What makes an online suggestion a good one for online health communities

Zhengchao Yang, Sudha Ram, Faiz Currim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An increasing number of people search online for health information or suggestions when they are confronted with health problems. However, identifying good suggestions when inundated with a wide variety of responses is a big challenge. Most online forums don't provide an automated suggestion-rating procedure for users to locate the quality suggestions that meet their expectations. In this study, we focus on the problem of identifying good suggestions. We propose a novel framework that accounts for the dynamic nature of social media by modeling the evolution of features over time. We use a combination of LSTM time series prediction of temporal features and Adaptive Thresholding Normalization to address this problem. Our study discusses why evolving language features need to be considered to determine the quality of suggestions. Besides, our method can identify important language features that can boost the prediction ability of the best suggestions.

Original languageEnglish (US)
Title of host publication26th Americas Conference on Information Systems, AMCIS 2020
PublisherAssociation for Information Systems
ISBN (Electronic)9781733632546
StatePublished - 2020
Event26th Americas Conference on Information Systems, AMCIS 2020 - Salt Lake City, Virtual, United States
Duration: Aug 10 2020Aug 14 2020

Publication series

Name26th Americas Conference on Information Systems, AMCIS 2020

Conference

Conference26th Americas Conference on Information Systems, AMCIS 2020
CountryUnited States
CitySalt Lake City, Virtual
Period8/10/208/14/20

Keywords

  • Adaptive thresholding normalization
  • LSTM
  • Random forest
  • Readability
  • Text quality
  • Time series
  • Understandability

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications
  • Library and Information Sciences

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