Users’ Continuance Participation in the Online Peer-to-peer Healthcare Community: A Text Mining Approach
2015
- 237Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage237
- Abstract Views177
- Downloads60
Article Description
The online peer-to-peer healthcare communities are known as the platform where dispersed groups of patients and their families query information, seek and offer support, and connect with others. The success of such communities relies on users’ ongoing involvement to generate benefits for both individuals and the communities. This study attempts to understand users’ continuance participation in online peer-to-peer healthcare community by classifying users’ goals of participation based on the user-generated text contents. We proposed a rule-based classification framework to categorize users’ goals of posting contents into four categories: information seeking, experience sharing, information sharing, and social interaction. We formalize and test the relationship between users’ continuance participation and all four posting goals, and find that the first three goals have significant impact on users’ continuance participation. Our findings can help researchers and practitioners better understand users’ behavior in the online peer-to-peer healthcare community.
Bibliographic Details
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