Social media-driven news personalization

While social media have achieved significant and widespread adoption as platforms for sharing information, their use as a source of data for predicting user interests has not yet been fully explored. In this paper, we present a content-based approach to modeling user interests based on Twitter. Our recommendation system uses information retrieval techniques to represent tweets and users as collections of news topics, including high-level categories (e.g., sports, politics, business) and detailed subtopics (e.g., Chicago Bulls, Mitt Romney, entrepreneurship). We discuss the design of a system that uses this information to deliver news recommendations in the form of a personalized newspaper. Finally, we describe a novel method for evaluating recommendation systems based on Twitter that involves mining Twitter data to identify explicit indicators of news interests and comparing these to retroactive system recommendations.

[1]  Abhinandan Das,et al.  Google news personalization: scalable online collaborative filtering , 2007, WWW '07.

[2]  Qi Gao,et al.  Analyzing user modeling on twitter for personalized news recommendations , 2011, UMAP'11.

[3]  Barry Smyth,et al.  Using twitter to recommend real-time topical news , 2009, RecSys '09.

[4]  Mary Beth Rosson,et al.  How and why people Twitter: the role that micro-blogging plays in informal communication at work , 2009, GROUP.

[5]  Kirsten Swearingen,et al.  Beyond Algorithms: An HCI Perspective on Recommender Systems , 2001 .

[6]  Chien Chin Chen,et al.  PVA: a self-adaptive personal view agent system , 2001, KDD '01.

[7]  Michael S. Bernstein,et al.  Short and tweet: experiments on recommending content from information streams , 2010, CHI.

[8]  Michael J. Pazzani,et al.  A personal news agent that talks, learns and explains , 1999, AGENTS '99.

[9]  Rashmi R. Sinha,et al.  The role of transparency in recommender systems , 2002, CHI Extended Abstracts.

[10]  Timothy W. Finin,et al.  Why we twitter: understanding microblogging usage and communities , 2007, WebKDD/SNA-KDD '07.

[11]  Jiahui Liu,et al.  Personalized news recommendation based on click behavior , 2010, IUI '10.

[12]  Michael J. Pazzani,et al.  User Modeling for Adaptive News Access , 2000, User Modeling and User-Adapted Interaction.

[13]  Evgeniy Gabrilovich,et al.  Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis , 2007, IJCAI.

[14]  George Karypis,et al.  Centroid-Based Document Classification: Analysis and Experimental Results , 2000, PKDD.

[15]  Rachel Davis Mersey,et al.  Can Journalism Be Saved?: Rediscovering America's Appetite for News , 2010 .