Rasim M. Alguliyev, Irada Y. Alakbarova

The intense and dynamic impact of information technology on everyday life and the behavior of citizens has led to the emergence of new social relations in society and certain changes in traditional relations. Each state has its own structure of relations between citizens. Analysis and classification of social relations in society are important for the effective management of economic development and security of the electronic state (e-government). The aim of the study is to identify the role of social relations in the formation of the e- government and develop proposals for the effectiveness of the analysis of social relations. The article explores some approaches and information systems used in the analysis of social relations, classifies social relations by nature, form and type. For effective management and evaluation of social relations, a categorical solution diagram was developed and it was proposed to analyze social relations using subnets. The study used a systematic approach, graph theory and comparative analysis methods. The results obtained in the article can be used to manage e-government more effectively (pp.65-79).

Keywords:e-state, social relations, cyber-physical systems, social groups, graph theory, Relationship Science, Traxor, Brand Analytics.
DOI : 10.25045/jpis.v11.i2.06
  • Əliquliyev R.M., Alıquliyev R.M., Ələkbərova İ.Y. Elektron dövlət mühitində sosial münasibətlərin təhlükəsizliyi “İnformasiya təhlükəsizliyinin aktual multidissiplinar elmi-praktiki problemləri” IV Respublika konfransı, Bakı, 14 dekabr, 2018. s. 64–67.
  • Rajkumar R. A Cyber-Physical Future / Proceedings of the IEEE, vol. 100, issue: Special Centennial Issue, 13 may, 2012, pp. 1309–1312.
  • Berscheid E. The greening of relationship science // American Psychologist, 1999, vol. 54, no. 4, pp. 260–266.
  • Козлов Н.И. Общение,
  • Peng J., Quan J., Zhang G., Dubinsky A.J. Knowledge Sharing, Social Relationships, and Contextual Performance: The Moderating Influence of Information Technology Competence // Organizational and End User Computing, 2015, vol. 27, no. 2, pp. 58–73.
  • Fiske A.P. The Four Elementary Forms of Sociality: Framework for a Unified Theory of Social Relations // Psychological Review, 1992, no. 99, pp. 689–723.
  • Moreno J.L., Jennings H.H. Statistics of social configurations // Sociometry, 1938, pp. 342–374.
  • Scott J. Social Network Analysis: A Handbook, SAGE Publications, 2000, 208 p.,
  • Əliquliyev R.M., Ələkbərova İ.Y. Sosial informatika: sosial proseslərin analizində informasiya texnologiyalarinin tətbiqi // İnformasiya cəmiyyəti problemləri. 2019, №2, səh. 3-13.
  • Dunbar R.I. How Many Friends Does One Person Need?: Dunbar's Number and Other Evolutionary Quirks, 2010, Fader and Fader limited, 302 p.
  • Smith A. What people like and dislike about Facebook, 2014,
  • Əliquliyev R.M., Mahmudov R.Ş. İnternet cəmiyyətin inkişafinın hərəkətverici qüvvəsi kimi // İnformasiya cəmiyyəti problemləri, 2016, №1, səh. 35-45.
  • Granovetter M. The Strength of Weak Ties // American Journal of Sociology, 1973, vol. 78, pp. 1360–1380.
  • Perer A., Guy I., Uziel E., Ronen I., Jacovi M. Visual social network analytics for relationship discovery in the enterprise / Proceedings of the IEEE Conference on Visual Analytics Science and Technology, 23–28 oct. 2011, Providence, RI, USA, pp. 71–79.
  • Relationship Science,
  • Brand Analytics
  • Ильин Е.П. Психология общения и межличностных отношений. СПб.: Питер, 2009, 576 с.
  • Li K., Zhang L., Huang H. Social Influence Analysis: Models, Methods, and Evaluation // Engineering, 2018, vol. 4, issue 1, pp. 40–46.
  • Collins R. The Sociology of Philosophies: A Global Theory of Intellectual Change. 1998, Cambridge MA and London: Harvard University Press,. 1120 pp.
  • Gillath O., Adams G.,  Kunkel A. Relationship Science: Integrating Evolutionary, Neuroscience, and Sociocultural Approaches 2012, Washington, American Psychological Association, 254 p.
  • Carolan B. Strong Ties, Weak Ties: Relational Dimensions of Learning Settings, 2006, EdLab, Teachers College, Columbia University, 25 p.
  • Sanaz K., Zuraini I., Bharanidharan Sh. Differences between Role of Strong Ties and Weak Ties in Information Diffusion on Social Network Sites // Advanced Research and Trends in New Technologies, Software, Human-Computer Interaction, and Communicability, 2014, chap. 28, pp. 307-311.
  • Lin N. Social Resources and Occupational Status Attainment. 1990, Social Mobility and Social Structure. N.Y.: Cambridge University Press. pp. 247-271.
  • Aguilar-Raab C., Grevenstein D., Schweitzer J. Measuring Social Relationships in Different Social Systems: The Construction and Validation of the Evaluation of Social Systems (EVOS) Scale, 2015, journal.pone.0133442
  • Coleman J.S. Social Capital in the Creation of Human Capital // American Journal of Sociology, 1988, vol. 94. pp. 95-120.
  • Wasserman S., Faust K. Social Network Analysis: Methods and Applications, 1994, Cambridge University Press, 825 p.
  • Frazzon M., Hartmann J., Makuschewitz T., Scholz-Reiter B. Socio-Cyber-Physical Systems in Production Networks // Procedia CIRP, 2013, vol. 7, pp. 49-54.
  • Department of Economic and Social Affairs, Report, BACK-GROUND-PAPER.SDGs1611.FINAL_.pdf.
  • Frazzona E.M., Hartmannb J., Makuschewitzb T., Scholz-Reiterc B. Towards Socio-Cyber-Physical Systems in Production Networks / Proceedings of the Forty Sixth CIRP Conference on Manufacturing Systems, 2013, pp. 49-54.
  • Hyvärinen A., Karhunen , Oja E. Independent Component Analysis. 2001, John Wiley & Son, 476 p.
  • Zhang L., Cai Z., Lu J., Wang X. Mobility-Aware Routing in Delay Tolerant Networks // Personal and Ubiquitous Computing, 2015, vol. 19, issue 7, pp. 1111-1123.
  • Mtibaa A., May M., Diot C., Ammar M. PeopleRank: Social Opportunistic Forwarding / Proceedings of the IEEE INFOCOM, San Diego, CA, USA. 14–19 march, 2010, pp. 1-5.
  • Nusratullah K., Khan S.A., Shah A., Butt W.H. Detecting Changes in Context using Time Series Analysis of Social Network / Proceedings of the SAI Intelligent Systems Conference, IEEE, 2015, London, pp. 996-1001.
  • Фролов Ю.Н., Габышева Л.К.. Социальные сети: теория и практика. Тюм.ГНГУ, 2012, 140 c.,
  • F., Zhao N., Li W., Effective Social Relationship Measurement and Cluster Based Routing in Mobile Opportunistic Networks // Sensors, 2017, vol. 17, no. 5, 19 p.
  • Akhtar M.M., Zamani A.S., El-Sayed A. Link Analysis using Data Mining System // Applied Research in Computer Science and Information Technology, 2012, vol. 1, no 2, pp. 38-49.
  • Liu D.W., Zhang Z.L.,Guo X.H. Web mining based on one-dimensional Kohonen's algorithm: analysis of social media websites // Neural Computing & Applications, 2017, vol. 28, pp. S641-S645.
  • Getoor L. Link mining: A new data mining challenge // ACM SIGKDD Explorations Newsletter, 2003, no. 5, pp. 84-89.
  • Agarwal S., Sureka A. Using KNN and SVM Based One-Class Classifier for Detecting Online Radicalization on Twitter / Proceedings of the International Conference on Distributed Computing and Internet Technology, ICDCIT 2015: Distributed Computing and Internet Technology, pp. 431-442.
  • Alguliyev R.M., Aliguliyev R.M., Alakbarova I.Y. Extraction of hidden social networks from wiki-environment involved in information conflict // Intelligent Systems and Applications (IJISA), 2016, vol. 8, no. 2, pp.20-27.
  • Park J., Lee J., Kim S. K., Jang K., Yang S-B. A forwarding scheme based on swarm intelligence and percolation centrality in opportunistic networks // Wireless Networks, 2016, vol. 22, no. 8, pp. 2511-2521.
  • Лакеев А.В. Элементы теории обыкновенных графов. Изд.: ИГУ, 2014. 83 с.
  • Schleicher D.J., Smith T.A., Casper W.J., Watt J.D., Greguras G.J. It’s all in the attitude: the role of job attitude strength in job attitude–outcome relationships // Applied Psychology, 2015. vol. 100, no. 4, pp. 1259-1274.
  • Zhou L., Lu Y., Vitale C.J., Mar P.L., Chang F., Dhopeshwarkar N., Rocha R.A. Representation of Information about Family Relatives as Structured Data in Electronic Health Records // Applied Clinical Informatics. 2014, vol. 5, no. 2, pp. 349-367.
  • Batagelj V., Mrvar A. Analysis of Kinship Relations With Pajek // Social Science Computer Review, 2008, vol. 26. issue. 2, pp. 224-246.
  • Erd ̋os P., R ́enyi A., S ́os V. On a problem of graph theory // Studia Scientiarum Mathematicarum Hungarica, 1966, vol.1, pp. 215-235.
  • Mertzios G.B., Unger W., The Friendship Problem on Graphs // Journal of Multiple-Valued Logic and Soft Computing, 2016, vol. 27, pp. 275-285.
  • Oldenburg B., Duijn M.V., Veenstra R. Defending one's friends, not one's enemies: A social network analysis of children's defending, friendship, and dislike relationships using XPNet // PLoS ONE, 2018ç vol. 13, issue 5, pp. 1-14.
  • Vaquera E, Kao G. Do you like me as much as I like you? Friendship reciprocity and its effects on school outcomes among adolescents // Social Science Research, 2008, vol. 37, no. 1. pp. 55-72.
  • Tur-Kaspa H, Margalit M, Most T. Reciprocal friendship, reciprocal rejection and socio-emotional adjustment: the social experiences of children with learning disorders over a one-year period // European Journal of Special Needs Education, 1999, vol. 14, no. 1, pp. 37-48.