U-M Industrial and Operations Engineering (IOE) assistant professor, Jessie Yang, has received research funding from Dell Inc. for sentiment analysis of online user-generated data for business intelligence enrichment.
With the rapid development of social media and online shopping, online user-generated data, especially reviews are increasingly prolific. For this reason, understanding consumer opinions of products and services is more important to businesses than ever, especially given the longevity and wide-spread exposure of online reviews.
Various methods are currently available for gathering information of this type such as interviews, focus groups and observations. While these methods can provide valuable insights about products and services, they are time-consuming and sometimes difficult.
Online user-generated data, especially product reviews, provides a specific channel to understand consumers that is less time consuming to access, however, the huge amount of online reviews that are generated every day makes any kind of manual processing infeasible.
“We aim to develop new techniques to process user-generated data and discover useful patterns in large data sets within a feasible timeframe,” said Yang. “This funding will allow us to develop new texting mining algorithms for understanding customer needs and could greatly impact product development.”
“We aim to develop new techniques to process user-generated data and discover useful patterns in large data sets within a feasible timeframe.”
Jessie Yang
Assistant Professor, U-M Industrial & Operations Engineering
Yang joined U-M IOE in 2016. Her research focuses on the interactions between humans, and between humans and autonomous systems including robots. She wants to understand the underlying mechanisms governing these interactions and propose design solutions to facilitate such interactions.
Feng Zhou, assistant professor of industrial and manufacturing systems engineering at UM-Dearborn joins Yang on the project.
