Project Name: Frame

Team Name: Frame

Team Members: Jovanny, Bereket, Lauren

The Problem

Media bias often misinforms consumers and influences their decisions in ways they could negatively impact them.

Use Cases: CNN comments on Hillary Clintons performance in the first Democratic debate, but doesnt reveal that Time Warner is a donor to her campaign. The incentive could potentially influence how CNN chooses to color the event. Although the user, hasnt been informed of the app would tell them how them that CNN might have "framed" the article a certain way that might give them pause and look to other resources to make a more informed judgement of Clintons policies and appearance.

The Solution

Frame aims to provide the user with a sense of what bias is coming out of the news so they can better adjust their frame or opinions and prevent internalizing implicit bias.

NOTE: Analysis on a hidden button revelead when the article cell is swiped. Facebook and Pocket Sharing can also be found when the cells on the history tab are swiped

Baseline Features:

• Article Analysis via Machine Learning APIs to provide the user with the implicit bias of the articles that they read. Article chaining, which allows user to attach articles of the same topic to provide a wholistic view from different perspectives. User profiles that contain the user's reading bias.
• Bonus features: Users will be able to upload user-created news content

Execution

Version 1 (due Tuesday, November 17)

• Aggregate news and display feed (Due 14th, Saturday)
• Analysis of article

Version 2 (due Tuesday, November 24)

• Allow users to search for news topics
• Create a user that can save articles, and see their aggregated analysis
• Display tone and subjectivity in the collection cell

Version 3 (due Tuesday, December 1)

• Create action extension
• Save articles from outside of the app
• Article chaining

Version 4 / Final (due Tuesday, December 8)

• Multiple users on the backend
• Saving chained articles
• User can see which article topics are most visited

Bonus:

• Analyzing political articles only and visualizing with graph, and adding that to user profile