Human-Centered Social Media Analytics

ISBN-13: 9783319347097 / Angielski / Miękka / 2016 / 208 str.

Yun Fu

Opis

Utilizing the ubiquity of social media in modern society, the emerging interdisciplinary field of social computing offers the promise of important human-centered applications. Human-Centered Social Media Analytics provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. The collected chapters present a range of different viewpoints examining the various possibilities and challenges to machine understanding of humans in a social context.Topics and features: includes perspectives from an international and interdisciplinary selection of pre-eminent authorities; presents balanced coverage of both detailed theoretical analysis and real-world applications; examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications; reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities; discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation; requires no prior background knowledge of the area.This authoritative text/reference will be a valuable resource for researchers and graduate students interested in social media and networking, computer vision and biometrics, big data, and HCI. Practitioners in these fields, as well as in image processing and computer graphics, will also find the book of great interest.

Recenzje

"Human-Centered Social Media Analytics focuses on the novel social computational methodologies that are being developed to investigate social media data. ... Scholars, both new and established, should consider reading ... to gain an understanding of the questions they should pursue and the challenges they must overcome as they strive to advance big data and social media analytics research." (Pratyush Bharati, Interfaces, Vol. 47 (3), May-June, 2017)

Spis treści

Part I: Social Relationships in Human-Centered Media

Bridging Human-Centered Social Media Content across Web Domains
Suman Deb Roy, Tao Mei, and Wenjun Zeng

Learning Social Relations from Videos: Features, Models and Analytics
Lei Ding and Alper Yilmaz

Community Understanding in Location-Based Social Networks
Yi-Liang Zhao, Qiang Cheng, Shuicheng Yan, Daqing Zhang, and Tat-Seng Chua

Social Role Recognition for Human Event Understanding
Vignesh Ramanathan, Bangpeng Yao, and Li Fei-Fei

Integrating Randomization and Discrimination for Classifying Human-Object Interaction Activities
Aditya Khosla, Bangpeng Yao, and Li Fei-Fei

Part II: Human Attributes in Social Media Analytics

Recognizing People in Social Context
Gang Wang, Andrew Gallagher, Jiebo Luo, and David Forsyth

Female Facial Beauty Attribute Recognition and Editing
Jinjun Wang, Yihong Gong, and Douglas Gray

Facial Age Estimation: A Data Representation PerspectiveXin Geng

Identity and Kinship Relations in Group Pictures
Ming Shao, Siyu Xia, and Yun Fu

Recognizing Occupations through Probabilistic Models: A Social View
Ming Shao and Yun Fu

Blurb

Utilizing the ubiquity of social media in modern society, the emerging interdisciplinary field of social computing offers the promise of important human-centered applications. 

Human-Centered Social Media Analytics provides a timely and unique survey of next-generation social computational methodologies. The text explains the fundamentals of this field, and describes state-of-the-art methods for inferring social status, relationships, preferences, intentions, personalities, needs, and lifestyles from human information in unconstrained visual data. The collected chapters present a range of different viewpoints examining the various possibilities and challenges to machine understanding of humans in a social context.

Topics and features:

• Includes perspectives from an international and interdisciplinary selection of pre-eminent authorities
• Presents balanced coverage of both detailed theoretical analysis and real-world applications
• Examines social relationships in human-centered media for the development of socially-aware video, location-based, and multimedia applications
• Reviews techniques for recognizing the social roles played by people in an event, and for classifying human-object interaction activities
• Discusses the prediction and recognition of human attributes via social media analytics, including social relationships, facial age and beauty, and occupation
• Requires no prior background knowledge of the area

This authoritative text/reference will be a valuable resource for researchers and graduate students interested in social media and networking, computer vision and biometrics, big data, and HCI. Practitioners in these fields, as well as in image processing and computer graphics, will also find the book of great interest.

Dr. Yun Fu is an assistant professor in the Department of  Electrical and Computer Engineering at Northeastern University, Boston, MA, USA, where he is the founder of the Synergetic Media Learning (SMILE) Lab.