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

H. Umutcan Ay; S. Nazlı Günesen; Tolga Kaya

doi:10.1007/978-3-030-51156-2_98

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

H. Umutcan Ay^*, S. Nazlı Günesen, Tolga Kaya

^*Corresponding author for this work

Department of Management Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques
Subtitle of host publication	Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Publisher	Springer
Pages	850-857
Number of pages	8
ISBN (Print)	9783030511555
DOIs	https://doi.org/10.1007/978-3-030-51156-2_98
Publication status	Published - 2021
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey Duration: 21 Jul 2020 → 23 Jul 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1197 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2020
Country/Territory	Turkey
City	Istanbul
Period	21/07/20 → 23/07/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Bag of words method
Feminism
Hierarchical clustering
Machine learning
Sentiment analysis
Text mining

Access to Document

10.1007/978-3-030-51156-2_98

Cite this

Umutcan Ay, H., Nazlı Günesen, S., & Kaya, T. (2021). Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference (pp. 850-857). (Advances in Intelligent Systems and Computing; Vol. 1197 AISC). Springer. https://doi.org/10.1007/978-3-030-51156-2_98

Umutcan Ay, H. ; Nazlı Günesen, S. ; Kaya, Tolga. / Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques. Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A. Cagri Tolga. Springer, 2021. pp. 850-857 (Advances in Intelligent Systems and Computing).

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title = "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.",

keywords = "Bag of words method, Feminism, Hierarchical clustering, Machine learning, Sentiment analysis, Text mining",

author = "{Umutcan Ay}, H. and {Nazlı G{\"u}nesen}, S. and Tolga Kaya",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2020 ; Conference date: 21-07-2020 Through 23-07-2020",

year = "2021",

doi = "10.1007/978-3-030-51156-2_98",

language = "English",

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series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "850--857",

editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Basar Oztaysi and Sari, {Irem Ucal} and Selcuk Cebi and Tolga, {A. Cagri}",

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Umutcan Ay, H, Nazlı Günesen, S & Kaya, T 2021, Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Advances in Intelligent Systems and Computing, vol. 1197 AISC, Springer, pp. 850-857, International Conference on Intelligent and Fuzzy Systems, INFUS 2020, Istanbul, Turkey, 21/07/20. https://doi.org/10.1007/978-3-030-51156-2_98

Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques. / Umutcan Ay, H.; Nazlı Günesen, S.; Kaya, Tolga.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A. Cagri Tolga. Springer, 2021. p. 850-857 (Advances in Intelligent Systems and Computing; Vol. 1197 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques

AU - Umutcan Ay, H.

AU - Nazlı Günesen, S.

AU - Kaya, Tolga

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Y1 - 2021

N2 - 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.

AB - 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.

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KW - Hierarchical clustering

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Umutcan Ay H, Nazlı Günesen S, Kaya T. Exploration of the Waves of Feminism Using Sentiment Based Text Mining Techniques. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Springer. 2021. p. 850-857. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-51156-2_98

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

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Keywords

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