Dmitry A. Gubanov

E-Expertise: Modern Collective Intelligence

This book focuses on organization and mechanisms of expert decision-making support using modern information and communication technologies, as well as information analysis and collective intelligence technologies (electronic expertise or simply e-expertise). Chapter 1 (E-Expertise) discusses the role of e-expertise in decision-making processes. The procedures of e-expertise are classified, their benefits and shortcomings are identified and the efficiency conditions are considered. Chapter 2 (Expert Technologies and Principles) provides a comprehensive overview of modern expert technologies. A special emphasis is placed on the specifics of e-expertise. Moreover, the authors study the feasibility and reasonability of employing well-known methods and approaches in e-expertise. Chapter 3 (E-Expertise: Organization and Technologies) describes some examples of up-to-date technologies to perform e-expertise. Chapter 4 (Trust Networks and Competence Networks) deals with the problems of expert finding and grouping by information and communication technologies. Chapter 5 (Active Expertise) treats the problem of expertise stability against any strategic manipulation by experts or coordinators pursuing individual goals. The book addresses a wide range of readers interested in management, decision-making and expert activity in political, economic, social and industrial spheres.

Informational influence and informational control models in social networks

We model the forming and dynamics of opinions in a social network with Markov chains. We set and solve, for a number of special cases, the problems of controlling agent opinions and game-theoretic problems of informational conflict.

A conceptual approach to online social networks analysis

This paper introduces a constructive approach to online social networks analysis. We suggest a conceptual model of a social network, formulate major problems of analysis and control in social networks, describe methods and algorithms for activity analysis in social networks, as well as technologies for social networks monitoring and analysis.

Game-theoretic models of informational confrontation in social networks

Several models are considered to illustrate feasibility and appropriateness of involving the game theory framework in describing the process and result of informational confrontation in social networks.

An actional model of user influence levels in a social network

This paper suggests a new approach to the constructive definition of user influence levels in social networks—the so-called actional model. According to the approach, the influence level of a user is calculated on the basis of their actions taking into account the goals of a control subject (a Principal). An example illustrates how the actional model can be applied to find the influence level of users in a real social network on the assumption of available initial data.

Language games in investigation of social networks: Finding communities and influential agents

The paper presents an investigation method of social networks based on language games. This method is used for finding implicit communities and influential agents in social networks. The authors introduce a naming game and explain how it is applied in investigation of social networks. Simulation results are demonstrated for specially designed graphs and a real-data graph. The authors also survey alternative methods of community detection and compare them with the above-mentioned method.

Influence Levels of Users and Meta-Users of a Social Network

This paper considers an extension of the actional model of influence in online social networks. Within the framework of this model, the influence and influence levels of separate agents (users) and meta-agents (subsets of users) are calculated on the basis of their actions taking into account the goals of a control subject (a Principal). We study some properties of the influence function. An example illustrates how the actional model can be used to calculate the influence levels of users in a concrete social network under available initial data.

Expert Technologies and Principles

This chapter pretends to be a navigator over expert technologies. It describes the basic stages and methods of expertise, methods of expert grouping, typical errors, as well as the general technology of expertise organization and its principles. Finally, we discuss some prediction problems. The exposition par excellence proceeds from generalization of well-known classical statements (see the theory of expert appraisals) with emphasizing the specifics of e-expertise.

E-Expertise: Organization and Technologies

Figure 3.1 demonstrates the institutional organization of e-expertise. In what follows, we discuss it in detail, i.e., provide a list of feasible technologies, study different forms such as polling, electronic brainstorming, etc.

Trust Networks and Competence Networks

Expert finding for specific e-expertise is a multidisciplinary problem at the junction of strategic analysis, decision-making theory, synergy, inverse problem solution, human capital and emotional potential assessment, motivation control, quantum semantics, knowledge management, organizational analysis, information retrieval (acquisition, indexing, storage of artefacts and other evidence of expert knowledge), and analysis of social and organizational networks. It seems often difficult or even impossible to localize potential experts in an organization. The reasons consist in very many employees of an organization, its functionally and/or geographically dispersed character. What is more important, problem solving may require inviting experts from related or totally different subject domains.