A look at our plugin
When we open news app or news website, the news that we see are mostly ingested in our flavour from our previous reading history. For example if a user supports the conservative party, he/she will be more likely to read news from conservative outlets. As the result, the reader will get "stuck" with a relative narrow range of perspectives and will not be likely to get expose to the point of views from the other side.
Therefore this inspired us to design and build this plugin that gives reader 3 articles recommendation based on the current article that the reader is reading, but which may share a different point of view.
What it does
when the news reader click onto Oppostasy on a news article site, a side bar will show up on the right side of the window that shows a list of 3 news article with opposing views with title, picture from the news with a clickable link that can redirect reader to the suggested news.
How I built it
Challenges I ran into
One of the biggest challenges that we faced is in the design of the nlp algorithm, which extracts keywords from the current article. We initially used TF-IDF formula that calculates the importance of a word in a document within a collection of documents. The issue is that we are only analyzing the article that the reader is currently reading instead of a collections. As the result, we tweaked the algorithm by changing it from article-base to sentence-base, and incorporates the idea of RAKE algorithm for single document keywords extraction.
Accomplishments that I'm proud of
We are proud that we have completed the plugin considering that we don't have previous experience working on Google Chrome plugin and have no prior knowledge in nlp.
What I learned
We learned how to crawl the web with a python html scraper. We have also learned how to search a website for keywords so that a computer can understand what the website is about. Our understanding of chrome extensions has also been greatly enhanced.
What's next for Oppostasy
There are three areas for Oppostasy that we can work on next. 1) support more news site so we can get more varieties in the recommandation output 2) deploy the server 3) improve the accuracy in nlp algorithm