Public survey instruments for business administration using social network analysis and big data
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 t...
Main Authors: | , , |
---|---|
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Eleftherios Thalassinos
2020
|
Subjects: | |
Online Access: | https://www.um.edu.mt/library/oar/handle/123456789/54649 |
id |
ftunivmalta:oai:www.um.edu.mt:123456789/54649 |
---|---|
record_format |
openpolar |
spelling |
ftunivmalta:oai:www.um.edu.mt:123456789/54649 2023-05-15T15:12:22+02:00 Public survey instruments for business administration using social network analysis and big data Kolmakov, V. V. Rudneva, L. N. Thalassinos, Y. E. 2020 https://www.um.edu.mt/library/oar/handle/123456789/54649 en eng Eleftherios Thalassinos Kolmakov, V. V., Rudneva, L. N., Thalassinos, Y. E. (2020). Public survey instruments for business administration using social network analysis and big data. International Journal of Economics and Business Administration, 8(2), 3-18. 22414754 https://www.um.edu.mt/library/oar/handle/123456789/54649 info:eu-repo/semantics/openAccess The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. Industrial management Industrial management -- Data processing Industrial management -- Social aspects Industrial management -- Research article 2020 ftunivmalta 2021-10-16T18:06:19Z 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. peer-reviewed Article in Journal/Newspaper Arctic University of Malta: OAR@UM Arctic |
institution |
Open Polar |
collection |
University of Malta: OAR@UM |
op_collection_id |
ftunivmalta |
language |
English |
topic |
Industrial management Industrial management -- Data processing Industrial management -- Social aspects Industrial management -- Research |
spellingShingle |
Industrial management Industrial management -- Data processing Industrial management -- Social aspects Industrial management -- Research Kolmakov, V. V. Rudneva, L. N. Thalassinos, Y. E. Public survey instruments for business administration using social network analysis and big data |
topic_facet |
Industrial management Industrial management -- Data processing Industrial management -- Social aspects Industrial management -- Research |
description |
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. peer-reviewed |
format |
Article in Journal/Newspaper |
author |
Kolmakov, V. V. Rudneva, L. N. Thalassinos, Y. E. |
author_facet |
Kolmakov, V. V. Rudneva, L. N. Thalassinos, Y. E. |
author_sort |
Kolmakov, V. V. |
title |
Public survey instruments for business administration using social network analysis and big data |
title_short |
Public survey instruments for business administration using social network analysis and big data |
title_full |
Public survey instruments for business administration using social network analysis and big data |
title_fullStr |
Public survey instruments for business administration using social network analysis and big data |
title_full_unstemmed |
Public survey instruments for business administration using social network analysis and big data |
title_sort |
public survey instruments for business administration using social network analysis and big data |
publisher |
Eleftherios Thalassinos |
publishDate |
2020 |
url |
https://www.um.edu.mt/library/oar/handle/123456789/54649 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_relation |
Kolmakov, V. V., Rudneva, L. N., Thalassinos, Y. E. (2020). Public survey instruments for business administration using social network analysis and big data. International Journal of Economics and Business Administration, 8(2), 3-18. 22414754 https://www.um.edu.mt/library/oar/handle/123456789/54649 |
op_rights |
info:eu-repo/semantics/openAccess The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. |
_version_ |
1766343061192835072 |