Proceedings ArticleDOI
People on drugs: credibility of user statements in health communities
Subhabrata Mukherjee,Gerhard Weikum,Cristian Danescu-Niculescu-Mizil +2 more
- pp 65-74
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TLDR
The authors proposed a method for automatically establishing the credibility of user-generated medical statements and the trustworthiness of their authors by exploiting linguistic cues and distant supervision from expert sources, which can reliably extract side-effects and filter out false statements, while identifying trustworthy users that are likely to contribute valuable medical information.Abstract:
Online health communities are a valuable source of information for patients and physicians. However, such user-generated resources are often plagued by inaccuracies and misinformation. In this work we propose a method for automatically establishing the credibility of user-generated medical statements and the trustworthiness of their authors by exploiting linguistic cues and distant supervision from expert sources. To this end we introduce a probabilistic graphical model that jointly learns user trustworthiness, statement credibility, and language objectivity.We apply this methodology to the task of extracting rare or unknown side-effects of medical drugs --- this being one of the problems where large scale non-expert data has the potential to complement expert medical knowledge. We show that our method can reliably extract side-effects and filter out false statements, while identifying trustworthy users that are likely to contribute valuable medical information.read more
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References
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