Abstract

Virtual newspapers and magazines have become a popular means to read news stories from an enormous collection of news articles from round the world. To help users manage this flood of information, we develop customized news recommender system using an OSN, “Twitter”. Tweets from Twitter’s timeline are used to rank the news articles based on popularity of the article. Additionally, users create a profile of their interests and the news articles are ranked based on how well they match the profile. These two techniques are combined to create a hybrid news recommender system that recommends news articles to the user which are popular as well as in relevance with their user profile.