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Galleries // 2019 Spark:Fall/Winter Student // Innerview
Winner - Bronze
Competition: Spark:Fall/Winter Student
Designer: Cheonkyu Park
Design Type: Web, UX, UI, IXO, HCII
Company / Organization / School: Yonsei University
Team Members: Cheonkyu Park, Geonhee Lee & Younah Kang (Faculty Advisor)
Interviews are an essential element in the UX design process or qualitative research. Analyzing interview data is a difficult process, but it's a must because it's a process where you can get a lot While there have been various QDA tools to help analyze interview data, there have been no tools to essentially address the challenges of interview data analysis. Two of the challenges of analyzing qualitative data is that it involves the inevitable subjectivity of individual researchers, and where and how to get the insight from when analyzing vast amounts of data. Innerview is a service that aims to overcome these limitations by utilizing AI NLP algorithm. The main point of Innerview is to help individual researchers interpret data objectively using artificial intelligence. This subjective view, of course, is a disadvantage, but it also works as a big advantage of qualitative research, so it's designed not to infringe on that. In addition, Innerview categorizes and visualizes the subjects' emotional state in the interview data into eight categories, helping researchers and designers see at a glance the outliers and trends that emerge from the vast This makes it easy for researchers to create new Insight.