1 Conceptualizing Ties: How & Why We Measure Which Relationships

Methods books generally take on one of two flavors. One option is basically a book of recipes. “You want to identify the effect of parental education on children’s mortality? Here’s the model and measures you need, how to gather them, what pitfalls to avoid, etc.” Another approach is basically to illustrate a set of examples of how people have done something in the past, then use those examples to derive a set of principles scholars ought to follow. If the first is a recipe book, this is a book on the theories of cooking. “Here’s how I selected which observations to record vs. which to ignore, how soon after fieldwork I made sure to translate my observations into fieldnotes, and the details of how I coded up those observations, including the version of the software I used.” From these practices, authors teaching ethnographic methods would extract general recommendations of best practices for standards of evidence, strategies for recording observations, schema for coding data, and what color pens you need to use to record those observations. Ok, maybe they won’t get hung up on pen color, but you get the idea.

Before diving into the recipes or principles of data collection, it is generally important to first provide at least some theoretical guidance on why we’d aim to do the things the methods will show us how to do. Some authors do this particularly well. Others assume that methods are agnostic to the research aims and can be equally useful across a range of research motivations. Still others think that all methodological decisions are clearly implicated from a sufficiently clear theoretical perspective. Here, I don’t aim to answer this question fully, but instead will address where social network data collection differs from the capacity and requirements of general principles for gathering social scientific data.

As Lin Freeman (among numerous others) has argued for decades, network methods are the necessary result of a variety of relational theoretical principles (Freeman 2004). This leads to the requirements for gathering high quality network data depending upon the theoretical bases of social networks. There is not room in this book to adequately address the variety of theoretical perspectives that motivate network studies. Instead, I will highlight aspects of those frameworks that lead to necessary adaptations of social science research practices to produce high quality network data.