Difference between revisions of "SuicideWatch: Proposal v2"

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<!-- Selected Dataset -->
 
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==<div style="background: #364558; padding: 15px; font-weight: bold; line-height: 0.3em; text-indent: 0px;font-size:20px"><font face="Arial" color=#fbfcfd>SELECTED DATASET</font></div>==
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==<div style="background: #364558; padding: 15px; font-weight: bold; line-height: 0.3em; text-indent: 0px; font-size:20px"><font face="Arial" color=#fbfcfd>SELECTED DATASETS</font></div>==
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<b> Primary data sets: </b> <br>
 
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Suicide statistics: https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016 <br>
 
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This data set consists of the suicide statistics for worldwide countries from 1985 to 2016. Further breakdown for gender, age group is provided. <br>
 
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https://www.who.int/mental_health/prevention/suicide/countrydata/en/ <br><br>
 
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<b>Secondary data sets:</b>
 
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<br>
 
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World Happiness index 2019: https://worldhappiness.report/ed/2019/ <br>
 
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World GDP report for correlation analysis: https://data.worldbank.org/indicator/ny.gdp.mktp.cd <br>
 
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Social media penetration for correlation analysis: <br>
 
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Source a: https://www.statista.com/statistics/282846/regular-social-networking-usage-penetration-worldwide-by-country/  <br>
 
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Source b: https://ourworldindata.org/internet
 
  
 
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! style="font-weight: bold;background: #536a87;color:#fbfcfd;" | Why this Dataset?
 
! style="font-weight: bold;background: #536a87;color:#fbfcfd;" | Why this Dataset?
 
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| <center>Dataset 1<br/>
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| <center>Suicide Rates Overview (1985 to 2016)<br/>
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(hyperlink) </center>
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(https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016) </center>
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* Suicide rate by country
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* Suicide demography (Age/Gender)
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* Economic data (GDP)
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<center>This dataset will be our main source of global suicide data.
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| <center>World Happiness index 2019<br/>
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(https://worldhappiness.report/ed/2019/) </center>
 
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* Attribute 1
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* Overall Happiness Rankings of Countries Worldwide
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* Attribute 2
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* Individual segment scores for each country (Freedom of speech, social support, etc)
 
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<center>This dataset will be used ...</center>
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<center>This dataset will be used for comparison to each country's suicide rates.</center>
 
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| <center>Dataset 2<br/>
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| <center>Worldwide GDP<br/>
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(hyperlink) </center>
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(https://data.worldbank.org/indicator/ny.gdp.mktp.cd) </center>
 
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* Attribute 1
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* Annual GDP by country
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* Attribute 2
 
 
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<center>This dataset will be used ...</center>
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<center>This dataset will be used for comparison to each country's suicide rates.</center>
 
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| <center>Dataset 3<br/>
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| <center>Worldwide Social Media Penetration Data<br/>
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(hyperlink) </center>
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(https://www.statista.com/statistics/282846/regular-social-networking-usage-penetration-worldwide-by-country/) <br/>
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(https://ourworldindata.org/internet) </center>
 
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* Attribute 1
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* Social Media Penetration by country
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* Attribute 2
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* Worldwide Internet access figures
 
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<center>This dataset will be used ...</center>
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<center>This dataset will be used for comparison to each country's suicide rates.</center>
 
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==<div style="background: #364558; padding: 15px; font-weight: bold; line-height: 0.3em; text-indent: 0px;font-size:20px"><font face="Arial" color=#fbfcfd>RELATED WORKS</font></div>==
 
==<div style="background: #364558; padding: 15px; font-weight: bold; line-height: 0.3em; text-indent: 0px;font-size:20px"><font face="Arial" color=#fbfcfd>RELATED WORKS</font></div>==
  

Revision as of 15:06, 7 October 2019

<--- Back to Project Groups

Team 3 - SuicideWatch Logo.png

ABOUT US

PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER


Version 2



PROBLEM & MOTIVATION

Suicide rates are at their highest since WWII. 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 the lifespan. In Singapore, suicide is the leading cause of death for those aged 10-29. 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. Can suicide rates be simply mapped to the Happiness Index or GDP per Capita? Or is there more than meets the eye?

With primary investigation, we found out that the suicide rate varies from country to country. To further study the suicide rate breakdown and the behind, we looked into Japan as it is a Asia country known for high suicide rate, and the Japan government has published more detailed statistics for annual suicide rate. This gives us a good starting point for visualization.




OBJECTIVES

In this project, we are interested to create a visualization that helps analysts perform the following:

  1. Explore suicides rates in each country
  2. Explore if there is a correlation between the suicide rate and happiness index
  3. Explore suicide demographic of each country
  4. Explore possible correlations of each country’s suicide with its GDP and social media penetration
  5. Conduct in-indepth visual analysis for Japan



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.
Worldwide GDP
(https://data.worldbank.org/indicator/ny.gdp.mktp.cd)
  • Annual GDP by country
This dataset will be used for comparison to each country's suicide rates.
Worldwide Social Media Penetration Data

(https://www.statista.com/statistics/282846/regular-social-networking-usage-penetration-worldwide-by-country/)

(https://ourworldindata.org/internet)
  • Social Media Penetration by country
  • Worldwide Internet access figures
This dataset will be used for comparison to each country's suicide rates.



RELATED WORKS

Example Takeaways

An interactive dashboard for worldwide suicide data 1985-2015

Worldmap suicide rate.png

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

Social media and depression.png

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

Two-point-line-graph.png

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

Bubble-chart.png

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 three pages... as can be seen below

LANDING PAGE

The purpose of this page is...

Proposed Storyboard Description

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...


OVERVIEW

The purpose of this page is...

Proposed Storyboard Description

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...


DEMOGRAPHICS

The purpose of this page is...

Proposed Storyboard Description

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...


SOCIOECONOMIC ANALYSIS

The purpose of this page is...

Proposed Storyboard Description

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...

Title/Description

Team 3 - SuicideWatch Logo.png
  • The purpose of this is...



PROJECT TIMELINE

Team 3 - SuicideWatch Logo.png


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

Feel free to leave us some comments or feedback!

Name Comment/Feedback

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  • Comment

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