Impact Analysis of Harassment Against Women in Bangladesh Using Machine Learning Approaches


Jahan, Busrat and Mahmud, Bahar Uddin and Al Mamun, Abdullah Sarwar and Majumder, Md. Mujibur Rahman and Alam, Mahbubul (2022) Impact Analysis of Harassment Against Women in Bangladesh Using Machine Learning Approaches. Lecture Notes in Electrical Engineering, 730. pp. 549-559. ISSN 1876-1100

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Violence against women is a major threat in Bangladesh, where reports of harassment of women and girls have spread an alarming rate. Unfortunately, despite significant achievements in women’s development and bearing a magnanimous history of women’s movement, incidences of harassment against women is still a burning issue. The majority of women are harassed by their relatives, friends and other people. From the survey we have tried to give an idea about the types, causes and impacts of harassment against women in Bangladesh. This is a survey-based paper and using Apriori algorithm to analyze the impacts of harassment against women and girls of Bangladesh. For these reasons, we have selected 2300 respondents to identify the impact of harassment. This study aims to find out the impact of violence in our society and cohere it with our social norms and values. The impact of sexual harassment on these outcomes (Anxiety, Intense fear, Ongoing fears, Depressions, Disrupted work life, Degradation of performances in study or work, Face difficulties with communication, Intimacy and enjoyment of social activities, Sleep disturbances or Nightmares) among different age’s women/school and college going girls was compared to the outcomes among each other. In this study, according to comparison we find out that teenager, age below 18, is most vulnerable to harassment.

Item Type: Article
Uncontrolled Keywords: Sexual harassment, survey sampling, apriori algorithm
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD4801-8943 Labor. Work. Working class > HD6050-6305 Classes of labor Including women, children, students, middle-aged and older persons, minorities
Divisions: Faculty of Management (FOM)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 04 Feb 2022 02:01
Last Modified: 04 Feb 2022 02:01


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