TY - GEN
T1 - A response quality model for online health communities
AU - Venkatesan, Srikanth
AU - Han, Wencui
AU - Sharman, Raj
PY - 2014
Y1 - 2014
N2 - It has been reported that about 113 million Americans has looked for health information on the internet. Patient safety can therefore be very easily compromised if the advice/information that people receive is incorrect. Particularly in case of a chronic and debilitating disease like Parkinson's disease, patients are very vulnerable to false information. Spread of misinformation can be a serious deterrent to information system use. However, the literature has been weak in linking the prevalence of misinformation on online social networks to the factors contributing to misinformation. This study seeks to reduce this gap by exploring the factors impacting the extent of misinformation in online social networking forum. Our findings show that the quality of a response is affected by clarity of the thread question, cumulative information quality and the users' potential for making useful contributions. The results from this study provide practical suggestions to reduce misinformation on social networks.
AB - It has been reported that about 113 million Americans has looked for health information on the internet. Patient safety can therefore be very easily compromised if the advice/information that people receive is incorrect. Particularly in case of a chronic and debilitating disease like Parkinson's disease, patients are very vulnerable to false information. Spread of misinformation can be a serious deterrent to information system use. However, the literature has been weak in linking the prevalence of misinformation on online social networks to the factors contributing to misinformation. This study seeks to reduce this gap by exploring the factors impacting the extent of misinformation in online social networking forum. Our findings show that the quality of a response is affected by clarity of the thread question, cumulative information quality and the users' potential for making useful contributions. The results from this study provide practical suggestions to reduce misinformation on social networks.
UR - https://www.scopus.com/pages/publications/85107715555
M3 - Conference contribution
SN - 9781634396943
T3 - 35th International Conference on Information Systems "Building a Better World Through Information Systems", ICIS 2014
BT - 35th International Conference on Information Systems "Building a Better World Through Information Systems", ICIS 2014
PB - Association for Information Systems
T2 - 35th International Conference on Information Systems: Building a Better World Through Information Systems, ICIS 2014
Y2 - 14 December 2014 through 17 December 2014
ER -