Coding of Data

Coding in Quantitative Versus Qualitative Research

At the cost of oversimplification, coding in quantitative research is more etic and deductive whereas coding in qualitative research is more emic and inductive. Whereas coding in quantitative research helps answer the what questions, coding in qualitative analysis addresses the why questions. The former starts with researchers’ preestablished conceptions logically deduced from previous empirical research or theoretical propositions, and follows explicit, unambiguous rules. The goal of coding in quantitative research is to produce numerical patterns to confirm or disconfirm theoretical propositions. Survey questionnaires are precoded with structured response categories from which respondents may choose. In communication research, content analyses of media coverage of a certain issue or topic mostly use quantitative coding. In these analyses, researchers aim to identify key characteristics with which the issue or topic is portrayed or depicted. For example, a number of content analyses on media frames of obesity on newspapers, TV programming, as well as social media such as YouTube have pointed to the frequent use of an individual responsibility frame, whereas a societal responsibility frame is underutilized.

For qualitative research, on the other hand, the primary goal is not to quantify preestablished concepts of interest. Rather, qualitative coding features an interpretive, hermeneutic approach to arrive at indigenous conceptions and meanings via close, constitutive interactions with the text. Though such reading is to different degrees guided by the researcher’s theoretical frameworks and sociocultural conditions, coding in qualitative research aims to uncover themes and ideas from the data, inductively create categories, and develop theoretical concepts.

...