Karma Yöntem Araştırmalarında Graph Teori ve Sosyal Ağ Analizinin İşlevselleştirilmesi: Bir Döngüsel Entegrasyon Modeli

Abstract

Graph teorisi, iletişim kalıplarını incelemede sosyal ağ analizine (SNA) kavramsal bir temel sunmaktadır. Bu çerçevede SNA’nın uygulanması, ağ içindeki önemli bileşenlerin belirlenmesine ve bağlantı biçimlerinin ölçülmesine imkân vermektedir. Mevcut alanyazın incelendiğinde, araştırmacıların, ağ yapılarını tanımlamada çoğunlukla niceliksel bir duruş benimsediği görülmektedir. Bu çalışma, niceliksel ve niteliksel yaklaşımları ortak bir zeminde birleştiren karma yöntemli sosyal ağ analizinin (MMSNA) potansiyelini teorik yorumlayıcı bir perspektifte incelemektedir. Ayrıca, bu çalışma ağ yapılarındaki ilişkilerin keşfini mümkün kılacak metodolojilerin geliştirilmesi ve bütünleştirilmesine dair temel bir teorik argüman sunmaktadır. Bununla birlikte, karma yöntemli araştırma tasarımlarının sosyal ilişkileri analitik biçimde yapılandırma kapasitesi tartışılmaktadır. Bu doğrultuda, MMSNA literatürünü haritalamak amacıyla sistematik bir kavramsal derleme tasarımı benimsenmiştir. Web of Science ve Scopus veri tabanlarında Eylül 2025 itibarıyla yürütülen taramalardan elde edilen 733 kayıt, R programlama dili kullanılarak birleştirilmiş ve yinelenen yayınlar çıkarılmıştır. Nihai olarak, konuyla doğrudan ilişkili 200 uluslararası akademik yayın inceleme kapsamına alınmıştır. Bu inceleme sonucunda, söz konusu boşluğu gidermek amacıyla metodolojik ve epistemolojik düzeyleri bütünleştiren özgün ve iki katmanlı bir kavramsal model önerilmektedir. İlk olarak, Döngüsel Entegrasyon Modeli, entegrasyonu yalnızca sonuç aşamasına bırakmayarak tasarım, veri toplama, analiz ve yorumlama süreçlerinin tamamında sürekli bir mekanizma olarak işletmektedir. İkinci olarak, Köprü Kurucu ve Ağ Örücü Modeli, araştırmacının entegrasyon sürecindeki yansıtıcı rolünü vurgulamakta; niceliksel “ne” ve niteliksel “nasıl/neden” soruları arasında bağlantılar kurmaktadır. Sonuç olarak çalışma, SNA’da kullanılan nicel, nitel ve karma yöntem yaklaşımlarına dair metodolojik yönelimleri ve entegrasyon tartışmalarını görünür kılarak, önerilen iki katmanlı modele kavramsal bir zemin sunmaktadır. Karma yöntemlerin çatısı altında nicel ve nitel yaklaşımların birleşimi, SNA araştırmalarında daha yorumlanabilir ve geçerli sonuçlar üretmekte; sosyal ilişki yapılarının incelenmesinde MMSNA’nın işlevselleştirilmesi ise alana vazgeçilmez bir katkı sağlamaktadır.

Keywords

• Graf Teori
• Sosyal Ağ Analizi
• Karma Yöntemli Sosyal Ağ Analizi
• Döngüsel Entegrasyon Modeli
• Köprü Kurucu ve Ağ Örücü Model

Operationalizing Graph Theory and Social Network Analysis in Mixed Methods Research: A Cyclical Integration Model

Abstract

Graph theory provides a conceptual foundation for social network analysis (SNA) in examining communication patterns. Within this framework, the application of SNA makes it possible to identify key components within the network and measure the types of connections. A review of the existing literature shows that researchers have predominantly adopted a quantitative stance in defining network structures. This study examines the potential of mixed-methods social network analysis (MMSNA), which combines quantitative and qualitative approaches within a common framework, from a theoretical-interpretive perspective. In addition, this study presents a fundamental theoretical argument for the development and integration of methodologies that enable the discovery of relationships within network structures. Furthermore, it discusses the capacity of mixed-method research designs to analytically structure social relations. To this end, a systematic conceptual review design was adopted to map the MMSNA literature. Searches conducted in the Web of Science and Scopus databases as of September 2025 yielded 733 records, which were merged using the R programming language and duplicates removed. Ultimately, 200 international academic publications directly related to the subject were included in the review. As a result of this analysis, an original two-layered conceptual model that integrates methodological and epistemological dimensions is proposed to address the identified gap. First, the Cyclical Integration Model operates integration not only at the final stage but also continuously throughout the design, data collection, analysis, and interpretation processes. Second, the Bridge-Builder and Network-Weaver Model emphasizes the researcher’s reflective role in the integration process, establishing connections between quantitative “what” questions and qualitative “how/why” questions. In conclusion, the study makes visible the methodological orientations and integration debates in SNA, providing a conceptual basis for the proposed two-layered model. The combination of quantitative and qualitative approaches under mixed-methods research produces more interpretable and valid results in SNA studies, and the operationalization of MMSNA makes an indispensable contribution to the examination of social relationship structures.

Keywords

• Graph Theory
• Social Network Analysis
• Mixed Methods Social Network Analysis
• Cyclical Integration
• Bridge-Builder and Network-Weaver Model

References

1. Baker-Doyle, K. J. (2015). Stories in networks and networks in stories: A tri-modal model for mixed-methods social network research on teachers. International Journal of Research & Method in Education, 38(1), 72-82. https://doi.org/10.1080/1743727X.2014.911838
2. Barabási, A. L. (2014). Linked-How everything is connected to everything else and what it means. Perseus Books Group.
3. Barnes, J. A. (1954). Class and committees in a Norwegian island parish. Human Relations, 7(1), 39-58. https://doi.org/10.1177/001872675400700102
4. Bazeley, P. (2003). Computerized data analysis for mixed methods research. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed methods in social and behavioral research (pp. 385-422). Sage Publications.
5. Bollobás, B. (2012). Graph theory: An introductory course (Vol. 63). Springer Science & Business Media.
6. Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing social networks. SAGE Publications.
7. Carrington, P. J. (2014). Social network research. In S. Domínguez & B. Hollstein (Eds.), Mixed methods social networks research: Design and applications (p. 408). Cambridge University Press.
8. Carrington, P. J., Scott, J., & Wasserman, S. (Eds.). (2005). Models and methods in social network analysis. Cambridge University Press.

9. Cooray, S. (2021). A qualitative enhancement to quantitative social network analysis. The Information Society, 37(4), 227-246. https://doi.org/10.1080/01972243.2021.1926028
10. Creswell, J.W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd edition). Sage.
11. Crossley, N. (2010a). Networks and complexity: Directions for interactionist research, Symbolic Interaction, 33(3), 341-363. https://doi.org/10.1525/si.2010.33.3.341
12. Crossley, N. (2010b). The social world of the network: Combining qualitative and quantitative elements in social network analysis. Sociologica. 1, 1-34. https://doi.org/10.2383/32049
13. Edwards, G. (2010). Mixed-method approaches to social network analysis. ESRC National Centre for Research Methods.
14. 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. https://doi.org/10.1177/205979910900400104
15. Emmel, N. (2008). Participatory mapping: An innovative sociological method. ESRC National Centre for Research Methods, University of Leeds.
16. Emmel, N., & Clark, A. (2009). The methods used in connected lives: Investigating networks, neighbourhoods and communities. ESRC National Centre for Research Methods.
17. Freeman, L. C. (2004). The development of social network analysis: A Study in the Sociology of Science. Empirical Press.
18. Froehlich, D. E., & Brouwer, J. (2021). Social network analysis as mixed analysis. In A.J Onwuegbuzie & R.B. Johnson (Eds.), The Routledge Reviewer’s guide to mixed methods analysis (pp. 209-218). Routledge.
19. Froehlich, D., Rehm, M., & Rienties, B. (2020). MMSNA: An introduction of a tale of two communities. In D. Froehlich, M. Rehm, & B. Rienties (Eds.), Mixed methods approaches to social network analysis (pp. 1-10). Routledge.
20. Greene, J. C., Caracelli, V. J., & Graham,W. F. (1989).Toward a conceptual framework for mixed- method evaluation designs. Educational Evaluation and Policy Analysis, 11, 255-274.
21. Hage, P., & Harary, F. (1983). Structural models in anthropology. Cambridge University Press.
22. Harary, F. (1999). Graph theory. Perseus Books.
23. Heath, S., Fuller, A., & Johnston, B. (2009). Chasing shadows: Defining network boundaries in qualitative social network analysis. Qualitative Research, 9(5), 645-661. https://doi.org/10.1177/1468794109343631
24. Hilpert, J. C., & Marchand, G. C. (2018). Complex systems research in educational psychology: Aligning theory and method. Educational psychologist, 53(3), 185-202. https://doi.org/10.1080/00461520.2018.1469411
25. Hollstein, B. (2014). Mixed methods social networks research: An introduction. In S. Domínguez & B. Hollstein (Eds.), Mixed methods social networks research: Design and applications (pp. 3-34). Cambridge University Press.
26. Jungnickel, D. (2012). Graphs, networks and algorithms. Springer.
27. Leinhardt, S. (1977). Social networks: A developing paradigm. Academic Press.
28. Litherland, R. (2009). Introduction to graph theory. Louisiana State University.
29. Martínez, A., Dimitriadis, Y., Rubia, B., Gómez, E., & De la Fuente, P. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & education, 41(4), 353-368. https://doi.org/10.1016/j.compedu.2003.06.001
30. Moreno, J. L. (1953). Who shall survive? Foundations of sociometry, group psychotherapy and socio-drama (2nd edition). Beacon House.
31. Newman, M. (2010). Networks. Oxford University Press.
32. Newman, M. E., Barabási, A. L. E., & Watts, D. J. (2006). The structure and dynamics of networks. Princeton University Press.
33. Nooraie, Y. R., Lohfeld, L., Marin, A., Hanneman, R., & Dobbins, M. (2017). Informing evidence-informed decision-making interventions with social network analysis: A mixed- methods study. BMC Health Services Research, 17(1), 1-14. https://doi.org/10.1186/s12913-017-2067-9
34. Pahl, R., & Spencer, L. (2004). Capturing personal communities. In G. Allan & C. Phillipson (Eds.), Social networks and social exclusion: Sociological and policy perspectives (pp. 72-96). Routledge.
35. Pantic, N., Brouwer, J., Thomas, L., & Froehlich, D. (2023). The potential of mixed-method social network analysis for studying interaction between agency and structure in education. International Journal of Research & Method in Education, 46(2), 187-199. https://doi.org/10.1080/1743727X.2022.2094361
36. Pryke, S. (2012). Social network analysis in construction. Wiley-Blackwell.
37. Saoub, K. R. (2021). Graph theory: An introduction to proofs, algorithms, and applications. CRC Press.
38. Scott, J. (2000). Social network analysis: A handbook, (2nd edition). SAGE.
39. Scott, J. (2011). Social network analysis: Developments, advances, and prospects. Social Network Analysis and Mining, 1(1), 21-26. https://doi.org/10.1007/s13278-010-0012-6
40. Simmel, G. (1972). On individuality and social forms (D. N. Levine, Ed.). University of Chicago Press.
41. Tashakkori, A., & Creswell, J. W. (2007). The new era of mixed methods. Journal of Mixed Methods Research, 1(1), 3-7. https://doi.org/10.1177/2345678906293042
42. Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. SAGE.
43. Thomas, L., Tuytens, M., Devos, G., Kelchtermans, G., & Vanderlinde, R. (2020). Unpacking beginning teachers’ collegial networks: A mixed-methods social network study. In D. Froehlich, M. Rehm, & B. Rienties (Eds.), Mixed methods approaches to social network analysis (pp. 139-158). Routledge.
44. Trotter, R. T. (1999). Friends, relatives and relevant others: Conducting ethnographic network studies. In J. J. Schensul, M. D. LeCompte, M. Singer, R. T. Trotter II, & E. K. Cromley (Eds.), Mapping social networks, spatial data, and hidden populations (Vol. 4, pp. 1-49). AltaMira Press.
45. Trudeau, R. J. (1994). Introduction to graph theory. Dover Publications.
46. Wallis, W. D. (2006). A beginner’s guide to graph theory. Birkhäuser.
47. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge University Press.
48. Wellman, B., & Berkowitz, S. D. (1988). Social structures: A network approach. Cambridge University Press.
49. Wilson, R. J. (1996). Introduction to graph theory (4th edition). Addison Wesley.