Identifying Women's Experiences With and Strategies for Mitigating Negative Effects of Online Harassment

Vitak, Jessica; Chadha, Kalyani; Steiner, Linda; Ashktorab, Zahra

doi:10.1145/2998181.2998337

Cited by 129 publications

(70 citation statements)

References 46 publications

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“…The availability, popularity/ubiquity of information as well as communication technology created а new opportunities for online harassment. [28] In Egypt, researchers reported that а large section of women has been harassed at least once in their lifetime. The Egyptian Government, international/non-governmental organizations have been working for several years on interventions and activities to combat sexual harassment.…”

Section: Discussionmentioning

confidence: 99%

Online Harassment and Cyberbullying Victimization and Its Emotional Impacts among Female Nursing and Non-Nursing Students

Hassan¹,

Sheha²,

Gamel³

et al. 2019

AJNR

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Background: The increasing internet utilization is associated with various disadvantages. Online cyberbullying and harassment victimization is one of these disadvantages that pose negative emotional consequences. Aim: This study aimed to detect the prevalence of online cyberbullying and harassment victimization amongst nursing students from El-Fayoum University in comparison to students from other faculties at the same university. In addition to figuring out the most significant correlates of victimization and its emotional consequences. Subjects and methods: A total of 308 female nursing students and 320 female non-nursing students from El-Fayoum University participated in this cross-sectional survey. For data collection, а self-administered questionnaire was designed and distributed. The questionnaire included 3 sections; personal characters of the included students, online cyberbullying and harassment victimization during the past year, and the emotional consequences of victimization. Results: Of the surveyed female university students, 84 (27.3%) of the nursing students and 88 (27.5%) of the non-nursing students stated online harassment victimization during the past year, with no statistically significant differences between both groups (Р>0.05). Almost two-thirds of the victimized students from nursing and non-nursing faculties reported online harassment, victimization more than once with no statistically significant differences between both groups (Р>0.05). Urban residence and more hours of internet use per day did not correlate with the prevalence of online harassment victimization (Р>0.05) but associated with frequent exposure (Р<0.05). Anger (74.4%) was the most commonly reported emotional impact of online harassment victimization. Hatred, fear, sorrow, loneliness, and disappointment came next, however, with considerably lower rates. Conclusion: Female university students from nursing and non-nursing faculties were exposed to online cyberbullying and harassment victimization in recognizable rates. Recommendations: Further studies on the coping techniques to online harassment victimization should be conducted. Interventional programs to increase awareness regarding the windows of interference against online harassment according to the Egyptian Penal Code to reduce such intrusions and minimize their emotional effects should be considered.

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Section: Discussionmentioning

confidence: 99%

Online Harassment and Cyberbullying Victimization and Its Emotional Impacts among Female Nursing and Non-Nursing Students

Hassan¹,

Sheha²,

Gamel³

et al. 2019

AJNR

View full text Add to dashboard Cite

show abstract

“…Jessica Vitak, et al, displayed the ramification of aspect correlate with women's online cyberbullying and point to the demand for both philosophers and engineers to continue their efforts to decrease cyberbllying behaviors and reduce their pessimistic effects. This does not extend the most empathetic of the present state of online annoyance for women and unable to construct more efficient apparatus based on what we already know more about the adults factors combined with intimidation in social media [13].…”

Section: Related Workmentioning

confidence: 95%

Identification and Classification of Cyberbully Incidents using Bystander Intervention Model

2019

ijrte

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Cyberharassment is bullying and degrading the adults by means of posting the comments like hurtful and derogatory humor over the internet in an online community. Though few bystanders ever try to reduce the conflicting effects of cyberbullying, and bystanders ever endeavor to interrupt. This will analyze the chattels of articulatory study on bystander intervention using the caricatured procedural made online Social Networking Sites. The proposed works mainly focus on the analysis of direct intervention by bystanders. The direct intervention allows bystanders to do reporting and blocking of cyberbully activities as additional features here. It will generate a report which contains the details of bully by means of alert message and block that bully by the bystander with the victim’s permission in the Facebook. This proposed framework will detect cyberbully words from the short hand text and emoticons on the comment sections using Latent semantic analysis (LSA). The Cyberbully words will be classified using a Random Decision Forest algorithm.

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“…A significant amount of previous work has focused on measuring and understanding adversarial behaviors online, including studies on victims' experiences [41,64] and attackers' motivations [11,12,40]. Other studies have developed machine learning tools that can be deployed at a large scale to support detecting personal attacks [20,46,65].…”

Section: Related Workmentioning

confidence: 99%

Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates

Hua

Нааман

Ristenpart

2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Social media provides a critical communication platform for political figures, but also makes them easy targets for harassment. In this paper, we characterize users who adversarially interact with political figures on Twitter using mixed-method techniques. The analysis is based on a dataset of 400 thousand users' 1.2 million replies to 756 candidates for the U.S. House of Representatives in the two months leading up to the 2018 midterm elections. We show that among moderately active users, adversarial activity is associated with decreased centrality in the social graph and increased attention to candidates from the opposing party. When compared to users who are similarly active, highly adversarial users tend to engage in fewer supportive interactions with their own party's candidates and express negativity in their user profiles. Our results can inform the design of platform moderation mechanisms to support political figures countering online harassment.

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Identifying Women's Experiences With and Strategies for Mitigating Negative Effects of Online Harassment

Cited by 129 publications

References 46 publications

Online Harassment and Cyberbullying Victimization and Its Emotional Impacts among Female Nursing and Non-Nursing Students

Online Harassment and Cyberbullying Victimization and Its Emotional Impacts among Female Nursing and Non-Nursing Students

Identification and Classification of Cyberbully Incidents using Bystander Intervention Model

Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates

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