Adaptive newsfeed filter system for the social networking site using artificial bee colony optimization

Social networking sites have recently received a lot of attention, which is particularly popular, provides a personal newsfeed of posts that is shared with friends. To enable users to quickly browse the most important and useful newsfeed posts from friends, the sites provides a newsfeed filter to show the top news for users. However, the selected results may not conform to the individual's viewing needs. This study proposes a newsfeed filter system on Facebook, which utilizes an artificial bee colony algorithm to provide adaptive newsfeed posts based on individual preferences. The experimental results indicate that the proposed method improves the accuracy of the newsfeed filter and outperforms other methods.