Finding influential users of online health communities

a new metric based on sentiment influence.

Kang Zhao, John Yen, Greta Greer, Baojun Qiu, Prasenjit Mitra, Kenneth Portier

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

Online health communities (OHCs) have become a major source of support for people with health problems. This research tries to improve our understanding of social influence and to identify influential users in OHCs. The outcome can facilitate OHC management, improve community sustainability, and eventually benefit OHC users. Through text mining and sentiment analysis of users' online interactions, the research revealed sentiment dynamics in threaded discussions. A novel metric--the number of influential responding replies--was proposed to directly measure a user's ability to affect the sentiment of others. Using the dataset from a popular OHC, the research demonstrated that the proposed metric is highly effective in identifying influential users. In addition, combining the metric with other traditional measures further improves the identification of influential users. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Original languageEnglish
JournalJournal of the American Medical Informatics Association : JAMIA
Volume21
Issue numbere2
DOIs
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Health
Licensure
Research
Data Mining
Insurance Benefits
Datasets

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Finding influential users of online health communities : a new metric based on sentiment influence. / Zhao, Kang; Yen, John; Greer, Greta; Qiu, Baojun; Mitra, Prasenjit; Portier, Kenneth.

In: Journal of the American Medical Informatics Association : JAMIA, Vol. 21, No. e2, 2014.

Research output: Contribution to journalArticle

Zhao, Kang ; Yen, John ; Greer, Greta ; Qiu, Baojun ; Mitra, Prasenjit ; Portier, Kenneth. / Finding influential users of online health communities : a new metric based on sentiment influence. In: Journal of the American Medical Informatics Association : JAMIA. 2014 ; Vol. 21, No. e2.
@article{e760179cbbd94a1eb596326e0e360cd8,
title = "Finding influential users of online health communities: a new metric based on sentiment influence.",
abstract = "Online health communities (OHCs) have become a major source of support for people with health problems. This research tries to improve our understanding of social influence and to identify influential users in OHCs. The outcome can facilitate OHC management, improve community sustainability, and eventually benefit OHC users. Through text mining and sentiment analysis of users' online interactions, the research revealed sentiment dynamics in threaded discussions. A novel metric--the number of influential responding replies--was proposed to directly measure a user's ability to affect the sentiment of others. Using the dataset from a popular OHC, the research demonstrated that the proposed metric is highly effective in identifying influential users. In addition, combining the metric with other traditional measures further improves the identification of influential users. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.",
author = "Kang Zhao and John Yen and Greta Greer and Baojun Qiu and Prasenjit Mitra and Kenneth Portier",
year = "2014",
doi = "10.1136/amiajnl-2013-002282",
language = "English",
volume = "21",
journal = "Journal of the American Medical Informatics Association",
issn = "1067-5027",
publisher = "Oxford University Press",
number = "e2",

}

TY - JOUR

T1 - Finding influential users of online health communities

T2 - a new metric based on sentiment influence.

AU - Zhao, Kang

AU - Yen, John

AU - Greer, Greta

AU - Qiu, Baojun

AU - Mitra, Prasenjit

AU - Portier, Kenneth

PY - 2014

Y1 - 2014

N2 - Online health communities (OHCs) have become a major source of support for people with health problems. This research tries to improve our understanding of social influence and to identify influential users in OHCs. The outcome can facilitate OHC management, improve community sustainability, and eventually benefit OHC users. Through text mining and sentiment analysis of users' online interactions, the research revealed sentiment dynamics in threaded discussions. A novel metric--the number of influential responding replies--was proposed to directly measure a user's ability to affect the sentiment of others. Using the dataset from a popular OHC, the research demonstrated that the proposed metric is highly effective in identifying influential users. In addition, combining the metric with other traditional measures further improves the identification of influential users. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

AB - Online health communities (OHCs) have become a major source of support for people with health problems. This research tries to improve our understanding of social influence and to identify influential users in OHCs. The outcome can facilitate OHC management, improve community sustainability, and eventually benefit OHC users. Through text mining and sentiment analysis of users' online interactions, the research revealed sentiment dynamics in threaded discussions. A novel metric--the number of influential responding replies--was proposed to directly measure a user's ability to affect the sentiment of others. Using the dataset from a popular OHC, the research demonstrated that the proposed metric is highly effective in identifying influential users. In addition, combining the metric with other traditional measures further improves the identification of influential users. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

UR - http://www.scopus.com/inward/record.url?scp=84905286162&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84905286162&partnerID=8YFLogxK

U2 - 10.1136/amiajnl-2013-002282

DO - 10.1136/amiajnl-2013-002282

M3 - Article

VL - 21

JO - Journal of the American Medical Informatics Association

JF - Journal of the American Medical Informatics Association

SN - 1067-5027

IS - e2

ER -