Alexander Troussov and Sergey Maruev (The Russian Presidential Academy of National Economy and Public Administration)
Nowadays, most of the digital content is generated within public and enterprise techno-social systems like Facebook, Twitter, blogs, wiki systems, and other web-based collaboration and hosting tools, office suites, and project management tools. Enterprises use software tools for social collaboration and team collaboration, such as Microsoft SharePoint, IBM Lotus Notes and others. These applications have transformed the collaboration environment from a mere document collection into a highly interconnected social space, where documents are actively exchanged, filtered, organized, discussed and edited collaboratively. In techno-social systems infrastructures are composed of many layers (such as Internet communication protocols, markup languages, metadata models, knowledge representation languages which have spanned over two decades) and interoperate within a social and organizational context that drives their everyday use and development. Proprietary data bases, such as customs records, contrary to the log-files of techno-social systems, frequently have data about the collaboration which happens between actors outside of the systems. By extension, we can apply the term techno-social systems to both types of data. Such generalisation simplifies knowledge transfer between different domains and types of applications.
In these techno-social systems “everything is deeply intertwingled” using the term coined by the pioneer of information technologies Ted Nelson: people are connected to other people and to “non-human agents” such as documents, datasets, analytic tools and concepts. These networks become increasingly multidimensional, providing rich context for understanding the role of particular nodes that represent both people and abstract concepts.
Techno-social systems bear most of the general characteristics of Big Data; for instance, in these systems, it is frequently easier to predict agents’ actions than to explain them. Mining of techno-social systems constitutes a new distinctive branch of Business Information Systems.
This book covers theoretical and practical aspects of mining techno-social systems which have potential for the creation of scalable methods and applications for business, governance and economics. Typically, off-the-shelf business intelligence tools do not meet the needs of clients who want to derive custom insights from their data. Medium-to-large organizations with access to strong technical talent usually prefer to build custom, in-house solutions. This book is a do-it-your-yourself guide for building in-house solutions.
Techno-social systems and their use in business, economy and governance:
Geographical and Internet demography
Mining of large volumes of governance-based records and other tabular data
Models and formal methods of analysis
Natural Language Engineering
Artificial Intelligence, Machine learning
Neural network frameworks
Network models, network science
Foundations of network science
Survey of artificial neural networks applications for non-sensor data processing
Recommender and advertising systems, data navigation
Engineering and epistemological approaches in Big data:
Semantic Web, Social Web
Big data engineering aspects
In-field case studies, applications
Health care and environmental applications
Internet sociology and demographics
The use of social media to fight crimes
Models of corruption
September 10, 2017: Proposal Submission Deadline
October 9, 2017: Full Chapter Submission
November 5, 2017: Final Chapter Submission
Deadlines are extended, information on the publisher’s website will be updated shortly
Alexander Troussov, Ph.D.
Director of the International Research Laboratory for Mathematical Methods for Social Network Mining at The Russian Presidential Academy of National Economy and Public Administration.
Publication costs nothing, All published chapter WILL BE indexed by SCOPUS