SuicideWatch: Proposal v2

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ABOUT US

PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Version 1

Version 2

After further discussion and consultations with Prof. Kam, our team concluded that our initial problem statement and methodology may not be the best approach to analysing suicide data. There was insufficient evidence to draw correlations between socioeconomic factors and suicide rates, as suicide is a complex issue encompassing many factors that cannot be generalised. As such, we decided to pivot our project's direction slightly. Instead of attempting to make conclusions, we will focus on creating a visualisation that allows for exploration and comparison of suicide rates globally.

PROBLEM & MOTIVATION

Close to 800 000 people die due to suicide globally every year, which is one person every 40 seconds. Suicide is a global phenomenon and occurs throughout all ages. In Singapore, suicide is the leading cause of death for those aged 10-29. Interestingly in Singapore, females are more likely to be diagnosed with depression and attempt suicide, but males accounted for more than 71% of all suicides in Singapore in 2018. The steady suicide figures signal the presence of an unseen epidemic, one that silently tips people over the edge. While most push the blame to depression, there is no one size fits all explanation when it comes to suicide.

Suicide rates vary from continent to continent, country to country. But are there similarities or patterns that we can discern from this data? Often seen as a taboo topic, suicide is a very real problem that is not talked about enough. Through our visualisation, we hope to be able to shed some light on and increase awareness of this issue.

OBJECTIVES

In this project, we are hope to create a visualization that enables the following:

1. Identify regions or countries with high/low suicide rates
2. Visualise the relationship between Happiness Index scores and suicide rates
3. Exploration of suicide demographics by country
4. Comparison of suicide demographics between countries
5. A more in-depth breakdown of Japan's suicide demographics

As mentioned, the reasons behind suicide is complex and cannot be generalised. Through our visualization we hope to show that generic measures like political stability or GDP per capita do not provide a general explanation for suicide. There are definitely many deep-seated issues or underlying cultural norms that could contribute to suicide rates as well. Ideally a further breakdown of the suicide demographics should be conducted for each country, as suicide rates within different parts of a country could vary as well. However, such data is not readily available. We managed to find detailed data on Japan's suicide rates and thought it would make for a good visualisation of the varying suicide rates within a country. Japan has long been known to have high suicide rates, posited to be an amalgamation of its aging population, overwork and even cultural glorification of suicide ("Seppuku"). As such, we decided to breakdown Japan's suicide figures across different prefectures.

SELECTED DATASETS

Dataset/Source	Data Attributes	Why this Dataset?
Suicide Rates Overview (1985 to 2016) (https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016)	Suicide rate by country Suicide demography (Age/Gender) Economic data (GDP)	This dataset will be our main source of global suicide data.
World Happiness index 2019 (https://worldhappiness.report/ed/2019/)	Overall Happiness Rankings of Countries Worldwide Individual segment scores for each country (Freedom of speech, social support, etc)	This dataset will be used for comparison to each country's suicide rates, to visualise the relationship between "Happiness" and suicides. Although it may not be the best measure of happiness, we will make do with it as it is the most comprehensive dataset available for happiness scores worldwide.
Japan Suicide Statistics(Yearly) (https://www.npa.go.jp/publications/statistics/safetylife/jisatsu.html/)	Suicide rate by prefecture Suicide rate breakdown by gender and age group Suicide rate breakdown by profession and reason of suicide	This dataset will be used for in-depth visual analysis for Japan. Compiled and released by Japan's National Police Agency, it contains a detailed breakdown of the suicide demographics across prefectures in Japan.

RELATED WORKS

Example	Takeaways
An interactive dashboard for worldwide suicide data 1985-2015 Source: https://www.kaggle.com/tavoosi/suicide-data-full-interactive-dashboard/#data	We get inspiration from this dashboard, which utilises the same set of data for world suicide statistics. This dashboard used a world map and bar chart for worldwide suicide rates, which we found informational and easy to understand. Breakdown by country,gender and age group are diplayed in diffierent charts accordingly.
Social Media Use and Depression and Anxiety Symptoms: A Cluster Analysis Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5904786/	This paper supports our hypothesis on use of social media leaders to depression and suicide. The research results shows that membership in 2 clusters – “Wired” and “Connected” – increased the odds of elevated depression and anxiety symptoms (AOR = 2.7, 95% CI = 1.5–4.7; AOR = 3.7, 95% CI = 2.1–6.5, respectively, and AOR = 2.0, 95% CI = 1.3–3.2; AOR = 2.0, 95% CI = 1.3–3.1, respectively). We will further look into this issue by plotting the correlation line graph for suicide rate against social media penetration by country.

DESIGN INSPIRATIONS

Example	Takeaways
The New Zealand Labour Market Dashboard Source: https://mbienz.shinyapps.io/labour-market-dashboard_prod/	Pros: This chart is suitable for showing figure change between two timestamps It is clear and easy to understand Cons: The value fluctuation within the duration is excluded from the graph
Bubble Chart - Obama’s 2013 Budget Proposal Source: https://archive.nytimes.com/www.nytimes.com/interactive/2012/02/13/us/politics/2013-budget-proposal-graphic.html	Pros: This chart is eye-appealing for two-dimension analysis Extreme data points can be easily identified Cons: Comparison for similar values is hard to be done, as no axis is given and all figures are displayed in color or size

PROPOSED STORYBOARD

Our proposed application will consist of four pages:

LANDING PAGE

Proposed Storyboard	Description
	This page will serve as an introduction to our problem and objectives, to give the viewer an overview of our project.

OVERVIEW

This page will provide the viewer with an overview of global suicide rates and overall happiness scores.

Proposed Storyboard	Description
	Allows visualization of Worldwide Suicide Rate/Happiness Index Scores by year, sorted in ascending/descending order. Color of the bars and map will correspond to the Suicide Rate/Happiness Index Score of each country. This makes it easy to identify clusters or regions where suicide rates or happiness index scores tend to be high or low.

DEMOGRAPHICS

Proposed Storyboard	Description
	Breakdown of Suicides by Gender/Age

CASE STUDY: JAPAN

The purpose of this page is...

Proposed Storyboard	Description
	Represents the correlation between Suicide Rate/GDP and Suicide Rate/Social Network Penetration. Suicide Rates are represented by the size of the bubble GDP/Social Network Penetration Rates are represented by the color of the bubble

PROJECT TIMELINE

KEY CHALLENGES

Challenge	Mitigation
The team is new to data visualization and R Shiny	Engage in hands-on practice during class time and after class Complete R Shiny training courses on Datacamp
Suicide data is not very accessible as it is a sensitive social issue	Acquire data from various sources and conduct data cleaning to organize the data
Tight timeline for the semester	The team should come up with a reasonable project timeline based on everyone's capability Set milestones and adjust the timeline accordingly based on the team's progress

REFERENCES

• link 1
• link 2

COMMENTS

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