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Social Media Analytics for User Behavior Modeling

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Social Media Analytics for User Behavior Modeling Synopsis

Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. 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. 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. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.

About This Edition

ISBN: 9780367211585
Publication date: 16th January 2020
Author: Arun Reddy (Graduate Student, Arizona State University, AZ) Nelakurthi, Jingrui (Associate Professor, Arizona State Univers He
Publisher: CRC Press an imprint of Taylor & Francis Ltd
Format: Hardback
Pagination: 114 pages
Series: Data-Enabled Engineering
Genres: Product design
Automatic control engineering
Ergonomics
Algorithms and data structures
Computer science
Databases
Communications engineering / telecommunications
Behaviourism, Behavioural theory
Digital and information technologies: social and ethical aspects