzing violence against women. Springer Nature Switzerland A.G. isbn:9783030059880.. https://doi.org/10.1007/978-3-030-05989-7
Walters, M. (2005). FEMINISM a very short introduction. Oxford University Press. isbn:9780192805102.
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Ay, H.U., Günesen, S.N., Kaya, T. (2022). Exploring the Third Wave of Feminism Through Hierarchical Clustering and Sentiment Analysis. In: Topcu, Y.I., Önsel Ekici, Ş., Kabak, Ö., Aktas, E., Özaydın, Ö. (eds) New Perspectives in Operations Research and Management Science. International Series in Operations Research & Management Science, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-91851-4_7
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