Trouble Faced by the LGBTQ Community and Prediction of the Suicidal Rate of LGBTQ Community using Support Vector Model

Lesbian, gay, bisexual, and transgender (LGBT) community refers to a broad group of organizations that are varied in respect to gender, sexuality, religion or ethnicity, and socio-economic status. Because of humiliation, racism, and harassment in society, young individuals who are identified as Lesbian, Gay, Bisexual, Transgender, Queer, Questioning, or Intersex (LGBTQI+) face unique challenges. This systematic review will look at qualitative studies with a focus on services for mental illnesses and the important support service policies and practices in order to better understand the challenges and issues that LGBTQ youth face. Four main themes emerged from studies are as follows: (1) Marginalization; (2) Isolation; (3) Depression; (4) Self-harm and Suicide. This detailed analysis of qualitative studies provides a lot of information to guide and assist the provision of remedies and policies that will solve the disparity in psychological health statistics for the LGBTIQQ youth group. To improve the psychological and mental health a predictive model is proposed that helps to predict the suicidal rate. Present study offers tons of information that may be used to guide the development of programmers and regulations that will narrow the statistical gap for psychological health for the group of young people who are identified as sexual and gender minorities. Statistical data represents challenges and problems faced by LGBTQ community.

I. Introduction

LGBTQ Represents Lesbian, Gay, Bisexual, Transgender, questioning as in still exploring one's sexuality or queer, or at times both. LGBT community is raising their voice for their rights rapidly in recent year [1]. LGBT community in India still facing the discrimination just because of the cheap mentality. The support of loved ones is a crucial factor for LGBT community. Transgender people are those whose identities are far different from the stereotypical gender norms or they are the purest soul ever, which give identity to the human being only as male or female [2]. Just because of socially backward people they face discrimination, social oppression and physical violence After so many incidents happen to LGBTQ community, government decided to enact the Transgender's (Protection of Right) Act, 2019 to provide prohibiting in contrast to employment, health Services and education to Welfare measures to transgender person[3]. LGBTQ community is more probably to face intolerance, racism, harassment, and the threat of violence just because of gender identity. In India marriage of same sex couple is very difficult because many socially backward people don't accept LGBTQ community. The main objective of LGBTQ community is to improve the health, lifestyle, safety and well being of lesbian, gay, bisexual and transgender people. Rising depression rates and suicide may arise from this. But nowadays social media is known as the biggest support for LGBTQ community many social media influencers come in support of LGBTQ community and start creating awareness for them[4]. This paper additionally offers with the overall LGBT community being affected by the deadly COVID-19 virus. Similar to this, we have explored how society views the LGBT community, the role that LGBT rights play in international law, the history of LGBT legal cases, and the movement against Sec. 377. Although there has been a substantial amount of research on LGBT issues, there has been little and infrequent research on the status under the Uniform Marriage Act and personal laws. Machine learning is a vital component in the constantly increasing field of data science and can help to solve many emerging issues in different areas. Processing emotions is a key component of the closely related polarity function. It is quite difficult in the world to capture the general public's feelings on-the-spot. So the machine learning algorithms are used to predict data from databases when the only data is available without linking output factors. While the results of supervised algorithms are known in advance, unsupervised algorithms closely resemble true artificial intelligence the idea that without any direct human interaction, a machine may learn to understand complicated processes and patterns. To control the suicidal attempts of such type of young people a Support Vector Model (SVM) is proposed in the manuscript. As one of the most crucial factors in human growth and development the paper discussed affective computing and emotional analysis to identify emotions in people.