User and Context Integrated Experience Mining in Online Health Communities

Jinhe Shi, Yi Chen

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

Abstract

Online Health Communities (OHCs) provide a platform for patients, caregivers, and researchers to exchange information and support each other. Identifying information that describes patient health experiences in OHCs has many important applications, such as trustworthy knowledge discovery and recommendation. To identify patient experience description, we observe that the same word may have different strengths as an indicator of patient experiences when written by different users. Based on this observation, we propose a User-Word Context Vector model, that holistically captures linguistic features of text, user information and context information to classify patient experiences in OHCs. Experimental evaluation shows that the proposed method significantly outperforms the existing methods on patient experience classification.

Original languageEnglish (US)
Title of host publicationCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages3457-3460
Number of pages4
ISBN (Electronic)9781450368599
DOIs
StatePublished - Oct 19 2020
Event29th ACM International Conference on Information and Knowledge Management, CIKM 2020 - Virtual, Online, Ireland
Duration: Oct 19 2020Oct 23 2020

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference29th ACM International Conference on Information and Knowledge Management, CIKM 2020
CountryIreland
CityVirtual, Online
Period10/19/2010/23/20

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Keywords

  • deep neural networks
  • experience mining
  • online health communities
  • user modeling

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