Identify the emotions of comment writers and analyze satisfaction level using ‘deep learning’ and ‘fuzzy decision structure’
Used in ‘consumer decision-making process’ analysis such as shopping mall item recommendation, service industry, etc.
Published in the latest issue of a globally prominent academic journal in the top 5% in the computer and IT sector
[June 22, 2021]
<Department of Computer Engineering Professor Hwang Do-sam (left) and Research Professor Phan Thi Huyen Trang (right)>
YU Department of Computer Engineering Professor Hwang Do-sam’s (63) research team drew the attention of academic and industrial sectors by developing a technology to identify the emotions of comment writers and to measure satisfaction level by analyzing online comments.
Professor Hwang’s team developed a system that measures the emotions of comment writers and measures their satisfaction level to help with third persons to make decision using ‘deep learning’ (mechanical learning technology where a computer learns using various data) and ‘fuzzy’ (theory of mathematically dealing with ambiguities included in the words, meanings, thoughts and measurements of humans) decision structures.
The research team explained their research outcomes stating, “Normally, when consumers shop online, there are many cases in which they make decisions referring to the product comments posted by other buyers. We developed a system to analyze the satisfaction level of comments using deep learning and fuzzy decision structure that are drawing attention as a next-generation research sector. This is more precise than existing satisfaction analysis techniques and it is possible to obtain more accurate results.”
This study was conducted as an international joint research with Poland. YU Department of Computer Engineering Research Professor Phan Thi Huyen Trang participated as the primary author, while Professor Hwang and Professor Ngoc Thanh Nguyen of the Wroclaw University of Science and Technology in Poland also led the research as joint corresponding authors. The research outcomes of Professor Hwang’s team was titled ‘Decision-making support system based on user satisfaction measures on Twitter’ and was carried in the latest issue (June 2021) of the internationally acclaimed academic journal (SCI) in the computer and IT sectors, <Information Science> top 5.01% in the world in the computer and IT sector).
Professor Hwang said, “The research results can be used for recommending products or in various decision-making systems. It will be especially helpful by using in portals and service industries that require identification of user emotions and decision-making processes,” while adding, “In the future, we will construct large-scale databases for different themes and fields, while elaborating the system through context analysis of comment sentences.”
