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Collective Identity, Sexual Coercion...

Julien, Chris.

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Collective Identity, Sexual Coercion, and Hegemonic Masculinity: Machine Learning and the Discourse of the Manosphere.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Collective Identity, Sexual Coercion, and Hegemonic Masculinity: Machine Learning and the Discourse of the Manosphere./
Author:	Julien, Chris.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	131 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
Contained By:	Dissertations Abstracts International85-05B.
Subject:	Feminism. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30720568
ISBN:	9798380723985

Collective Identity, Sexual Coercion, and Hegemonic Masculinity: Machine Learning and the Discourse of the Manosphere.
Julien, Chris.

Collective Identity, Sexual Coercion, and Hegemonic Masculinity: Machine Learning and the Discourse of the Manosphere. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 131 p.

Source: Dissertations Abstracts International, Volume: 85-05, Section: B.

Thesis (Ph.D.)--The Pennsylvania State University, 2023.

In this project, I scrape and curate a novel dataset consisting of all posts and comments written in 58 subreddits belonging to the "Manosphere". This is a diffuse social movement concerned with what they believe is the rampant misandry of contemporary feminism. As such, it represents the first study to examine such a breadth of Manosphere discourse and analyze the themes therein, advancing our understanding of the prevalence and ubiquity of the themes of their discourse. This project uniquely captures the main forums in which the Manosphere congregated for over a decade and analyzes the texts therein with machine learning techniques. The aim of this project is to increase our knowledge about the Manosphere, with particular attention paid to: 1) the role of misogynist terrorist attacks and their influence on the Manosphere's discourse and collective identity, 2) the optimal machine learning techniques for analyzing nascent text-based communities, and 3) rhythms of sexual coercion that are normalized in a specific kind of Manosphere post, the "Field Report."In Chapter 2 of this project, I examine the discourse of the Manosphere on Reddit in the aftermath of violent misogynist attacks. Drawing on scholarship related to terrorist studies, collective identity, and precarious masculinity, I show how the main issues of the Manosphere, masculinity, and perceived misandry influence the beliefs and behaviors of the movement's members. I find that varying kinds of posts in the Manosphere forums are influenced differently by the violent attacks. Rather than one uniform pattern of influence following violent attacks, posts with relational topics, where members share interpersonal concerns, are stymied, while posts with ideological topics, where members refine and reiterate their core beliefs, receive a boost in frequency. I discuss the implications of this finding in light of the movement's collective identity.In Chapter 3, I evaluate several different machine learning techniques in the task of predicting popular and controversial content on Reddit. These data contain a class imbalance, common for many text datasets. As such, it advances our understanding of best practices for evaluating small textual datasets with a class imbalance. This is relevant as new communities take root in digital spaces and forums akin to subreddits. I also overview several common metrics for evaluating machine learners for class imbalance prediction tasks, finding balanced accuracy to be most successful.In Chapter 4, I analyze a specific kind of post from the Pick-Up Artist and Seduction communities within the Manosphere: "Field Reports". While many field reports detail consensual interactions, some describe an ebb and flow of resistance to sexual escalation and subsequent persistence even in spite of that resistance. These patterns that are legitimated through the encouraging comments of Manosphere members reify hegemonic masculinity and reproduce gender inequality in contemporary society. I analyze these findings in light of the Traditional Sexual Script, which undergirds the beliefs of these subsets of the Manosphere.

ISBN: 9798380723985Subjects--Topical Terms:

526785
Feminism.
Subjects--Index Terms:

Manosphere

Collective Identity, Sexual Coercion, and Hegemonic Masculinity: Machine Learning and the Discourse of the Manosphere.
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500 $a Advisor: Felmlee, Diane.
502 $a Thesis (Ph.D.)--The Pennsylvania State University, 2023.
520 $a In this project, I scrape and curate a novel dataset consisting of all posts and comments written in 58 subreddits belonging to the "Manosphere". This is a diffuse social movement concerned with what they believe is the rampant misandry of contemporary feminism. As such, it represents the first study to examine such a breadth of Manosphere discourse and analyze the themes therein, advancing our understanding of the prevalence and ubiquity of the themes of their discourse. This project uniquely captures the main forums in which the Manosphere congregated for over a decade and analyzes the texts therein with machine learning techniques. The aim of this project is to increase our knowledge about the Manosphere, with particular attention paid to: 1) the role of misogynist terrorist attacks and their influence on the Manosphere's discourse and collective identity, 2) the optimal machine learning techniques for analyzing nascent text-based communities, and 3) rhythms of sexual coercion that are normalized in a specific kind of Manosphere post, the "Field Report."In Chapter 2 of this project, I examine the discourse of the Manosphere on Reddit in the aftermath of violent misogynist attacks. Drawing on scholarship related to terrorist studies, collective identity, and precarious masculinity, I show how the main issues of the Manosphere, masculinity, and perceived misandry influence the beliefs and behaviors of the movement's members. I find that varying kinds of posts in the Manosphere forums are influenced differently by the violent attacks. Rather than one uniform pattern of influence following violent attacks, posts with relational topics, where members share interpersonal concerns, are stymied, while posts with ideological topics, where members refine and reiterate their core beliefs, receive a boost in frequency. I discuss the implications of this finding in light of the movement's collective identity.In Chapter 3, I evaluate several different machine learning techniques in the task of predicting popular and controversial content on Reddit. These data contain a class imbalance, common for many text datasets. As such, it advances our understanding of best practices for evaluating small textual datasets with a class imbalance. This is relevant as new communities take root in digital spaces and forums akin to subreddits. I also overview several common metrics for evaluating machine learners for class imbalance prediction tasks, finding balanced accuracy to be most successful.In Chapter 4, I analyze a specific kind of post from the Pick-Up Artist and Seduction communities within the Manosphere: "Field Reports". While many field reports detail consensual interactions, some describe an ebb and flow of resistance to sexual escalation and subsequent persistence even in spite of that resistance. These patterns that are legitimated through the encouraging comments of Manosphere members reify hegemonic masculinity and reproduce gender inequality in contemporary society. I analyze these findings in light of the Traditional Sexual Script, which undergirds the beliefs of these subsets of the Manosphere.
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