There are 5 repositories under suicide-data topic.
Visualizing suicide data with javascript libraries
Data analysis of suicide happened in India between year 2001 to 2012
Data Analysis of suicides in India
To categorize tweets according to the severity level of suicidal intentions expressed in tweets’ text.
This research project seeks to comprehensively investigate suicide rates and their underlying factors over the period from 1985 to 2020.
From growing up in the heart of Silicon Valley, I have always wondered what was the factors that play a role in Suicide. There have been a plethora of suicide clusters from my High School in Palo Alto. This project seeks to explore the underlying factors. We will use a sample of 44,000 gather data from 141 different Countries, between the 80's to 2016.
Analysis scripts and randomly generated data for Suicide and Life-Threatening Behavior paper: 'Identifying person-specific coping responses to suicidal urges: A case series analysis and illustration of the idiographic method'
In this project, three different models based on GAT, GCN and SAGE have been implemented to examine their performance on two prominent social networking platforms, namely Twitter and Reddit.
This project is about the suicide rate in India and comparison between the different states and union territories of India of the year 2022. This Report will help us to know the official rate of suicide in India and the number of male and female suicide rate, the status of the person, and mode or methods of suicide also the different causes.
This part of the Capstone Project entails a machine learning model to predict macroeconomic movements using geo-regional data in the EU. This project involved extensive data analysis, predictive modeling, and cross-comparison techniques.
Suicide rate research
Our study aims to explore the suicides pattern from the year 1985 to the year 2016 through global, continent and country scales, as well as gender, age, GDP and generation factors. The descriptive exploration obtained will then be verified through statistical inferential analysis. We set the target audience as World Health Organization officer who are concerned to track the trend and factors associated with suicides, as we wish the analysis will provide insights and inspire necessary actions taken on suicides prevention.
Code repo for JMIR Mental Health paper: Emerging Trends of Self-Harm Using Sodium Nitrite in an Online Suicide Community: An Observational Study Using Natural Language Processing Analysis
An interactive Excel dashboard analyzing global suicide data from 1985 to 2015. Explore trends by generations, age groups, countries, and continents to better understand global suicide rates.
Analysis of suicides that occurred in 35-year period
Analysis of the suicide death rates within the US Hispanic & Latino population. Data collected from the Centers for Disease Control and Prevention.
An interactive map that plots U.S. CDC suicide rate and population data on a county level built with React and Python.
This repo contains code, a presentation, and a project report regarding suicide rates in the US from 1985 - 2015
Suicide Statistics for India in the year 2020 classified by Gender, Age Bracket and Reposted Cause. Visualised using Python
https://group102-suicide-app-r.herokuapp.com/
Statistical analysis of relationship between overall happiness, climate and suicide ratio accross the Globe.
This repo contains the analysis of suicide data over years implemented through streamlit
Problem to solve: find the patterns for increased suicide rates (1985 to 2016) among different cohorts globally, across the socioeconomic spectrum, using exploratory data analysis. Using bivariate analysis, I try to determine if there is any relationship between two variables.
Data Visualization with Microsoft's Power BI
https://suicideanalysis.onrender.com/
Building a dashboard to present the suicide rate (per 100,000 population) for 2019 across the world for as crude suicide rate and suicides rate by gender.
Depression and Suicidal Thoughts Support Chat App
Data visualisation of suicide rates and social media