The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-408

“Charles Ragin's Fuzzy Set Qualitative Comparative Analysis (fsQCA) Applied to Linguistic Summarization”

by Jerry M. Mendel and Mohammad Korjani

December 2010

Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It was developed by the eminent sociologist Prof. Charles C. Ragin, but has, as of this date, not been applied by engineers or computer scientists. Unlike more quantitative methods that are based on correlation, fsQCA seeks to establish logical connections between combinations of causal conditions (conjunctural causation) and an outcome, the result being rules that summarize (describe) the sufficiency between subsets of all of the possible combinations of the causal conditions (or their complements) and the outcome. The rules are connected by the word OR to the output. Each rule is a possible path from the causal conditions to the outcome and represents equifinal causation.

This report, for the first time, explains fsQCA in a very quantitative way, something that is needed if engineers and computer scientists are to use fsQCA.

There can be multiple results from fsQCA, i.e. collections of combinations of causal conditions each of which can be interpreted as a linguistic summary, ranging from the most "complex" summary to "intermediate" summaries to the most "parsimonious" summary. The method that is used to obtain the intermediate linguistic summaries is called counterfactual analysis; it is very important to fsQCA and is also described in this report.

This report also provides examples that illustrate every step of fsQCA, guidelines for the number of causal conditions that can be used as a function of the number of cases that are available, comparisons of fsQCA with two existing approaches to linguistic summarization that also use fuzzy sets, and descriptions of a method for obtaining the membership functions that are needed in order to implement fsQCA.

To download the report in PDF format click here: USC-SIPI-408.pdf (9.8Mb)