  What characterizes influential users in online health communities (OHCs)? We
hypothesize that (1) the emotional support received by OHC members can be
assessed from their sentiment ex-pressed in online interactions, and (2) such
assessments can help to identify influential OHC members. Through text mining
and sentiment analysis of users' online interactions, we propose a novel metric
that directly measures a user's ability to affect the sentiment of others.
Using dataset from an OHC, we demonstrate that this metric is highly effective
in identifying influential users. In addition, combining the metric with other
traditional measures further improves the identification of influential users.
This study can facilitate online community management and advance our
understanding of social influence in OHCs.
