<BLOCKQUOTE><br/><br/><P><EM><STRONG>Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards.</STRONG></EM></P><br/><br/><P><EM>The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community.</EM></P></BLOCKQUOTE><br/><br/><P></P><br/><br/><P>In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. </P><br/><br/><P>Features:</P><br/><br/><UL><br/><br/><P><br/><br/><LI>Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity</LI><br/><br/><P></P><br/><br/><P><br/><br/><LI>Presents a detailed study of existing research</LI><br/><br/><P></P><br/><br/><P><br/><br/><LI>Provides convergence and complexity analysis of the frameworks</LI><br/><br/><P></P><br/><br/><P><br/><br/><LI>Includes algorithms to implement the proposed research work</LI><br/><br/><P></P><br/><br/><P><br/><br/><LI>Covers extensive empirical analysis</LI><br/><br/><P></P></UL><I><br/><br/><P></P><br/><br/><P>Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective </I>is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.</P>