A quantitative approach to social network analysis involves the application of mathematical and statistical techniques and graphical presentation of results. Nonetheless—as with all sciences—subjectivity is an integral aspect of network analysis, manifested in the selection of measures to describe connection patterns and actors’ positions (e.g., choosing a centrality indicator), in the visualization of social structure in graphs, and in translating numbers into words (telling the story). Here, we use network research as an example to illustrate how quantitative and qualitative approaches, techniques, and data are mixed along a continuum of fusion between quantitative and qualitative realms.
AlbaR. (1973). A graph-theoretic definition of a sociometric clique. Journal of Mathematical Sociology, 3, 113-126.
2.
BazeleyP. (2009). Editorial: Integrating data analyses in mixed methods research. Journal of Mixed Methods Research, 3(3), 203-207.
3.
BazeleyP. (2012). Integrative analysis strategies for mixed data sources. American Behavioral Scientist, 56, 814-828.
4.
BazeleyP. (2016). Mixed or merged? Integration as the real challenge for mixed methods. Qualitative Research in Organizations and Management, 11, 189-194.
5.
BazeleyP. (2017). Inherently mixed, hybrid methods In Integrating analyses in mixed methods research (pp. 235-262). Thousands Oaks, CA: Sage.
6.
BazeleyP.KempL. (2012). Mosaics, triangles, and DNA metaphors for integrated analysis in mixed methods research. Journal of Mixed Methods Research, 6(1), 55-72.
7.
BennettC.RyallJ.SpalteholzL.GoochA. (2007). The aesthetics of graph visualization. In SpencerS. N. (Ed.), Proceedings of computational aesthetics in graphics, visualization, and imaging (pp. 57-64). New York, NY: Association for Computing Machinery.
8.
BernardH. (2013). Foreword. In HollsteinB.DominguezS. (Eds.), Mixed methods social networks research: Design and applications (pp. xxv-xxviii). Cambridge, England: Cambridge University Press.
BlytheJ.McGrathC.KrackhardtD. (1995). The effect of graph layout on inference from social network data. In BrandenburgF. J. (Ed.), International symposium on graph drawing (pp. 40-51). Heidelberg, Germany: Springer.
12.
BoldiP.VignaS. (2014). Axioms for centrality. Internet Mathematics, 10, 222-262.
13.
BorgattiS. (2005). Centrality and network flow. Social Networks, 27, 55-71.
14.
BurtR. (2000). The network structure of social capital. Research in Organizational Behavior, 22, 345-423.
15.
CheongL. H. M.ArmourC. L.Bosnic-AnticevichS. Z. (2013). Primary health care teams and the patient perspective: A social network analysis. Research in Social & Administrative Pharmacy, 9, 741-757. doi:10.1016/j.sapharm.2012.12.003
16.
ChiuL.WestR. (2007). Health intervention in social context: Understanding social networks and neighbourhood. Social Science & Medicine, 65, 1915-1927.
17.
CovielloN. (2005). Integrating qualitative and quantitative techniques in network analysis. Qualitative Market Research, 8, 39-60.
18.
CreswellJ. W.Plano ClarkV. L. (2007). Designing and conducting mixed methods research. Thousand Oaks, CA: Sage.
19.
CrossleyN. (2010). The social world of the network. Combining qualitative and quantitative elements in social network analysis. Sociologica, 1. doi:10.2383/32049
20.
DominguezS.HollsteinB. (Eds.). (2014). Mixed methods social networks research: Design and applications. Cambridge, England: Cambridge University Press.
21.
DubiniP.AldrichH. (1991). Personal and extended networks are central to the entrepreneurial process. Journal of Business Venturing, 6, 305-313.
22.
EdwardsG. (2010). Mixed methods approaches to social networks analysis (Rev. Pap. NCRM/015). Southampton, England: ESRC National Centre for Research Methods.
23.
EliasN. (1978). What is sociology. London, England: Hutchinson.
24.
FettersM.Molina-AzorínJ. (2017). The Journal of Mixed Methods Research starts a new decade: The mixed methods research integration trilogy and its dimensions. Journal of Mixed Methods Research, 11(3), 291-307.
25.
FreemanL. (1978). Centrality on social networks; conceptual clarification. Social Networks, 1, 215-239.
26.
FreemanL. (2004). The development of social network analysis: A study in the sociology of science. Vancouver, British Columbia, Canada: Empirical Press.
27.
FuhseJ.MützelS. (2011). Tackling connections, structure, and meaning in networks: Quantitative and qualitative methods in sociological network research. Quality & Quantity, 45, 1067-1089. doi:10.1007/s11135-011-9492-3
28.
GoboG. (2015). The next challenge: From mixed to merged methods. Qualitative Research in Organizations and Management, 10, 329-331.
29.
GoboG. (2016). Why “merged” methods realize a higher integration than “mixed” methods: A reply. Qualitative Research in Organizations and Management, 11, 199-208.
30.
GorardS. (2010). Research design, as independent of methods. In TashakkoriA.TeddlieC. (Eds.), Handbook of mixed methods in social & behavioral research (pp. 237-251). Thousand Oaks, CA: Sage.
31.
GranovetterM. (1973). The strength of weak ties. American Journal of Sociology, 78, 1360-1380.
32.
HoganB.CarrascoJ.WellmanB. (2007). Visualizing personal networks: Working with participant-aided sociograms. Field Methods, 19, 116-144.
33.
HsiehH.ShannonS. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15, 1277-1288.
34.
HummonN.CarleyK. (1993). Social networks as normal science. Social Networks, 15, 71-106.
35.
IyengarR.Van den BulteC.ValenteT. W. (2011). Opinion leadership and social contagion in new product diffusion. Marketing Science, 30, 195-212.
36.
JacomyM.VenturiniT.HeymannS.BastianM. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS One, 9, e98679.
37.
JaworskaN.Chupetlovska-AnastasovaA. (2009). A review of multidimensional scaling (MDS) and its utility in various psychological domains. Tutorials for Quantitative Methods for Psychology, 5, 1-10.
38.
JohnsonR.OnwuegbuzieA. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33, 14-26.
39.
KolaczykE. D. (2010). Centrality. In Statistical analysis of network data: Methods and models (p. 88-92). New York, NY: Springer.
40.
KratzerJ. A. N.LettlC. (2009). Distinctive roles of lead users and opinion leaders in the social networks of schoolchildren. Journal of Consumer Research, 36, 646-659. doi:10.1086/599324
41.
LeechN.OnwuegbuzieA. (2009). A typology of mixed methods research designs. Quality & Quantity, 43, 265-275.
42.
LewisJ. (2006). Being around and knowing the players: Networks of influence in health policy. Social Science & Medicine, 62, 2125-2136.
43.
LeydesdorffL. (2007). “Betweenness centrality” as an indicator of the “interdisciplinarity” of scientific journals. Journal of Association for Information Science and Technology, 58, 1303-1319.
44.
MarinA.WellmanB. (2011). Social network analysis: An introduction. In ScottJ.CarringtonP. (Eds.), The SAGE handbook of social network analysis (pp. 11-25). Thousand Oaks, CA: Sage.
45.
MarsdenP. (1990). Network data and measurement. Annual Review of Sociology, 16, 435-463.
46.
MarsdenP. (2011). Survey methods for network data. In ScottJ.CarringtonP. (Eds.), The SAGE handbook of social network analysis (pp. 370-388). Thousand Oaks, CA: Sage.
47.
MartínezA.DimitriadisY.RubiaB.GómezE.de la FuenteaP. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & Education, 41, 353-368.
48.
McGrathC.BlytheJ. (2004). Do you see what I want you to see? The effects of motion and spatial layout on viewers’ perceptions of graph structure. Journal of Social Structure, 5, 2.
49.
McGrathC.BlytheJ.KrackhardtD. (2014). Visualizing multiple levels and dimensions of social network properties. In HuangW. (Ed.), Handbook of human centric visualization (pp. 513-525). New York, NY: Springer.
50.
MorganD. L. (2007). Paradigms lost and pragmatism regained: Methodological implications of combining qualitative and quantitative methods. Journal of Mixed Methods Research, 1(1), 48-76. doi:10.1177/2345678906292462
51.
MorganD. L. (2018). Living within blurry boundaries: The value of distinguishing between qualitative and quantitative research. Journal of Mixed Methods Research, 12(3), 268-279.
52.
MuellerR. (1997). Structural equation modeling: Back to basics. Structural Equation Modeling, 4, 353-369.
53.
NeergaardH.ShawE.CarterS. (2005). The impact of gender, social capital and networks on business ownership: A research agenda. International Journal of Entrepreneurial Behavior & Research, 11, 338-357.
54.
NewmanI.HitchcockJ. (2011). Underlying agreements between quantitative and qualitative research: The short and tall of it all. Human Resource Development Review, 10, 381-398.
55.
OnwuegbuzieA. (2002). Positivists, post-positivists, post-structuralists, and post-modernists: Why can’t we all get along? Towards a framework for unifying research paradigms. Education, 122, 518-530.
56.
OnwuegbuzieA.JohnsonR.CollinsK. (2009). Call for mixed analysis: A philosophical framework for combining qualitative and quantitative approaches. International Journal of Multiple Research Approaches, 3, 114-139.
57.
OnwuegbuzieA.LeechN. (2005a). On becoming a pragmatic researcher: The importance of combining quantitative and qualitative research methodologies. International Journal of Social Research Methodology, 8, 375-387.
58.
OnwuegbuzieA.LeechN. (2005b). Taking the “Q” out of research: Teaching research methodology courses without the divide between quantitative and qualitative paradigms. Quality & Quantity, 39, 267-295.
59.
OnwuegbuzieA.TeddlieC. (2003). A framework for analyzing data in mixed methods research. In TashakkoriA.TeddlieC. (Eds.), Handbook of mixed behavioral research (pp. 351-383). Thousand Oaks, CA: Sage.
60.
PattonM. (1980). Strategic themes in qualitative inquiry. In PattonM. (Ed.), Qualitative evaluation and research methods (pp. 35-60)., London, England: Sage.
61.
RatnerB. (2010). Variable selection methods in regression: Ignorable problem, outing notable solution. Journal of Targeting Measurement and Analysis for Marketing, 18, 65-67.
62.
RyanL.D’AngeloA. (2018). Changing times: Migrants’ social network analysis and the challenges of longitudinal research. Social Networks, 53, 148-158.
63.
SaleJ.LohfeldL.BrazilK. (2002). Revisiting the qualitative-quantitative debate: Implications for mixed-methods research. Quality & Quantity, 36, 43-53.
64.
SaleJ.ThielkeS. (2018). Qualitative research is a fundamental scientific process. Journal of Clinical Epidemiology, 102, 129-133.
65.
SandelowskiM. (1993). Theory unmasked: The uses and guises of theory in qualitative research. Research in Nursing & Health, 16, 213-218.
TeddlieC.JohnsonR. (2009). Methodological thought before the 20th century. In TeddlieC.TashakkoriA. (Eds.), Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences (pp. 40-59). Thousand Oaks, CA: Sage.
68.
TeddlieC.TashakkoriA. (Eds.). (2009). Foundations of mixed methods research: Integrating quantitative and qualitative approaches in the social and behavioral sciences. Thousand Oaks, CA: Sage.
69.
TreweekS.ZwarensteinM. (2009). Making trials matter: Pragmatic and explanatory trials and the problem of applicability. Trials, 10, 37.
70.
TubaroP.RyanL.D’angeloA. (2016). The visual sociogram in qualitative and mixed-methods research. Sociological Research Online, 21, 1-18.
71.
von der LippeH.GamperM. (2017). Drawing or tabulating ego-centered networks? A mixed-methods comparison of questionnaire vs. visualization-based data collection. International Journal of Social Research Methodology, 20, 425-441.
72.
WassermanS.FaustK. (1994). Social network analysis: Methods and applications. Cambridge, England: Cambridge University Press.
73.
WattsD. (1999). Networks, dynamics, and the small-world phenomenon. American Journal of Sociology, 105, 493-527.
74.
WestE.BarronD.DowsettJ.NewtonJ. (1999). Hierarchies and cliques in the social networks of health care professionals: Implications for the design of dissemination strategies. Social Science & Medicine, 48, 633-646.
75.
Yousefi NooraieR.LohfeldL.MarinA.HannemanR.DobbinsM. (2017). Informing the implementation of evidence-informed decision making interventions using a social network analysis perspective; a mixed-methods study. BMC Health Services Research, 17. doi:10.1186/s12913-017-2067-9
