Suicidal ideations (SI), often called suicidal thoughts or ideas, is a broad term used to describe a range of contemplations, wishes, and preoccupations with death and suicide. Suicide remains the second leading cause of death among the young generation with an overall suicide rate
Suicide Ideation and Detection
Suicidal ideations (SI), often called suicidal thoughts or ideas, is a broad term used to describe a range of contemplations, wishes, and preoccupations with death and suicide. Suicide remains the second leading cause of death among the young generation with an overall suicide rate of 10.5 per 100,000 people. Sometimes people post more personal content that shows signs of something going wrong in their life. It’s a call for help, these posts may have words to convey fear, loneliness, and hopelessness yet we don’t even realize it or know for sure.
This study sought to analyze “Suicide Ideation” documents posted on social media with an aim to determine reasons for suicide actualization and to analyze the post to know behind the meaning of that statement which if a person is going to suicide or not. For that purpose, we will use NLP to do sentimental analysis and use machine learning and some advanced technique like transformer models to train our model so that we can accurately predict if a person is going to do suicide or not. On top of that, we are building a Chatbot for front-end development that will predict whether the conversation is suicidal or not accurately and provide help, awareness, and give suggestions to improve the mood of a person.

We will be using a labeled dataset collected from the subreddit of the Reddit social platform and did research on this dataset to find the accuracy using different models mentioned project implementation section.
For chatbot, we have applied the support machine algorithm (SVM).
With the help of a trained model, we will create chatbot that will understand our input and prove brief conversation to ask users how they are feeling and what's going in their life.
We have used RASA for our chatbot. RASA is an open framework for natural language understanding, dialogue management, and integration.
Intent and their example are used as training data for the assistant natural language understanding (NLU) model.
We group these examples according to the idea of the goal of the message is expressed.
Stories are used to train our assistant's dialogue management model.
Stories can be sued to train models that are able to generalize to unseen conversation paths.
It is a representation of a conversation between a user and an AI assistant.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| System Requirements | Equipment | 1 | 35000 | 35000 |
| Total in (Rs) | 35000 |
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