Engagement as a Driver of Growth of Online Health Forums: Observational Study
Author(s) -
Rahul Gopalsamy,
Alexander Semenov,
Eduardo L. Pasiliao,
Scott McIntosh,
Alexander Nikolaev
Publication year - 2017
Publication title -
journal of medical internet research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.446
H-Index - 142
eISSN - 1439-4456
pISSN - 1438-8871
DOI - 10.2196/jmir.7249
Subject(s) - metric (unit) , exploit , observational study , user engagement , online community , value (mathematics) , tracking (education) , psychology , internet privacy , community engagement , computer science , data science , world wide web , public relations , business , medicine , marketing , computer security , political science , pedagogy , pathology , machine learning
Background The emerging research on nurturing the growth of online communities posits that it is in part attributed to network effects, wherein every increase in the volume of user-generated content increases the value of the community in the eyes of its potential new members. The recently introduced metric engagement capacity offers a means of quantitatively assessing the ability of online platform users to engage each other into generating content; meanwhile, the quantity engagement value is useful for quantifying communication-based platform use. If the claim that higher engagement leads to accelerated growth holds true for online health forums (OHFs), then engagement tracking should become an important tool in the arsenal of OHF managers. Indeed, it might allow for quantifying the ability of an OHF to exploit network effects, thus predicting the OHF’s future success. Objective This study aimed to empirically analyze the relationship between internal OHF use (quantified using engagement measurement) , and external growth. Methods We collected data from 7 OHFs posted between the years 1999 and 2016. Longitudinal analyses were conducted by evaluating engagement in the OHFs over time. We analyzed 2-way causality effects between the engagement value and metrics evaluating OHF growth using Granger causality tests. User activity metrics per week were correlated with engagement metrics, followed by linear regression analyses. Results Observational data showed a 1-way causal relationship between the OHF engagement value and reach ( P =.02). We detected a 2-way causal relationship between the engagement value and delurking, with further analysis indicating that the engagement value was more likely to cause delurking ( P <.001 with lag 2; for the reverse hypothesis, P =.01 with lag 2). Users who engaged each other more were more likely (up to 14 times, depending on how much one user engaged another) to develop personal connections. Finally, we found that the more engaging an OHF user was in a given week, the more likely (up to 2 times, depending on their ability to engage others) they were to remain active in the OHF in the following week. Conclusions This study supports the claim that network effects play an important role in accelerating OHF growth, opening the door to exploiting these effects in calculated ways. In such efforts, engagement metrics can be used to monitor the “health” of an OHF and to identify the users most important to its success.
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