VisualizeR Report
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Contents
Motivation of the application
Crowdfunding - the practice of using small amounts of capital from a relatively large number of individuals to fund a project or venture typically through the Internet – has risen almost exponentially to prominence.
Crowdfunding makes use of the easy accessibility of vast networks of friends, family and colleagues through social media websites like Facebook, Twitter and LinkedIn to get the word out about a new business or campaign and attract investors.
Mobile Application-mediated crowdfunding, especially, is an emerging paradigm used by individuals to solicit funds from other individuals to realize projects. Crowdfunding platforms, such as RocketHub, Kickstarter, and IndieGoGo have been providing opportunities for anyone with Internet access to pitch an idea to their social network and beyond and to gather funding to realize their work.
Currently, there are more than 100 crowdfunding websites in the US, and they are experiencing an exponential growth in popularity. Kickstarter.com, which started in 2009, now hasmore than $9,000,000 pledged per month. And considering the outlook for technology, this field will continue to expand given that it secures the right rules and regulations for functioning.
Campaigns are across various markets sectors and domains, across technology, businesses, nonprofit orgs, political, charity, commercial, or even financing for a startup.
With this sort of rise in online platforms allowing people to easily create campaigns, crowdfunding has emerged as an area that is ripe for research.
Review and critic on past works
Despite the growing popularity of crowdfunding, there is little scholarly research in this domain.
Economists study consumer behavior and how consumers continually make choices among products and services. They examine advantages of crowdfunding such as practicing menu pricing and extracting a larger share of the consumer surplus, and disadvantages of crowdfunding such as constraining the choices of prices to attract a large number of funders.
Management scholars find crowdfunding eliminates the effects of distance from funders whom creators did not previously know.
As an area of analysis, crowdfunding has largely featured literature that focused more on predicting the success/failure of campaigns.
As a field of visualization, the data has relatively been left untapped; most visualizations that exist simply show the accuracy of these prediction algorithms.
Design framework
Through this project and application of R and its tools, we have tried to set a platform to explore the datasets gathered by the crowdfunding apps for understanding and visualizing patterns between the viewers and investors. The application sets the tone for performing exploratory data analysis (via choropleths and heatmaps and calendar maps) by way of communicating the age group that contributes most or the states that contribute highly on crowd funding projects. The application helps us find specific segments of users who show interest on specific category of project (Health/Environmental/ Technological/ Sports/Politics, etc.) that the app launches/publishes. It helps unleash the user behavior through sunburst charts for various regions/states and help us find the regions that indulge in cautious investing or impulsive funding. Usage of clustering algorithms (k means and parallel coordinates visualization) demonstrated in CFVAR help us segment the users in ways or methods that matter to individual users or corporations for their ongoing as well as upcoming projects. Both researchers of crowdfunding as well as people interested in starting their own campaigns can benefit from such tools as they can utilize these visualizations to make better sense of the data. Because of this emerging domain, the visualizations explored would just be the beginning of what can be an ever-increasing domain of research and analysis for this growing field.
DESIGN WORKFLOW:
For this analysis, we have made use of a dataset that was publicly available for Bootloader app, an app that collects information on the viewing and funding activity of the users on crowdfunding sites.
The dataset consists of 50000 observations of 10466 distinct Users/Visitors across 5 category of projects (Environment, Games, Sports, Fashion, Technology)
The dataset consists of US demography with the information on the location(latitude,longitude) of the visitors.
DASHBOARD:
The crowdfunding dashboard is largely split into 4 areas
- A chloropleth map representing USA with states color intensity proportional to the amount coming from that particular state.
- A calendar map to understand the pattern of the funding received at what day of the month and at which hour.
- Bar chart to understand the proportion of the funded categories by each state
Demonstration
Discussion
What has the audience learned from your work? What new insights or practices has your system enabled? A full blown user study is not expected, but informal observations of use that help evaluate your system are encouraged.
Future Work
- First, we plan to collect more data and do a deeper analysis. We would ideally want the data to have IDs for each of the projects to reveal patterns of viewing and funding for specific projects coming from the creators. Any information about the creators of the project (viz. the rating or expertise of the creator)
- Second, we would like to consider how one project leads up to other projects or innovations and how many of them turn into mega projects or companies at record pace. It would be good to find if investors also play the role of creators at any point in time and how varied or similar is the project scope from the ones they have invested in the past.
- Third, we would like perform time series analysis to find any cyclical patterns to understand linking of investments with the financial calendar of the investors.
- In sum, the application has set a good foundation for us to perform data analytics on this area of research and it can be further strengthened and made robust with the right sort of data.
Installation guide
- Post the setup of Rstudio (https://www.rstudio.com/products/rstudio/download/), the end user of this application will have to avail the following packages and library for the functioning of this application:
Shinydashboard
Plotly
Tidyverse(lubridate, dplyr,readr)
sunburstR
User Guide
- Step-by-step guide on how to use the data visualisation functions designed.
