Apple Crunch: Proposal

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Proposal

Problem and Motivation

Problem: For many, acquiring enough finances to turn their idea into a business is a big issue so some would go for crowdfunding platforms as a means to obtain the required amount to start their business. Kickstarter is one of the more popular crowdfunding platform, but they have an "all or nothing" rule where the campaign cannot get the donated amount if it does not reach the goal set by the business. As of October 5th 2018, only about one in every three campaigns reach their funding goal, which means that most do not get the funding they need from Kickstarter.

Motivation: There is a need to understand what makes a successful campaign. Are there any attributes that sets apart projects that are successful? The team would like to create several visualizations on kickstarter campaign data to analyze trends and determine if certain attributes of a campaign such as "amount of funding set" affects its chances of succeeding. In the end, the team hopes that others can use the visualizations created in order to have a better understanding of how they should create their campaign to have a higher chance of success.

Data

The group will only use one csv file as the source of data.

Dataset
ks-projects-201801.csv from https://www.kaggle.com/kemical/kickstarter-projects#ks-projects-201801.csv

Details of Dataset

Column	Description
ID	ID of the campaign / project
name	Name(Title) of the campaign / project
category	Sub-category of the campaign
main_category	Main category of the campaign
currency	Currency used for funds of the campaign
deadline	Until when the campaign will run
goal	Goal amount to reach of the campaign in their currency
launched	When this campaign started
pledged	Amount pledged by donors in the currency of the campaign
state	Status of the campaign (successful? failed?)
backers	How many donors
country	Which country is the campaigned launched
usd pledged	Pledged amount converted to USD by KS conversion
usd_pledged_real	Pledged amount converted to USD by fixer.io
usd_goal_real	Goal amount converted to USD

Survey of Related Work

Related Work	Points to Consider
https://www.appsblogger.com/behind-kickstarter-crowdfunding-stats/	The inforgraphic has presented various ideas to explore in terms of what kinds of visualizations to create. The inforgraphic mostly presented numbers and not an in depth visualization. The things to consider by looking at this work would be the following: By how much do projects/campaigns succeed or fail? What are the success rates per category? Which features of a campaign are related with its success?
https://www.displayr.com/how-to-guarantee-your-kickstarter-will-succeed/	This chart shows another point to consider which is how the number of backers affect the success rate of a project. The use of pie chart however, may not be what the group will use.
Example	Example

Charts

Chart	Description and Analysis
Visualisation Dashboard	Methodology We would be using most of the data given from the dataset How the visualisation dashboard works is that, as the user interact with the tree map on the left hand side, the visualisation on the right hand side would be dynamically changed showing the users insights according to the users' interaction with the tree map Purpose This is to allow users to explore the world of KickStarter in a lot more intuitive way Pros Clearly show the data with all the necessary stats needed before anyone launch their kickstarter campaign Cons Information might be cluttered, experimentation is needed
Word Cloud	Data Used Titles of projects And other filtering attributes Methodology We would be doing text analysis for all the titles of the projects in each category Based on the analysis, we would be visualising the result using Word Cloud There will be filtering function to allow users to only select successful/failed/cancelled projects as well as filtering based on countries/project categories Purpose This is to allow the user to understand for each of the category, what are the words being used by the past projects Pros It reveals the distribution of words in a visually appealing way It is engaging with the users Cons Users might have difficulty in deciphering the size and comparing the size of one word with another

Technical Challenges

Technical Challenge	Solution
Group is not that experienced and familiar with visualization softwares	Watch Videos Online Learn as a group and help each other
Crawling Certain information such as the city or state of the campaign and the description of the campaign have to be obtained by crawling	Learn how to crawl online Set aside time every day to work together
No experience with javascript and D3	Watch videos and read about javascript and D3 Work and ask one another