Indicators of Ego-centric Networks: Systematic Review

Document Type : Research ŮŽ Article

Authors

1 Ph.D. Candidate in Knowledge and Information Science, Faculty of Education and Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran

2 Associate Professor of Knowledge and Information Science Group, Faculty of Education and Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran

3 Assistant Professor of Information Management Group, Islamic World Science & Technology Monitoring and Citation Institute(ISC), Shiraz, Iran

4 Assistant Professor of Knowledge and Information Science Group, Faculty of Education and Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran

10.30484/nastinfo.2023.3479.2239

Abstract

Purpose: The purpose of this study was to systematically examine dimensions and categorize the indicators of ego-centric networks in the literature to create a basis for evaluating the performance of scientific outputs or networks of people
Method: The current research was done with an analytical approach and a systematic review method. The steps of data search and analysis in this study were developed based on the standard guidelines of Prisma. For this purpose, 23 researches related to EGO network indicators from 2003 to 2023 have been presented in the core collection of Science, Scopus, and IEEE websites after refining the results. Moreover, in all three databases, restrictions on the type of documents (articles and books), period (2003 to May 22, 2023), and language (English) were applied.
Findings: The reviewed studies have identified three levels of ego network indicators according to structural and combined characteristics in the form of 21 indicators: ego-alter ties indicators, alter attributes indicators, and Alter-alter ties. Four indicators of ego-alter ties include network size, Multiplexity, Tie Strength, and Tie Dispersion, which show different dimensions of relationships between the central entity (ego) and alters. The indicators related to the altered attributes in the ego network include six indicators of network composition: ego-alter similarity, heterogeneity, alter centrality, altered dispersion, and geographical dispersion. Two common social sciences concepts, social capital, and social support, can be defined and calculated as a subset of the combination criterion. Eleven indicators in the category of alter-alter ties include density, number, and size of components, Burt's Structural Hole Measures (four measures of effective size, Constraint, efficiency, and hierarchy are proposed to calculate this index), Gould and Fernandez Brokerage, Ego betweenness index, Degree centrality, closeness centrality, Alter Betweenness centrality, cliques, number of isolates nodes and Core-periphery. Some network structural metrics are graph-based and based on graph theory. Among others, we can refer to density, closeness centrality, degree centrality, alter Betweenness centralization, cliques, number of isolates nodes, and Core-periphery. When applied to personal networks, these metrics typically have a particular meaning and interpretation, especially if the ego is excluded. These meanings are different from their socio-centric network meaning.
Conclusion: Several kinds of research have been conducted on ego-centric networks, each dealing with some specific number of criteria related to the characteristics of these networks, and have tried to be a basis for evaluating the performance of the networks. Research gaps we identified in this field include reviewing the software required to implement the indicators and how to illustrate, validate, and apply these indicators in scientometrics, science evaluation, and technology research and policy.

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References

Abbasi, A., Chung, K. S. K., & Hossain, L. (2012). Egocentric analysis of co-authorship network structure, position, and performance. Information Processing & Management, 48(4): 671-679.
Ahuja, G. (2000). Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45(3): 425-455.
An, W., Beauvile, R., & Rosche, B. (2022). Causal network analysis. Annual Review of Sociology, 48(3): 23-41.
Bidart, C., Degenne, A., & Grossetti, M. (2018). Personal networks typologies: A structural approach. Social Networks, 54(2): 1-11.
Borgatti, S. P., & Everett, M. G. (2006). A graph-theoretic perspective on centrality. Social Networks, 28(4): 466-484.
Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2018). Analyzing Social Networks. Sage Publications.
Borgatti, S. P., Jones, C., & Everett, M. G. (1998). Network measures of social capital. Connections, 21(2): 27-36.
Burt, R. S. (2004). Structural holes and good ideas. American Journal of Sociology, 110(2): 349-399.
Burt, Ronald S. (1992). Structural Holes: The Social Structure of Competition. Harvard University Press.
Burt, R. S., & Minor, M. J. (1983). Applied network analysis: A methodological introduction. Newcastle: Sage.
Carrasco, J. A., Hogan, B., Wellman, B., & Miller, E. J. (2008). Collecting social network data to study social activity-travel behavior: an egocentric approach. Environment and Planning B: Planning and Design, 35(6): 961-980.
Campbell, K. E., Marsden, P. V., & Hurlbert, J. S. (1986). Social resources and socioeconomic status. Social Networks, 8(1): 97-117.
Christakis, N. A., & Fowler, J. H. (2007). The spread of obesity in a large social network over 32 years. New England Journal of Medicine, 357(4): 370-379.
Chung, K. S. K., Hossain, L., & Davis, J. (2005) Exploring Sociocentric and Egocentric Approaches for Social Network Analysis. International Conference on Knowledge Management Asia Pacific, Victoria University Wellington, New Zealand, November 27-29: pp. 1-8.
Cross, R., & Cummings, J. N. (2004). Tie and network correlates of individual performance in knowledge-intensive work. Academy of Management Journal, 47(6): 928-937.
Crossley, N., Bellotti, E., Edwards, G., Everett, M. G., Koskinen, J., & Tranmer, M. (2015). Social network analysis for ego-nets: Social network analysis for actor-centred networks. Newcastle: Sage.
DeJordy, R., & Halgin, D. (2008) Introduction to ego network analysis. Boston, MA: Boston College and the Winston Center for Leadership and Ethics, Academy of Management PDW. http://www.analytictech.com/enet/pdwhandout.pdf
Djomba, J. K., & Zaletel-Kragelj, L. (2016). A methodological approach to the analysis of egocentric social networks in public health research: a practical example. Slovenian Journal of Public Health, 55(4): 256-263.
Edwards, G., & Crossley, N. (2009). Measures and meanings: Exploring the ego-net of Helen Kirkpatrick Watts, militant suffragette. Methodological Innovations Online, 4(1): 37-61.
Everett, M. G., & Borgatti, S. P. (2020). Unpacking Burt's constraint measure. Social Networks, 62(2): 50-57.
Fowler, J. H., & Christakis, N. A. (2008). Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study. The BMJ [British Medical Association], 337 (a2338): 1-9.
Freeman, L. C. (1982). Centered graphs and the structure of ego networks. Mathematical Social Sciences, 3(3): 291-304.
Froehlich, D. E., & Brouwer, J. (2021). Social network analysis as mixed analysis. In: Anthony J. Onwuegbuzie and Burke Johnson (editors), The Routledge Reviewer's Guide to Mixed Methods Analysis (pp. 209-218). Routledge.
Giannella, E., & Fischer, C. S. (2016). An inductive typology of egocentric networks. Social Networks, 47(1): 15-23.
Gould, R. V., & Fernandez, R. M. (1989). Structures of mediation: A formal approach to brokerage in transaction networks. Sociological Methodology, 3(2): 89-126.
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380.
Halgin, D. S., & Borgatti, S. P. (2012). An introduction to personal network analysis and tie churn statistics using E-NET. Connections, 32(1): 37-48.
Herz, A., & Petermann, S. (2017). Beyond interviewer effects in the standardized measurement of ego-centric networks. Social Networks, 50(1): 70-82.
Hogan, B., Carrasco, J. A., & Wellman, B. (2007). Visualizing personal networks: Working with participant-aided sociograms. Field Methods, 19(2): 116-144.
Huang, Y., Bu, Y., Ding, Y., & Lu, W. (2018). Number versus structure: towards citing cascades. Scientometrics, 117(3): 2177-2193.
Kim, D. Y., & Kim, H. Y. (2021). Trust me, trust me not: A nuanced view of influencer marketing on social media. Journal of Business Research, 134(4): 223-232.
Lubbers, M. J., Molina, J. L., Lerner, J., Brandes, U., Ávila, J., & McCarty, C. (2010). Longitudinal analysis of personal networks. The case of Argentinean migrants in Spain. Social Networks, 32(1): 91-104.
Marin, A., & Hampton, K. N. (2007). Simplifying the personal network name generator: Alternatives to traditional multiple and single name generators. Field Methods, 19(2): 163-193.
Marsden, P. V., & Campbell, K. E. (1984). Measuring tie strength. Social Forces, 63(2): 482-501.
McCarty, C., Lubbers, M. J., Vacca, R., & Molina, J. L. (2019). Conducting Personal Network Research: A Practical Guide. Guilford Publications.
McCarty, C., & Wutich, A. (2005). Conceptual and empirical arguments for including or excluding ego from structural analyses of personal networks. Connections, 26(2): 82-88.
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of Internal Medicine, 151(4): 264-269.
O'Malley, A. J., Arbesman, S., Steiger, D. M., Fowler, J. H., & Christakis, N. A. (2012). Egocentric social network structure, health, and pro-social behaviours in a national panel study of Americans. PloS One, 7(5): e36250
Park, N., Lee, S., & Kim, J. H. (2012). Individuals' personal network characteristics and patterns of Facebook use: A social network approach. Computers in Human Behaviour, 28(5), 1700-1707.
Perry, B. L., Pescosolido, B. A., & Borgatti, S. P. (2018). Egocentric Network Analysis: Foundations, Methods, and Models (Structural Analysis in the Social Sciences, Vol. 44). Cambridge University Press.
Pescosolido, B. A. (2006). Of pride and prejudice: the role of sociology and social networks in integrating the health sciences. Journal of Health and Social Behaviour, 47(3): 189-208.
Pescosolido, B. A. (1991). Illness careers and network ties: A conceptual model of utilization and compliance. Advances in Medical Sociology, 2(16): 164-181.
Pescosolido, B. A., & Rubin, B. A. (2000). The web of group affiliations revisited: Social life, postmodernism, and sociology. American Sociological Review, 2(3): 52-76.
Rajkumar, K., Saint-Jacques, G., Bojinov, I., Brynjolfsson, E., & Aral, S. (2022). A causal test of the strength of weak ties. Science, 377(6612): 1304-1310.
Rodan, S., & Galunic, C. (2004). More than network structure: How knowledge heterogeneity influences managerial performance and innovativeness. Strategic Management Journal, 25(6): 541-562.
Scott, J. (2012). Social Network Analysis, edited by Katie Metzler. Thousand Oaks, CA: Sage Publications.
Skotko, B. G., Krell, K., Haugen, K., Torres, A., Nieves, A., & Dhand, A. (2023). Personal social networks of people with Down syndrome. American Journal of Medical Genetics Part A, 191(3): 690-698.
Stolz, S., & Schlereth, C. (2021). Predicting tie strength with ego network structures. Journal of Interactive Marketing, 54(1): 40-52.
Tamil Selvi, P., Balasubramaniam, K., Vidhya, S., Jayapandian, N., Ramya, K., Poongodi, M., Hamdi, M., & Tunze, G. B. (2022). Social network user profiling with multilayer semantic modeling using ego network. International Journal of Information Technology and Web Engineering (IJITWE), 17(1): 1-14.
Vacca, R., Solano, G., Lubbers, M. J., Molina, J. L., & McCarty, C. (2018). A personal network approach to the study of immigrant structural assimilation and transnationalism. Social Networks, 53(1): 72-89.
Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge: Cambridge University Press.
Wellman, B. (1999). Networks in the Global Village. Boulder, CO: Westview Press
Wielens, J. (2014). Ego Network Analysis: An Overview. Bachelor’s Thesis, University of Mannheim, Mannheim, Germany.
Wu, Y., Pitipornvivat, N., Zhao, J., Yang, S., Huang, G., & Qu, H. (2015). egoSlider: Visual analysis of egocentric network evolution. IEEE Transactions on Visualization and Computer Graphics, 22(1): 260-269.
Wyngaerden, F., Tempels, M., Feys, J. L., Dubois, V., & Lorant, V. (2020). The personal social network of psychiatric service users. International Journal of Social Psychiatry, 66(7): 682-692.
 
 
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History

  • Receive Date: 27 August 2023
  • Revise Date: 08 October 2023
  • Accept Date: 20 December 2023

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