Sentey is a data visualization tool that is used to analyze tweets for varying sentiment and emotion. Users will provide a key word or hastag, and Sentey will filter and retrive the lastest tweets that match the specific keyword or hastag and then parse the information for the context it was used in. This data will then be sent for sentiment analysis using Meaning Cloud text analysis API, which will return JSON of the completed analysis.
The results of this analysis will be graphically displayed to the User using a data visualization tool, most likely D3 or Chart.js, etc.
In Sentey, users will be able to:
- Filter Twitter based on specific keyworks or hashtags
- View some sample tweets from the filter
- Have their filtered tweets analyzed for sentiment
- View the analyzed data in graphical form
The following are preliminary ideas in the process of designing this webpage:
This app will consist of a single screen with an input form to retrieve the keyword or hashtag with a submit button. This would be used to update the data visualization portion of the page.
There will be a footer with links to the Github and my LinkedIn. A navbar will be there for a custom logo hyperlinked to reset the data. There will a section where the User can input a keyword/hashtag and submit the form. There will be a data visualization section where the chart/graph will reside
This project will be implemented with the following technologies:
- Vanilla JavaScript for overall structure,
- D3 for data visualization,
- Twitter authenticated API to retrieve tweets,
- Microsoft Azure to analyze the retrieved tweets
Day 1:
- Create index.html and sample CSS file
- Learn how to access the twitter API
- Create a static dummy form on the webpage
Day 2:
- Access the twitter api
- Recieve tweets from twitter in JSON format
- Connect it to the form on the page
- Display a few of the tweets on the webpage
Day 3:
- Learn how to use sentiment API
- Learn how to use D3 library
- get resulting data from sentiment API
Day 4:
- Format the data from the sentiment API
- Get a chart on the webpage
- Style the webpage
There are many directions in which this project could evolve.
- Have a tabbed section to visualize the data in many ways
- Ability to compare search results
- First time using OAuth
- Issues with Twitter tokens
- Implicit implementation of API keys from Google's Natural Language Processing API
- Code for Sentiment Analysis present but was unable to visualize the data effectively in the time period