Triangulation is a metaphor for research strategies that employ different methods, theories, or data sources in order to capture social reality in a comprehensive manner, reflecting appropriately the multifaceted nature of social objects. While all research approaches in themselves have certain shortcomings, a combination of several approaches may compensate for one another’s weaknesses and provide a more complete picture. The term triangulation originally comes from geodesy and refers to a procedure that uses the known distance between two points in order to determine the unknown distance to a third point (Flick 2004).
Denzin (1989) expands the idea of triangulation to four research strategies: triangulation with data, methods, theories, and investigators. Data triangulation involves using several data sources that vary in time, space, and persons. For example, to investigate the role of television for the cohesion of a social group, it may be useful to interview different kinds of social groups like families, college students, and childless couples. Here, the research objects differ, but the method is the same. Observing the same individuals in different situations, for example watching them use their mobile phones at home or on public transport, is another example of data triangulation. This strategy seeks to investigate the same social phenomenon in different circumstances, and tries to find new aspects until theoretical saturation is achieved; it constitutes a parallel to theoretical sampling in grounded theory (Flick 2004).
In contrast, methodological triangulation involves the same object being investigated with different methods (between-method triangulation), e.g., combining interviews and observation to study television viewing habits; or with different instruments of the same method (within-method triangulation), e.g., using subscales in a standardized questionnaire. The research logic of the latter version is straightforward: both studies should produce the same results, which is similar to the idea of reliability in quantitative research. Using different methods, however, might result in different insights or give information about completely unrelated aspects of the phenomenon. If different methods do not have the ability to capture the same phenomenon, the goal cannot be to validate methods with each other, but to gather different insights that complement one another (Erzberger & Kelle 2003). For example, observing television viewing may reveal patterns of behavior that viewers may not be sufficiently aware of to reproduce them in self-reporting; confronted with the results from the observation in an interview, however, people may be better able to provide subjective views on the behavior and indicate what was intended with a particular action.
Different theories may triangulate data in that they provide competing or complementary frames of interpretation. For example, observational data of television viewing in a family may be seen in the context of social cohesion, or in the context of identity. With this strategy, the researcher keeps an open mind about how to interpret the data, and compares the ability of different theories to explain a social situation, which ultimately serves a more profound theory development (Flick 2004).
Finally, triangulation with different investigators ensures that aspects of social reality are not dependent upon one researcher and his or her understanding of the social situation. The goal is to become aware of individual biases, to make an effort to find common ground among researchers about the interpretation of a social fact, and to increase the reliability of data collection.
While the original term “triangulation” implies that the object under investigation is fixed and can be uncovered validly and objectively by approaching it from several angles, many social scientists have concluded in recent decades that methods do not uncover, but construct a social object. Accordingly, different methods might not capture the very same phenomenon; divergences in results might call for a truth criterion which does not exist. For the same reason, theoretical triangulation may after all have limited applicability in research: data cannot be collected in a theoretical way. Even if hypotheses and standardized instruments are not used, some previous knowledge about the phenomenon will guide method selection and perception in the field (Erzberger & Kelle 2003). Data collected for one purpose may not be useful in informing about a different theory. For these reasons, triangulation in social sciences is today conceived as a strategy to gain deeper and fuller understanding of a social object rather than to provide a cross-validation of methods; it is a means of collecting the manifold facets of the social tableau rather than producing an objective picture (Flick 2004).
Another strategy discussed in the context of triangulation consists of combining qualitative and quantitative methods and data (Erzberger & Kelle 2003). Qualitative methods may be used to explore the field in order to prepare for a quantitative study, but also to follow up results from quantitative studies that require more in-depth explanation. Also, parallel collection of both types of data may be used, either in a continuous and integrated way, or in such a way that the results from one method influence how the next step with the other method is executed (Miles & Huberman 1994). Even more than in method or theory triangulation, applying different methodological paradigms in the same study may result in divergent insights into the social issue, which is detrimental when one expects congruence in triangulation, but advantageous when one expects to get a fuller picture (Erzberger & Kelle 2003).
- Denzin, N. K. (1989). The research act: A theoretical introduction to sociological methods, 3rd edn. Englewood Cliffs, NJ: Prentice Hall.
- Erzberger, C., & Kelle, U. (2003). Making inferences in mixed methods: The rules of integration. In A. Tashakkori & C. Teddlie (eds.), Handbook of mixed methods in social and behavioral research. Thousand Oaks, CA: Sage, pp. 457–488.
- Flick, U. (2004). Triangulation: Eine Einführung [Triangulation: An introduction]. Wiesbaden: VS Verlag für Sozialwissenschaften.
- Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook, 2nd edn. Thousand Oaks, CA: Sage.