News Feed is a data visualization and sound art installation that reads major worldwide online newspapers, exposing the sentiment of news stories published.

As new articles are published from major journals, an algorithm analyses and classifies them according to whether they are positive or negative in sentiment. These results are then interpreted and transformed into sound and visual meanings, making the audiovisual installation to perform accordingly with the data.

Recently, some scientific research advances in the field of natural language processing (NLP) have led to the creation of algorithms that are able to extract sentiment and emotion from text, sometimes even outperforming individual human raters. These methods are generally used in research and scientific domains. We propose to use this text-based analysis as a means to expose the sentiment of news stories published everyday to create awareness about the emotional impact it might have in our daily lives.

The exhibition acts as a performative mechanism. News Feed will be reading news stories from major online newspapers such as The New York Times, The Guardian, CNN, Japan Today or Al Jazeera from the 14th to the 31th of March. In the finissage the data collected during the exhibition period will be shared.