Challenge Overview
This challenge will be a proof of concept as the base for a new project for analyzing social media posts using sentiment analysis. The sentiment analysis will be used to determine trends in sentiment over a period of time.
John Hancock, like any company, cares about its customers and how it’s being perceived in social media. Many companies have failed to monitor these communication avenues at their peril as now more than ever it is where people go to both praise and criticize their experiences with brands.
A previous challenge has implemented the data scraping and sentiment analysis. This challenge will update the data scraper project with some basic data visualization so we can see word clouds and the raw data in the DB in a browser window.
Environment Requirements
You are welcome to offer suggestions for languages and libraries to use for this particular challenge, with these guidelines:
1. The latest version of Node is required
2. The solution must be deployable to Heroku
3. The solution must use MongoDB as the backend data storage
Requirements
The requirements are comprised of these Gitlab tickets:
* https://gitlab.com/jh-topcoder/social-sa-scraper/issues/1
* https://gitlab.com/jh-topcoder/social-sa-scraper/issues/2
* https://gitlab.com/jh-topcoder/social-sa-scraper/issues/3
Submission:
The existing code is available in Gitlab here: https://gitlab.com/jh-topcoder/social-sa-scraper
You will be expected to submit a Git patch file that can be applied to the commit hash 54612076eb1e21e55015bd4a4ca3f85de70338a7.
Your submission must include a Git patch file against the commit hash above. The Git patch file should include any relevant changes to the README for this challenge, including a separate file for validation information.