We live in a knowledge worker age. We attain information from books, news, internet, people, life experience, and everything else.
Books are highly condensed but outdated. News articles are fresh but not condensed. So there is a gap between books and news.
The current recommendation systems used by news websites like BBC or apps like InShorts or Google Assistant News are not user customizable particularly with respect to time. For example the user cannot pick the most popular articles as per the time specified like say last year.
So I made a webapp which is live at https://www.condense.press/ It shows the popularity of the articles, the dates written, the number of words and the category of the articles through charts and other means which will help the user in picking the right article to read.
Also personalisation and analytics used by Facebook and Google News is not user customizable. For example, in Facebook a user might not click the Like button of a post for privacy reasons but might actually be interested in it. In such cases the user is not given the control to tweak the algorithm. Another example is that search engines balance relevance of the search term and popularity in their results. I aim to provide control to the user on what should be prioritized more.