Qualitative Approaches
iBetina Hollstein
In: John Scott & Peter J. Carrington (Eds.): Sage Handbook of Social Network Analysis. London/New Delhi: Sage (forthcoming).
INTRODUCTION
QUALITATIVE APPROACHES TO SOCIAL REALITY: THE SEARCH FOR MEANING
CONTRIBUTIONS OF QUALITATIVE APPROACHES TO NETWORK STUDIES
Exploration of networks Network practices
Network orientations and assessments How networks matter
Understanding network dynamics Validation of network data, field access
QUALITATIVE STRATEGIES FOR DATA COLLECTION AND DATA ANALYSIS
Data collection
Observations; Interviews; Documents, archival data Data analysis
Thick descriptions, developing typologies; Developing models and theories; The surplus of mixed-methods
INTRODUCTION
From the outset, network research has made use of qualitative data, less structured approaches to data collection, and interpretive methods in describing and analyzing social networks. In the 1950s and 1960s, British social anthropologists conducted ethnographic community studies on class structures in small Norwegian island parishes (Barnes, 1954), networks in Central African towns (Mitchell 1969), and also personal networks in their own country (Bott, 1957).
Roethlisberger and Dickson’s (1939) seminal study of the Western Electric Company, a pathbreaking contribution to organization research, adopted an explorative, interpretive, and inductive approach geared toward openness and responsiveness for what was happening in the work teams under study. Besides experiments, they mostly relied on participant observation at the workplace and non-directive interviewing. The concepts developed in these studies became important points of reference in network research, for instance, density (Mitchell, 1969), cliques and clusters (Barnes, 1969), or the distinction between formal and informal organization
(Roethlisberger and Dickson, 1939).
The potential benefits of a qualitative approach in network research, however, are not just limited to the opportunities for exploring and developing new concepts. Qualitative approaches to data collection and analysis are powerful tools, which can enrich the study of social networks in substantial ways. Among other things, qualitative research methods offer special tools for addressing challenges faced in network research, namely to explicate the problem of agency, linkages between network structure and network actors, as well as questions relating to the constitution and dynamics of social networks. The most fruitful results are achieved when qualitative methods, more standardized methods used to describe network structures as well as quantitative methods are employed in concert.
The following chapter gives an overview of qualitative approaches and methods used in studying social networks. It gives a systematic account of the contributions of qualitative methods to social network research, illustrating them with empirical studies from a variety of research fields.
First, however, we must determine more precisely what we mean when speaking of qualitative research and qualitative data.
QUALITATIVE APPROACHES TO SOCIAL REALITY: THE SEARCH FOR MEANING
When we speak of qualitative methods, we are referring to a heterogeneous research landscape, which due to this variety is difficult to comprehensively account for. Among them are different forms of observation, interviewing techniques with low levels of standardization (such as open-ended, unstructured interviews, partially or semi-structured interviews, guided or narrative interviews), and the collection of documents or archival data. At the same time, a host of methods are used for analysis, which rest on various theoretical assumptions and
methodological positions. Among them are symbolic interactionism, sociology of knowledge, phenomenology, ethnomethodology, and constructivism to name but a few major approaches. Yet, in spite of their differences, those approaches all share some common ground, as advocates of the ‘interpretive paradigm’ agree on certain ideas about the nature of social reality (Hollstein and Ullrich, 2003). First, social reality is not simply given but constructed. Recall the well-known Thomas theorem, ‘If men define situations as real, they are real in their consequences.’ Second, social reality is shaped by social meaning. Social reality is always a meaningful reality and, by representing meaning, refers to a context of action in which actors (deliberately) organize action. Third, social reality always depends on a certain point of view or perspective and is therefore tied to social location. And last, since social reality is negotiated, it is always
dynamic: social reality is a process. In these aspects, one can recognize a common basis of such
different methodological positions as symbolic interactionism, ethnomethodology, or phenomenologyii.
Interpretive approaches view these aspects of social reality to be of such key importance that they make up an area of social research in its own right also requiring an appropriate
methodology of its own. Defining feature of qualitative methods is the pivotal role assigned the
understanding of meaning (Sinn-Verstehen). Qualitative research aims to systematically
reconstruct such meaning or, in other words, involves what in German has been coined a
methodically controlled understanding of the other. Qualitative approaches emphasize that
making sense of action and meaning (verbal utterances are also speech acts) always involves understanding the other. In this respect, they adopt a stance akin to everyday communication, which also fundamentally relies on interpretation and understanding (first-order constructs) and in this regard is not categorically different from the process of understanding as applied by the researcher (second-order constructs). As opposed to the objects of research, however, the researcher has the privilege of being in a position to reflect upon and reconstruct the situation without facing demands to act and being forced to do so under the time constraints imposed by the situation. Differences between qualitative approaches emerge depending on the conception of ‘meaning’ one adopts and/or and the kind of ‘meaning’ that is supposed to be analyzed. For
example, phenomenology is concerned with actors’ subjective perspectives. In contrast,
objective hermeneutics aims at reconstructing latent (unconscious) meaning and the inner logic of interaction systems (Oevermann et al., 1979; cf. Titscher et al., 2000). Finally,
ethno-methodology is not interested in the thematic content of meaning (instead it focuses on the ‘how’ of action, actors’ sense-making practices, and the formal rules of communication).
Given the objective of understanding meaning, the two most important aspects for analysis can be derived: First of all, if something has a ‘meaning’, it is understood that such meaning does not exist apart from a context, i.e. from a specific frame of reference. That is the basic idea of
contextuality: one can only understand the meaning of an action and/or an act of expression
with reference to the context of this action or expression. For example, in a biographical
interview the frame of reference (context) would be the entire life history. Second, an approach along the lines of a methodically controlled understanding of the other demands the researcher be open to the subject matter and acknowledge that any previous understanding of the topic in question is only preliminary: That which is not yet recognized, cannot yet be defined. This does not suggest handling preconceptions about the subject matter in a naïve fashion, for instance by simply denying their existence. Rather, an explorative and inductive approach systematically geared toward maintaining openness must start with an explication of one’s own preconceptions and commonsense knowledge on the matter of concern. This should occur while at the same time remaining responsive to the new and unexpected – i.e. open towards the object of research (Hopf, 1979).
Certain methodological principles for data collection and analysis follow from the objective of understanding meaningiii. Open procedures are required in collecting data (i.e., in particular, less structured interviews and observation methods or use of documents already available), and data analysis calls for use of interpretive methods. Applying openness in data collection, above all else, means to design the instrument employed for this purpose in a way that it can cover as broad a data stream as possible. We must take care not to exclude certain data beforehand by the design of our research instruments (i.e. by phrasing questions in very general terms, thus avoiding suggestive questions, and allowing interviewees to elaborate their own frame of relevance and symbol systems when giving answers). The context of meaning should thus be allowed to unfold in as undistorted a form as possible. Accordingly, any act of expression (be it action, a verbal utterance, or a written text) that allows inferences about the context of action, system of meaning, and frame of reference related to the instance of expression in question is considered qualitative data.
Overall, as one zeros in on the object of research, a qualitative approach does so in an open mindset and gradually, inductive and by way of iteration. There are different ways to ensure
validity and methodically control the fact that researchers are bound by their perspective. For example, theoretical sampling and comparative analyses, like in grounded theory (Glaser and Strauss, 1967), interpretation and discussion of the material in groups of researchers, as well as the explication and representation of the steps of analyses. Of course, such a stepwise, gradual approach to the subject matter does not allow raising claims of representativity. Instead, when making statements that go beyond the sample, detailed theoretical justification has to be provided on the basis of the concrete results and procedure. This implies careful consideration of the selectivity of the cases investigated as well as the sampling criteria applied.
The discussion so far has sought to argue the case that qualitative methods are especially well-suited for certain kinds of research questions and objects of research (Hopf, 1979). In formal respect, new or marginal phenomena fall into this category, or phenomena that have not yet been studied. In terms of content, we must distinguish between interpretations, relevances, and complex interpretation systems as well as between structured social entities and interaction systems. The latter comprise loose systems of interaction (such as conversations or
consultations), group and clique relationships, as well as industrial, state, and other types of organizations (ibid.).
CONTRIBUTIONS OF QUALITATIVE APPROACHES TO NETWORK STUDIES
Now that we have determined the nature of qualitative methodology let us turn to possible applications in network research. There are essentially six areas most suitable for qualitative research: exploration of networks, network practices, network orientations and assessments, network effects, network dynamics, and the validation of network data. These are the areas where a qualitative approach can hence be expected to yield the most promising results. They will be exemplified drawing on empirical case studies from different fields of network research.
Exploration of networks
First of all, there is the classical field for applying qualitative procedures: issues that one knows little about because they are either entirely new or have yet to be studied. In such cases,
qualitative studies are employed to explore new or yet unexplored forms of networks, integration patterns, and network practices, which are then followed up by quantitative,
hypotheses-testing forms of investigation at a later time. This can involve exploring egocentric networks of certain people or groups of people, for instance, networks of ‘corner boys’ in slums (Whyte, 1955), networks of migrants (Wong and Salaff, 1998; Schütze, 2006), or junior
researchers commuting between continents in pursuit of their academic careers (Scheibelhofer, forthcoming). Networks of organizations can be the objects of such exploration as well, for
instance, the effectiveness of community mental health networks (Provan and Milward, 1995) or the networks in which firms are embedded (Uzzi, 1997). Finally, entire networks are also explored: networks in small villages (Barnes 1954), in towns (Mitchell 1969), social
movements (Broadbent, 2003; Mische, 2003; 2008), or transnational issue networks, their actors, their knowledge practices, and networking activities (Riles, 2000).
In many cases, such exploration is only the first – preparatory – stage leading up to the main study, which then follows a quantitative design, for instance, when policy networks or networks of research collaborators are initially assessed for important topics, events, actors, and types of collaboration (Franke and Wald, 2006; Baumgarten and Lahusen, 2006). The methods of choice in those cases are typically document research and expert interviews. Thorough preliminary studies of a qualitative nature and pretests are in order especially in quantitative, standardized research on entire networks. Since such studies typically require expending huge efforts on data collection, detailed knowledge of the field under study is an important precondition for research to yield rich results (Baumgarten and Lahusen, 2006).
Network practices
The concrete acts, practices, interactions, and communication patterns in light of the respective contexts in which they occur – thus what actors actually do and how they network are another field of application for qualitative approaches. What kinds of exchange patterns characterize the network ties of immigrants (Menjivar, 2000; Dominguez and Watkins, 2003) or the ties
between entrepreneurial firms (Uzzi, 1997)? What do cooperation and interaction patterns in innovation networks (Franke and Wald, 2006; Gluesing et al., forthcoming) look like? What cultural practices are involved in the ‘art of networking’ among the nobility during the time of the Italian Renaissance (McLean, 1998), or what are the main conversational mechanisms in Brazilian youth organizations (Mische, 2003, 2008)?
In investigating network practices, traditional social anthropological methods are most valuable. The methods used are mostly observation techniques and in-depth interviewing, for instance, for the study of class structures in small Norwegian island parishes (Barnes, 1954) or in investigating gossip in Central African social networks (Epstein, 1969). The Chicago School and the Birmingham Centre for Contemporary Cultural Studies applied ethnographic
approaches in research on their own society, especially in studies on the cultural practices of fringe groups and subcultures, for instance, as in William Foote Whyte’s (1955) classic study of the Street Corner Society in an Italian slum. Furthermore, ethnographic approaches, observation techniques, and open-ended interviews are also used in research on collaboration and
innovation networks, new patterns of work, newly emerging roles, and new meaning within global networking organizations (Gluesing et al., forthcoming). Ethnographic research also
played a key role in observing the modes of discourse, communication patterns, and conversational dynamics that Ann Mische, an advocate of relational sociology, studied in Brazilian social movements (2003, 2008).
Sometimes documents are the main source of information in uncovering cultural practices of networking: for instance, in his study on the art of networking in Italian Renaissance, Paul McLean (1998) analyzed several hundreds of private letters through which Florentines sought favors from one another. Based on an interactionist approach to the presentation of self and political culture, he analyzed the strategies reflected in these writings that members of this society employed in constructing network ties with patrons and in building their own careers. ‘Network work’ can also be approached by reconstructing types of actors. This, for example, is how Engelbrecht (2006) examined the dynamics of knowledge in religious networks in a phenomenological analysis. Based on in-depth interviews with key members of religious communities, he differentiates two forms of contact (bridges) among religious networks, the type he coins ‘diplomat’ and the type referred to as ‘traveler’. While the diplomat mainly acts as a mediator, translator, and innovator in the dialogue of the religions, the traveler is
characterized by spiritual learning that transcends the traditional demarcation lines drawn by religious groups and traditions.
Network orientations and assessments
Qualitative procedures are particularly suitable for collecting data on actor interpretations, individual systems of relevance, and orientations of action. This aspect gains relevance in network research concerned with actors’ perceptions and assessments of the relationships and networks of which they are a part. Research falling into this category may address, for instance, how people locate themselves in their social networks, people’s sense of belonging, or feelings of loneliness, as in studies on patterns of integration and network strategies of migrants (Wong and Salaff, 1998; Schütze, 2006), commuters (Scheibelhofer, forthcoming), members of social movements (Höfer et al., 2006), or the elderly (Schütze and Lang, 1996; Hollstein, 2002). These studies are preoccupied with individual perceptions, meanings, orientations, and
strategies involved in personal networks. Sometimes only certain relationships are subjected to qualitative analysis, for instance, different meanings of friendship (Pahl and Spencer, 2004). Other studies specifically examine certain aspects of relationships, for instance, which ties play a role in parenthood decisions (Keim et al., forthcoming), the significance of emotional
closeness (Hollstein, 2002), or what people mean when they state in the US General Social Survey that they consult others in ‘important matters’ (Bearman and Parigi, 2004). Individual perceptions and assessments, however, not only play a role in personal, egocentric networks but also in networks within and between organizations. Research concerned with the functioning and evaluation of research and innovation networks (Franke and Wald, 2006) or the assessment
of the effectiveness of mental health systems (Provan and Milward, 1995) belongs in this category. In these cases, the respondents are approached as experts of their field of action. Their perception of their environment (context of action) is shaped by their specific social position. They define problems and objectives, assign relevance, and pursue strategies accordingly.
Typically, unstructured or semi-structured interviews and open-ended questions are used for data collection, allowing interviewees to freely respond in accordance with their own systems of relevance to the greatest possible extent. Of course, perceptions, systems of relevance, and attributions of meaning can also be assessed employing standardized methods of data collection and formal methods of analysis (Krackhardt, 1987; Carley, 1984, 1997). Nevertheless, an open, inductive approach is in order in any research of a more exploratory nature as well as in cases where individual meanings or systems of relevance can be expected to vary considerable among respondents or where there is reason to suspect considerable disparity between respondents’ perspectives and the system of relevance assumed by the researcher (Hollstein, 2001; Franke and Wald, 2006).
Whereas the previous uses are primarily of a descriptive nature, qualitative approaches can also be of explanatory value: they can help to uncover how networks actually matter (i.e. the effects of networks) and how networks evolve and change over time. Here, open, less structured procedures of data collection and interpretive approaches in data analysis are in order in cases where we expect context and actor strategies to play a crucial role in determining network impact or network composition and network dynamics (Provan and Milward, 1995; Mische, 2003; Franke and Wald, 2006).
How networks matter
Qualitative approaches not only give insight into how networks work (i.e. the practices of networking). They can also contribute to a better understanding of how networks matter and – in combination with quantitative approaches – of what mechanisms and conditions figure in in producing certain network outcomes. Sandra Susan Smith (2005), for instance, examined job-finding assistance and strategies of activating social capital among the black urban poor. The in-depth interviews show that people who have job-relevant information and some leverage in this respect are very reluctant to provide job-finding assistance for the time and emotional energy it involves and, in some cases, the risk it may pose to one’s own reputation. Other research has employed qualitative interviews and participant observation in the study of
assistance practices among poor immigrants (Menjivar, 2000; Dominguez and Watkins, 2003), the impact of personal networks on decisions to emigrate (Wong and Salaff, 1998) and on decisions affecting fertility (Bernardi, 2003; Bernardi et al., 2007), as well as for the analysis of connections between network position and conversion (Smilde, 2005). Qualitative interviewing
and participant observation is also used in organization research, for instance, to account for success or failure of research or innovation networks (Franke and Wald, 2006) or to identify conditions for the effectiveness of mental health systems (Provan and Milward, 1995). The members of organizations are considered as experts on the networks of which they are part. Accordingly, they are interviewed about their perceptions and assessments of problems (e.g., why cooperation between research teams failed) and about specific contexts and strategies of action (e.g. framework conditions and patterns of interpretation in the fields of nanotechnology, astrophysics, and microeconomics; Franke and Wald, 2006). Drawing on ethnographic
fieldwork in entrepreneurial firms, Brian Uzzi (1997) identifies characteristics of embedded interfirm relationships (trust, fine-grained information transfer, and joint problem-solving arrangements) and explicates the mechanisms by which embeddedness shapes organizational and economic outcomes. It is worth noting that the studies that go beyond thick descriptions (Geertz, 1973) to explain the impact of networks in terms of Verstehen are always comparative studies. Generalization of findings and the formulation of theoretical models that are grounded in data (Glaser and Strauss, 1967) are achieved by systematically comparing cases and taking different contexts of action into consideration (e.g. Provan and Milward, 1995; Franke and Wald, 2006), as well as by careful analysis of (on first glance) contradictory observations (e.g. Provan and Milward, 1995; Mische, 2003).
Understanding network dynamics
Apart from the question of how networks function, issues related to the formative conditions, dynamic processes, and change of networks pose the greatest theoretical and methodological challenges for network research (cf. Jansen, 1999; Snijders, this volume). This concerns not only fluctuation or change in networks over time but also fluctuation and change in networks in physical space (e.g. migrant networks). Qualitative social research provides unique means for understanding (in the sense of Verstehen) network change: Since so far little is still known about the emergence and change of networks, qualitative research frequently serves for purposes of network exploration. Actor orientations and strategies are a first source of important insights into network formation and change. However, since network dynamics always involve at least two actors, analysis of concrete interaction and network practices are a key to understanding the dynamic side of network development. For example, Uzzi’s (1997) in-depth interviews with managers of entrepreneurial firms reveal how embedded ties are formed.
Embedded ties are distinct from so-called arm’s-length ties in that the former are defined by
special bonds of trust entailing specific competitive advantages. Embedded ties are products of third-party referral networks and already existing personal networks; in forging such ties, so-called go-betweens (persons acting as links between previously unconnected actors) play an important mediating role (ibid.). In cases where research on network dynamics also seeks to understand connections between network orientations and actual network changes, longitudinal
data on concrete networks, changes in those networks, actor orientations, and shifts in such orientations are most suited. The studies on migrant acculturation by Menjivar (2000) and Schütze (2006) or on socialization and social integration of young adults by Bidart and
Cacciuttolo (forthcoming) are examples for such research. An interpretive analysis of network change can also be based on document analysis, as in Crossley’s study (2008) of the changing music scene in Manchester. If the inquiry is concerned with the influence of concrete social interaction and actor practices on network dynamics, observation over lengthy periods of time can be expected to deliver the best data basis for this purpose. Gluesing et al.’s study
(forthcoming) on innovation networks in global teams or Ann Mische’s study (2003; 2008) on Brazilian youth movements are cases in point. Based on participant observation and semi-structured interviews, Mische reconstructs different conversational mechanisms (identity qualifying, temporal cuing, generality shifting, and multiple targeting), each of which have a different impact on network building and network mobilization depending on institutional setting (ibid.).
Validation of network data, field access
Besides the applications just mentioned, it can be worthwhile to complement data from standardized surveys with qualitative data even in studies that rely exclusively on the formal procedures of social network analysis in analyzing network data. There are several advantages in doing so. First of all, combining data in this way can serve as a strategy of validating network data. For instance, in their study of network effectiveness of community mental health systems, Provan and Milward (1995) employed three qualitative strategies to enhance validity of the data and validity of the results: in-depth meetings with members of the organizations in focus to review questionnaire items and responses to ensure that respondents were interpreting them as the researcher had intended; follow-up by telephone and additional interviewing to collect missing data and to check data that appeared to be inaccurate after comparing questionnaire responses with field notes; and, finally, after data were initially analyzed, to discuss findings with organization members (‘reality check’) to ensure that major conclusions were consistent with members’ understandings of system operations (ibid.). Second, a systematic, standardized survey to identify alteri and the content of relationships, designed to enable comparison, involves considerable time and effort (Marsden, this volume). For this reason, standardized studies on whole networks mostly limit themselves to assessing but a few contact and
relationship variables and only ask about more general relationship patterns. Thus, in research on heterogeneous groups of actors (such as in policy networks) or multiplex relationships, use of open-ended, less structured methods of collecting data on certain aspects of network
structures can prove to be more effective than sole reliance on standardized procedures. In such cases, open-ended questions aiming at respondents’ systems of relevance and meaning may be more appropriate for capturing the multidimensional nature of these networks (Baumgarten and
Lahusen, 2006; Franke and Wald, 2006). Third, the ‘soft’ approach employed in qualitative interviewing sometimes may be the best (or only) way of obtaining information from certain populations. The advantage of less structured interviews is that in contrast to standardized questionnaires they to a greater extent resemble ‘normal communication’. Moreover, they can easily be adapted to the respective interviewee and the demands of the situation at hand. This can be crucial for being able to obtain network information from some populations at all, for instance, because they are greatly pressed for time (e.g. politicians), their activities are illegal (mafia, drug addicts), or they are in danger (e.g. human rights activists under authoritarian regimes). Network data involve sensitive and sometimes even delicate data. This is more likely to be the case when such data concerns not only ego’s networks but also relationships among alteri.
QUALITATIVE STRATEGIES FOR DATA COLLECTION AND DATA ANALYSIS
As demonstrated above, research on social networks uses different kinds of qualitative data and a range of different modes of data collection: observation techniques, various forms of
interviewing and open-ended questions, as well as collecting all kinds of documents and archival material. Different interpretive methods are used in data analysis. Theoretical and methodological points of reference are symbolic interactionism (Fine and Klineman, 1983; Lazega, 1997; McLean, 1998) and pragmatism (Franke and Wald, 2006), relational sociology (Mische, 2008), phenomenology, sociology of knowledge (Engelbrecht, 2006), and actor-network theory (cf. Mützel, forthcoming; Knox et al., 2006). Since the qualitative methods employed for data collection and data analysis in network research are essentially the same as the methodology otherwise used in qualitative social research, the following section will be limited to providing a cursory overview of qualitative research strategies as they are put to use in social network analysis. For details on individual methods, the reader may consult the respective literature (e.g. Miles and Huberman, 1984; Denzin and Lincoln, 2005; Bryman and Burgess, 1999; Bernard 1994; 2000).
Data Collection
Several aspects need to be considered in choosing the method of data collection. First of all, it needs to be clarified what aspects of social relations will be studied and how relations and networks are to be theoretically conceptualized (Marsden, 1990). A key question in this respect is whether the research will be concerned with actually existing relations (e.g. network
practices) or with actors’ perceptions of such relations (e.g. network orientations and
‘Accurate knowledge of actually existing ties is arguably important to the study, for example, of certain diffusion processes (…) while perceived ties might be more appropriate for studying social influence on attitudes or opinions’ (Marsden, 1990: 437). The focus can also be directed at concrete interaction between actors when network dynamics are being studied. Besides, such an approach also lends itself to research aimed at describing strategies and network orientations at the level of individual actors (e.g. McLean, 1998). The decision to use observation data or to rely on actor self reports (in interviews or in written ego documents) will depend on whether actual behavior or strategies of action and perceptions of relations are at the center of attention.
Explorative research often adopts a holistic, ethnographic approach marked by utmost openness toward its subject matter and aimed at achieving an as comprehensive as possible understanding of the phenomenon in question. Here, as much data as possible is collected from multiple sources to shed light on the phenomenon from different angles: observation data, documents, interviews, diaries, and questionnaires. Some network studies begin with an exploratory phase in which all available data is compiled and significant actors, relationships, and modes of communication are identified. This is especially pertinent in studies concerned with whole networks in order to be able to determine network boundaries (cf. Marsden, 2005), which is a particularly challenging task in the case of flux networks, such as social movements (Diani and McAdam, 2003) or transnational NGO networks (Riles, 2000). Initially approaching the field in this holistic, ethnographic manner is generally useful when network research is concerned with unfamiliar social worlds (e.g. other cultures) that the researcher has to first become acquainted with, for instance, in case of organizations (Provan and Milward, 1995; Uzzi, 1997; Gluesing et al., forthcoming), migrant communities (Menjivar, 2000; Dominguez and Watkins, 2003), or comparative cultural analyses (Lonkila and Salmi, 2005). Furthermore, such a multi-source approach, drawing on different types and sources of data (e.g. combining participant observation and interviewing), represents a strategy for validating data (e.g. Provan and Milward, 1995; Uzzi, 1997; Gluesing et al., forthcoming).
Of course, the choice of method also involves pragmatic considerations, particularly concerning available time and funding: Observation, for instance, is very time-consuming. Archival data, on the other hand, often have the advantage of being easily accessible and thus economical. And sometimes there is actually little scope for choice of method since only certain data are available, as in McLean’s study of favor-seeking letters from Florentine nobility during the Renaissance (1998). This situation forces the researcher to carefully consider what kind of questions and what aspects of networks can be tackled in view of the available data. Accordingly, McLean (1998) in his analysis of letters concentrates on strategies of
self-presentation and how actors sought to mobilize social capital through writing letters. In general, utmost attention must be paid to the conditions under which data originated. The conditions of
origin are the ultimate measure in gauging whether certain data lend themselves to answering a specific question and thus can be considered valid (cf. Marsden, 2005).
Observations
Observation methods belong to the ethnographer’s traditional toolkit. In the early days of network research, they found most prominent use in social anthropological studies (e.g.
Mitchell, 1969; Epstein, 1969). Today, observation methods are employed in research on social movements (Mische, 2008; Broadbent, 2003), organizations (Provan and Milward, 1995; Uzzi, 1997; Gibson, 2005; Häussling, 2006; Gluesing et al., forthcoming), and ethnic communities (Dominguez and Watkins, 2003; Menjivar, 2000; Smilde, 2005). Only rarely does observation data serve as the main data source, as in Gibson’s (2005) investigation of the conversation practices of managers or Häussling’s study on interaction and network formation in school classes (forthcoming). For the most part, observation is used to complement other data. On the one hand, it serves to access the field (actors, content of relationships, forms of interaction). For instance, in social movement research, meetings and gatherings of various groups are attended in order to identify conversation practices, topics, and significant actors
(Broadbent, 2003; Mische, 2008). Some researchers shadow actors, as did Gluesing et al. (forthcoming) who escorted the members of the innovation team under study over a number of days to find out who they met, how often, for how long, and what topics they talked about. On the other hand, observation data play an important role in complementing and checking data from other sources (e.g. Provan and Milward, 1995; Uzzi, 1997). In this vein, Gluesing et al. (forthcoming) analyzed thousands of e-mails (documents) and also face-to-face encounters (observed) in their study revealing national differences in e-mail usage. Observation data are considered to be particularly reliableiv when actual behavior (that is, the content of relationships and modes of communication) is the main concern (cf. Marsden, 1990; 2005). Of course, it needs to be mentioned that there can be great variation in the quality of observation data. For instance, much depends on the window of observation selected (time-sampling; Kashy and Kenny, 1990; cf. Marsden, 2005). To be sure, repeated observation over extended periods of time is an appropriate strategy of ensuring good data quality (e.g. Menjivar, 2000; Dominguez and Watkins, 2003; Mische, 2008; Gluesing et al., forthcoming). Yet it is also very time-consuming. Careful attention must further be paid to the number and training of research staff involved in observation, the choice of recording devices (video, audio), placement of recording devices, as well as the mode of transcription.
Interviews
Open-ended interviewing of some kind is employed in almost all of the qualitative studies discussed in this overview: in-depth-interviews (e.g. Wong and Salaff, 1998; Menjivar, 2000; Broadbent, 2003; Smith, 2005; Gluesing et al., forthcoming), narrative Interviews (Hollstein,
2002), focused, thematic, or problem-centered interviews (e.g. Lonkila and Salmi, 2005; Bernardi et al., 2007; Scheibelhofer, 2008), but also single, open-ended questions as part of standardized surveys (Bearman and Parigi, 2004). Qualitative interviews are typically used to complement other data, particularly observation data, in research on actual behavior (network practices; see above, e.g. Uzzi, 1997; Gluesing et al., forthcoming). They are the first choice in studying actors’ networking strategies, network orientations, and assessments (thus the
individual significance attached to and perception of relationships and networks). This includes studies of integration into personal networks (Höfer et al., 2006; Schütze, 2006), the impact of networks on life course decisions (Lonkila and Salmi, 2005; Bernardi et al., 2007), or the assessment of networking strategies and network success among and between networks of organizations (Provan and Milward, 1995; Uzzi, 1997; Franke and Wald, 2006). In addition, open-ended interviews are a useful way of becoming familiar with the field under study
(exploration) and for accessing certain populations (politicians, criminals; see above). An open-ended approach in inquiring about significant relationships and relationship content can also be in order for economical reasons, for instance, when a standardized survey would be too time-consuming due to the multiplexity of relationships or contents (Franke and Wald, 2006; Baumgarten and Lahusen, 2006). Franke and Wald (2006) argue that, as a rule of thumb, questions should be designed as open-ended the more so, the less one knows about a
phenomenon, the more important individual actors’ strategies and systems of relevance are, and the greater impact context factors can be assumed to have.
In case of self-reports, we must bear in mind that utterances (as a matter of perspective) are always bound to social location. This can be the particular focus of research, as is the case in research concerned with the individual perception of integration into personal networks. However, in cases when actors are approached as experts on specific behavior (e.g. routines, other actors, or relations in organizations), the socially biased nature of individual perception must be reckoned with in the choice of interview partners and the interpretation of statements. For example, persons who occupy central positions in networks are more knowledgeable about network events compared to persons on the fringes (Krackhardt, 1990). The greater the
proximity between persons the more accurate are their statements concerning the other
(Bondonio, 1998). Research has produced an array of findings on factors affecting the accuracy of self-reports; the work in the wake of the Bernard, Killworth, and Sailer Studies (1981) are especially noteworthy in this respect (cf. the overviews provided in Johnson, 1994; Marsden, 2005; this volume).
Finally, it must be noted that even the most open and unstructured interviews are typically combined with some form of standardized inquiry, especially for obtaining information via name generators and name interpreters (Hanneman and Riddle, Marsden, this volume; e.g.
Franke and Wald, 2006; Bernardi et al., 2007). Such method triangulation ensures the
comparability of data (across cases as well as between certain aspects of an individual case). At the same time, it allows making substantive statements about the structure of networks that go beyond a merely metaphorical reference to the term ‘network’ (cf. Johnson, 1994). Network charts are another useful tool for collecting qualitative data, for instance on egocentric networks (cf. Straus, 2002; McCarty et al., 2007; Hogan et al., 2007). Kahn and Antonucci’s concentric circles (1980) are a good example of such an instrument. Due to its semi-standardized design, the instrument also supports the comparability of cases. Furthermore, the graphical
representation of networks functions as a cognitive aid in describing relationships. It allows keeping track of the relationships discussed in the interview. In qualitative interviews, geared toward approaching as close as possible the systems of relevance and action orientations of interviewees mapping networks is a well-suited means of facilitating the discussion of
relationships while it provides a strong stimulus for the production of narratives (e.g. Hollstein, 2002; Bernardi et al., 2007).
Documents, archival data
In addition to qualitative data obtained through observation and interviewing, various kinds of documents can also be put to use in network-related inquiry: archival data, newspaper articles, biographies, letters, e-mails, weblogs, etc. The main advantage of this type of data is that it is mostly easily accessible and available at low cost. In recent years, data offered by computer-mediated systems have gained increasing importance in network research. Because of large volume, such data are usually subjected to computerized, more strongly standardized and formalized methods of data mining (see below; on archival records Batagelj et al., this volume). In these cases, documents are mostly the primary data sources. Studies based on interpretive methods of analysis, on the other hand, generally draw on documents only for complementary information. For instance, newspaper articles, books, archival material are used in research on political parties and social movements (e.g. Broadbent, 2003; Mische, 2008) or company documents and company portrayals in company case studies (e.g. Gluesing et al., forthcoming). Of course, documents are the key source of data in historical studies. Examples for network research of this type are McLean’s work on network practices of Florentine nobility based on analysis of favor-seeking letters (1998) or Crossley’s (2008) study of the changing music scene in 1970s Manchester based on musicians’ biographies and autobiographies, as well as online resources. Documents represent data ‘not created expressly for social research’ (Marsden, 2005: 24). This to an even greater extent demands giving close thought to the conditions under which the data originated with an eye to the respective research question (see above). Data
interpretation requires giving consideration to such aspects as motives, purpose, and mode of data production, the specific demands posed by the medium, and initiating parties and the intended audience.
Data Analysis
In principle, qualitative data can be analyzed using interpretive as well as formal (quantitative) methods of analysis. The majority of qualitative studies referred to in this article employ grounded theory as the method of choice (e.g. Lonkila and Salmi, 2005; Bernardi et al., 2007), often in conjunction with ethnographic descriptions (e.g. Provan and Milward, 1995; Uzzi, 1997; Menjivar, 2000, Broadbent, 2003; Dominguez and Watkins, 2003, Gluesing et al., forthcoming). Yet, it needs to be emphasized that, depending on research focus and
methodological orientationv (interactionist, structuralist, pragmatic, or oriented by sociology of knowledge), a range of interpretive methods may qualify as candidates well-suited for the analysis of network practices, network orientations, and network assessments. Methods of analysis are frame analysis (e.g. McLean, 1998), conversation analysis (e.g. Mische, 2003), various types of interaction analyses (e.g. Häussling, 2006), narrative analysis (e.g. Uzzi, 1997; Hollstein, 2002), as well as analytical procedures based on sociology of knowledge or
phenomenology (e.g. Engelbrecht, 2006).
However, qualitative data can also be analyzed using quantitative or other methods of a more formal nature. Methods of this type applied to qualitative data are, for instance, methods designed to analyze texts (transcripts, documents) for formal structures, such as quantitative content analysis (Franzosi, 2008), semantic network analysis (Carley, 1984, 1997), network analysis of narratives (e.g. Bearman and Stovel, 2000; Smith, 2007), or Galois lattice analysis (e.g. Yeung, 2005; Mische, 2008). Those methods of analysis are to a greater degree
standardized, less interpretive, and in this sense reduce data complexity. For this reason, they have clear advantages when the task is handling large volumes of data (cf. Bagatelj et al., this volume), as increasingly is the case in the wake of easier access to large quantities of data via the Internet as well as ongoing advances in software development (cf. Huisman and van Duijn, this volume).
This is not the place to discuss the various methods in detail. Instead, some final considerations will be devoted to the general strategies pursued in analyzing qualitative data as observed in the qualitative studies touched upon so far. They can be distinguished by the generalizability of their findings and the claims they can make as to the scope of explanation. There is some agreement that systematically combining qualitative with quantitative data and data on network structures (so-called mixed method designs) enhances the explanatory power of analysis.
Thick descriptions, typologies
A common strategy of analyzing qualitative data is to give a detailed account of individual cases by way of ‘thick descriptions’ (Geertz 1973) geared toward tracing how actions or events
unfold and the impact they have in order to make them comprehensible (Verstehen) and in this way explain them. Understanding the individual case is the objective and, as such, an ‘end in itself’, as exemplified by Riles’ study on knowledge practices and networking activities in transnational issue networks (2000). In another strategy, analysis proceeds by systematic comparison and abstraction aimed at developing typologies that capture the range of possible variation that can be expected in a certain field of action. An example is the typology of
‘traveler’ and ‘diplomat’ developed by Engelbrecht (2006) to account for the different modes of bridging the gap between different religious communities.
Developing models and theories
Typologies based on descriptions leave questions unanswered pertaining to the conditions under which the respective types emerge and the impact they have. Generalization of findings and formulation of theoretical models grounded in data (Glaser and Straus, 1967) require using the respective data for systematically comparing cases and contrasting patterns of action and the conditions surrounding them (e.g. Provan and Milward, 1995; Franke and Wald, 2006) as well as systematic and careful analysis of (on first glance) contradictory findings and outliers (e.g. Provan and Milward, 1995; Mische, 2003). This also involves careful consideration of sample composition and the selection of cases (cf. Frank, this volume).
The surplus of mixed method designs
Mixed method designs open an array of opportunities for data analysis (cf. Tashakkori and Teddlie, 2003; Axinn and Pearce, 2006; Bryman, 2006; Creswell and Plano, 2007; Bernardi, forthcoming). In network research, this refers, first, to research designs that employ both qualitative data as well as standardized data used to describe formal properties of networks, such as network size, measures of density, centrality, etc. This specific mode of data
triangulation (Denzin, 1970) is a key element in network research in order to make substantive
statements about actual networks that range beyond using the term ‘network’ merely in a metaphorical sense (Johnson, 1994). Relating data in this way also has theoretical implications: Since qualitative data comes closer to individual actors, their systems of relevance (compared to relational data on relationship and network structures), incorporating qualitative and structural data provides a way of linking theoretical perspectives that either focus on structure or agency (Hollstein, 2001; Häussling, 2006). Advocates of a relational sociology have been arguing to that effect since the early 1990s (White, 1992; Emirbayer and Goodwin, 1994; Mizruchi, 1994). We can thus expect empirical studies along such lines to also yield theoretically inspiring insights.
Moreover, mixed methods designs can enhance the explanatory power and generalizability of statements. This is the case if, secondly, qualitative and quantitative strategies of analysis are
combined as well (‘method-triangulation’; Denzin, 1970). Combining qualitative and quantitative analyses can take very different shapes depending on the research in question. Quantitative analyses can provide a general framework for selecting specific cases for
qualitative analysis (e.g. typical cases, outlier) and for determining their significance (in terms of quantity, distribution, relevance, etc.) (mapping; e.g. White, 1961; McLean, 1998; Wong and Salaff, 1998; Hollstein, 2002). In this way, McLean (1998) maps networking strategies of Florentine nobility by using multidimensional scaling techniques. Quantitative analyses not only allow more precisely assessing the extent to which certain patterns of action are spread among a certain population. They also help gaining a more complete picture of the conditions (institutional settings) under which such patterns have effect (Mische, 2003; 2008). By means of in-depth interviews about assistance practices among black urban poor, Smith (2005), for example, brings to fore why people having job-relevant information are reluctant to pass such knowledge on to others. She then employs quantitative survey data to check for circumstances (strength of ties, socio-economic status of neighborhood) that make providing assistance more or less likely (ibid.). In other research, quantitative and qualitative approaches are used
simultaneously and are more strongly integrated (e.g. Häussling, 2006; Bernardi et al., 2007; Gluesing et al., forthcoming), for instance, by applying formal procedures like cross-site display (Miles and Huberman, 1984; adopted for network research by Uzzi, 1997) or qualitative
comparative analysis (Ragin, 1987; applied in network research by Smilde, 2005).
I believe to have demonstrated that qualitative approaches have important contributions to make to social network research. Their definite strengths lie with exploring networks, validating network data, describing network practices, network orientations and assessments, and the insight they can provide into network impacts and dynamics. Yet, combining qualitative and quantitative data and analyses promises to yield the most fruitful results.
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i
For helpful comments on an earlier draft, I am grateful to Janet Salaff, Stephan Elkins, Laura Bernardi, and Werner Rammert.
ii
Although these approaches share the same basic assumptions, they focus on different aspects in detail. For example, some focus more on the process of action and the construction of reality (like ethnomethodology). Other approaches are more concerned with the results of the construction processes, i.e. the ‘structures of meaning’ (like objective hermeneutics; cf. Titscher et al., 2000).
iii
For details on qualitative approaches and individual methods, see for example the overviews in Miles and Huberman (1984), Denzin and Lincoln (2005), Bryman and Burgess (1999) and Bernard (1994; 2000).
iv
In particular, see the seminal studies by Bernard, Killworth, and Sailer on informant accuracy (1981). For details about the important debates initiated by these studies, see Johnson (1994); Marsden (1990; 2005; this volume).
v
Acts of expression can be analyzed for different layers of meaning, for instance, with regard to an intended or deliberate meaning but also for latent meaning. Depending on the level of meaning targeted by an analysis either more phenomenological approaches (which focus on actor perspectives) or methods relying on a more in-depth, structural hermeneutical analysis (like objective hermeneutics, which focuses on the latent, unconscious aspects of meaning and the logic of action; Oevermann et al., 1979, cf. Titscher et al., 2000) are employed.
