Public Survey Instruments for Business Administration Using Social Network Analysis and Big Data

• Main Authors: V.V. Kolmakov, L.N. Rudneva, Y.E. Thalassinos
• Format: Article in Journal/Newspaper
• Language: unknown
• Subjects: Arctic
• Online Access: https://www.ijeba.com/journal/440/download

Purpose: The subject matter of this research is closely intertwined with the scientific discussion about the necessity of developing and implementing practice-oriented means of measuring social well-being taking into account the intensity of contacts between individuals. The aim of the research is to test the toolkit for analyzing social networks and to develop a research algorithm to identify sources of consolidation of public opinion and key agents of influence. The research methodology is based on postulates of sociology, graph theory, social network analysis and cluster analysis. Design/Methodology/Approach: The basis for the empirical research was provided by the data representing the reflection of social media users on the existing image of Russia and its activities in the Arctic, chosen as a model case. Findings: The algorithm allows to estimate the density and intensity of connections between actors, to trace the main channels of formation of public opinion and key agents of influence, to identify implicit patterns and trends, to relate information flows and events with current information causes and news stories for the subsequent formation of a "cleansed" image of the object under study and the key actors with whom this object is associated. Practical Implications: The work contributes to filling the existing gap in the scientific literature, caused by insufficient elaboration of the issues of applying the social network analysis to solve sociological problems. Originality/Value: The work contributes to filling the existing gap in the scientific literature formed as a result of insufficient development of practical issues of using analysis of social networks to solve sociological problems. Sociological research, public opinion, big data, social space, social networks.