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The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields.

Intro -- Acknowledgments -- Introduction -- Chapter Overview -- Terminology and Definitions -- Attributes -- Privacy Settings of Attributes -- Risk Sources -- Data Inference -- Threat -- Privacy Harm -- Privacy Risks -- Privacy Risk Analysis -- Dimensions of Privacy Scoring in OSNs -- Type of Data -- Assumptions About the User -- Privacy Settings -- Risk Sources -- Privacy Metrics -- Sensitivity -- Visibility -- Reachability -- Data Inference -- Suggestion of Countermeasures -- Attribute Visibility in OSN -- Visibility Matrix -- Construction of Visibility Matrix -- An Illustration -- Open Problems -- Harm Trees for OSNs -- Harm Trees -- Construction of Harm trees -- Harm Likelihood -- Harm Expressions -- Harm Database -- Open Problems -- Privacy Risk Analysis in OSNs -- An Overview -- PrivOSN in Details -- Computation of Accuracy -- Evaluation of Harm Likelihoods -- Computation Profile Similarity -- Presentation of Privacy Risk to the User -- Residual Risks -- Open Problems -- Social Benefits -- Social Ties -- Social Capital -- Understanding Social Benefits -- Social Benefit Criteria -- Attributes and Social Benefit Criteria -- Evaluation of Social Benefit -- Open Problems -- Choosing the Right Privacy Settings -- Privacy and Social Benefit Tradeoff in Privacy Management -- An Integer Programming Model -- Balancing Privacy Risks and Social Benefits -- Formulation of the IP Problem -- Objective Function -- Privacy Risk Constraints -- Social Benefit Constraints -- Privacy Setting Constraints -- Open Problems -- Conclusion -- Notations and Their Meanings -- Comparison of Privacy Scoring Mechanisms -- Cases 3 and 4 -- Bibliography -- Authors' Biographies -- Blank Page.

"Following the introduction of Myspace, Linkedin and Facebook, social networks have become part of people's everyday life. New online social networks appear almost daily developed to attract the attention of Internet users. However, design and implementation standards and guidelines are often sacrificed for innovation resulting in unusable social networking platforms destined to be doomed. Within this context, the present book recommends a design and implementation methodology which will allow future social networking platform designers and developers to work in a scientifically systematic and sound manner to reach their goal. The journey begins with the identification of the pursued objective of the social network and the potential participants. The presentation of various methods and techniques to collect the requirements of the intended user group of the social networking platform follows. Best practices, guidelines and standards that will facilitate the conceptual and physical design of the platform are portrayed. An analysis of advantages and limitations for existing implementation platforms and potential implementation techniques is subsequently offered to facilitate the selection of the most appropriate tool for the implementation of the online social networking website. Various representative visualization techniques are examined in order to enhance the visual representation of the social network participants. Various usability evaluation techniques are then presented to aid in the assessment of usability and improvement of the actual user experience. Finally, future trends in the design and use of social networks are presented."--Publisher's website.

This book provides insights into the structural properties of personal online social networks and the mechanisms underpinning human online social behavior. As the availability of digital communication data generated by social media is revolutionizing the field of social networks analysis. It discusses the use of large- scale datasets to study the structural properties of online ego networks, to compare them with the properties of general human social networks, and to highlight additional properties. Users will find the data collected and conclusions drawn useful during design or research service initiatives that involve online and mobile social network environments. It presents quantitative evidence of the Dunbar's number in online environments and discusses original structural and dynamic properties of human social network through OSN analysis. --

The fourth revolution -- The new social norms -- How relationships and social capital are changing -- Social networking across your organization -- Sales in the facebook era -- Customer service in the facebook era -- Marketing in the facebook era -- Innovation and collaboration in the facebook era -- Recruiting in the facebook era -- Step-by-step guide to social networking for business -- How to : develop your facebook era plan and metrics -- How to : build and manage relationships on the social web -- How to : engage customers with facebook pages and twitter -- How to : advertise and promote on the social web -- Social networking strategy -- Advice for small business -- Advice for nonprofits, healthcare, education, and political campaigns -- Corporate governance, strategy, and implementation -- The future of social business

Chapter 1 - Introduction: Mediated Accounts of Graduate Education and Advising Relationships among US Korean Graduate Students Chapter 2 - Mediated Accounts of Institutional Matters upon Advising Relationships Chapter 3 - Mediated Accounts of Academic Matters upon Advising Relationships Chapter 4 - Mediated Accounts of Cultural Matters upon Advising Relationships Chapter 5 - Mediated Accounts of Social Matters upon Advising Relationships Chapter 6 - Conclusions and Implications Notes Bibliography Index