The idea for the project was to find the actuality of user submitted articles. We planned on creating a chrome extension that would allow any user to implement our program to a chosen article. Our program would then evaluate the "realness" of the article based on finding relationships between the label and the content (text) of the article. By vectorizing the text, we were able to format x value implementations and decode them. After implementing a passive aggressive modifier, we were able to predict the realness probability of any given article by comparing the test value data set with the actual value data set. Although we were able to produce some form of similar probability (as shown in the attached pictures), we were unable to implement our test data and real data set results. Presented in our GitHub page is the seperate fake article identification system and the constructed chrome extension. Source code ideas credit

• Python
• Web Development (HTML, CSS, JS)
• JSON

1. Clone or download the repository
2. Type in chrome://extensions in the URL
3. In the top left corner, click on the Load unpacked. Navigate to the folder where the repository is cloned.
4. The functionality of the Chrome Extension includes a popup menu, which can be accessed when the extension icon is clicked on. The menu is purely front-end due to the time restrictions of the Hackathon and challenges faced.