Don’t Mention It? Analyzing User-Generated Content Signals for Early Adverse Event Warnings

With greater impetus on broad postmarket surveillance, the Voice of the Customer (VoC) has emerged as an important source of information for understanding consumer experiences and identifying potential issues. In organizations, risk management groups are increasingly interested in working with their information technology teams to develop robust VoC listening platforms. Two key challenges have impeded success. First, prior work has leveraged diverse sets of channels, adverse event types, and modeling methods, resulting in diverging conclusions regarding the viability and efficacy of various user-generated channels and accompanying modeling methods. Second, many existing detection methods rely on “mention models” that have low detection rates, have high false positives, and lack timeliness.

• 저널Information Systems Research · 30(3) · 1007–1028
• 토픽Advanced Text Analysis Techniques · Artificial Intelligence
• DOI10.1287/isre.2019.0847
• 저자Ahmed Abbasi, Jingjing Li, Donald Adjeroh, Marie A. Abate, Wanhong Zheng