Using Natural Language Processing to Support Interview Analysis

Abstract

Summary High­quality qualitative work is difficult and can be replicated by another researcher with access to the same data within the maximum level of inter­human agreement. Concept extraction involves identifying key topics within text and sentiment analysis may be used to identify the valence of terms associated with the concepts. Here, a nlp tool is used on interview data to explore if concept extraction and sentiment analysis can be used to validate or support coding by researchers. Work Results ● Literature review ○ Sentiment analysis ○ Agreement levels in data coding: human/human and human/machine ○ Qualitative data analysis, in particular interview analysis, especially formal/automated methods of demonstrating the validity of the results ● Preparation ○ Evaluate existing Open Source sentiment analysis tools and/or libraries ○ Identify sources of data for training domain knowledge and document the process ● Research results ○ A nlp tool capable of training on a corpus of public or private data and identifying key concepts from interviews and abstracting them ○ A theory on the validity of the approach of applying nlp to confirm human qualitative analysis

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