Paper Type

ERF

Description

Research into online support communities is becoming more important as researchers strive to understand the dynamics behind these communities and the interactions of their participants. Since these communities are largely Q&A platforms where seekers request information or support, the quality of responses is increasingly relevant in most studies, yet this is a difficult variable to measure. We propose a method for measuring answer quality by using text analytics to determine the topics that are addressed in the questions and then determining the quality of responses based on whether the topics in the answer match the topics in the question. This research discusses how to generate this type of metric and demonstrates its validity using a unique data set from multiple mental health communities in China.

Paper Number

1430

Comments

SIG Health

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Aug 10th, 12:00 AM

Content Quality in Online Q&A Communities: An Approach for Measuring Content Quality

Research into online support communities is becoming more important as researchers strive to understand the dynamics behind these communities and the interactions of their participants. Since these communities are largely Q&A platforms where seekers request information or support, the quality of responses is increasingly relevant in most studies, yet this is a difficult variable to measure. We propose a method for measuring answer quality by using text analytics to determine the topics that are addressed in the questions and then determining the quality of responses based on whether the topics in the answer match the topics in the question. This research discusses how to generate this type of metric and demonstrates its validity using a unique data set from multiple mental health communities in China.

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