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UNVEILING THE CHILDHOOD EMOTIONAL ABUSE USING AI-GENERATED IMAGERY AND NATURAL LANGUAGE PROCESSING (NLP)

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dc.contributor.author 03-275232-005, Aqsa Tanveer
dc.date.accessioned 2025-12-08T05:24:33Z
dc.date.available 2025-12-08T05:24:33Z
dc.date.issued 2025-08-01
dc.identifier.uri http://hdl.handle.net/123456789/20087
dc.description Dr. Syed Mubashir Ali en_US
dc.description.abstract Childhood Emotional Abuse (CEA) is a delicate issue, often overlooked, which has immense psychological consequences. In spite of a growing consideration of the issue, there exist enormous lacunae in the identification of specific abusive strategies, their effects, and the utilization of cutting-edge analytical tools like artificial intelligence (AI) and natural language processing (NLP). This study attempts to bridge these gaps through the utilization of NLP and AI-generated imagery to examine the manifestations of emotional abuse and the psychological consequences. The study aims to examine the utilization of AI-generated imagery as a tool for the visualization of the experiences and sentiments of victims of emotional abuse. It will examine qualitative data collected from tales narrated by survivors of child maltreatment through the lens of natural language processing. For the research, data will be collected from unmarried participants between 18 and 35 years of age, from a diverse sample that includes 10 transgender individuals, 10 females, and 10 males, through a qualitative narrative inquiry method. Participants will be asked to write tales that outline the strategies of emotional maltreatment inflicted on children, like gaslighting, humiliation, verbal aggression, isolation, and neglect, using AI-generated images as a backdrop. An NLP-guided analysis will identify relational patterns and emotional dispositions, enabling better understanding of trauma and coping strategies. The Comparative Analysis Method will be employed with Image Generation tools to rigorously examine AI-generated images, with the hope of identifying significant trends in maltreatment. The findings of the present study indicate that the most prevalent modalities of emotional maltreatment among all gender identities were verbal maltreatment and emotional neglect, with a specific spike in identity-based maltreatment—like emotional isolation and gaslighting—among transgender participants. Furthermore, there was a significant relationship between emotionally abusive behavior and authoritarian parenting among transgender individuals. As new technological methods and psychological studies evolved, interdisciplinarity highlights more effective interventions and prevention. en_US
dc.language.iso en_US en_US
dc.relation.ispartofseries ;BULC1451
dc.subject Childhood emotional abuse, AI-generated imagery, Natural language processing, Trauma theory. en_US
dc.title UNVEILING THE CHILDHOOD EMOTIONAL ABUSE USING AI-GENERATED IMAGERY AND NATURAL LANGUAGE PROCESSING (NLP) en_US
dc.type Thesis en_US


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