The current media industry is dominated by negative news, which contains strong emotional language that can significantly impact a reader’s mental well-being. This project introduces a website designed to mitigate these negative effects by selectively curating news articles with a positive sentiment. Using the Guardian API, our website retrieves a wide array of articles in real time, which are then filtered by their positivity. We use a document level, lexicon-based sentiment analysis algorithm using the Natural Language Tool Kit to evaluate and score each article. We also give users the ability to adjust the positivity threshold to find a sentiment level that suits their needs. The user interface of our website is designed to provide an intuitive and engaging user experience, whilst simultaneously looking visually appealing. Our pilot user testing yielded promising results, with participants reporting an easy to use interface and finding the content positivity to be of high quality. Our websites quality assessment also reported good performance, accessibility and compatibility and our functional testing found no errors. This project demonstrates the potential for an enhanced media industry that doesn’t portray a majority of negative emotion and sets a course for further research into the long-term impact of positive and negative news on mental health.