title: Community Structure of a Mental Health Internet Support Group: Modularity in User Thread Participation.
abstract: BACKGROUND
  Little is known about the community structure of mental health Internet support groups, quantitatively. A greater understanding of the factors, which lead to user interaction, is needed to explain the design information of these services and future research concerning their utility.
  
  
  OBJECTIVE
  A study was conducted to determine the characteristics of users associated with the subgroup community structure of an Internet support group for mental health issues.
  
  
  METHODS
  A social network analysis of the Internet support group BlueBoard (blueboard.anu.edu.au) was performed to determine the modularity of the community using the Louvain method. Demographic characteristics age, gender, residential location, type of user (consumer, carer, or other), registration date, and posting frequency in subforums (depression, generalized anxiety, social anxiety, panic disorder, bipolar disorder, obsessive compulsive disorder, borderline personality disorder, eating disorders, carers, general (eg, "chit chat"), and suggestions box) of the BlueBoard users were assessed as potential predictors of the resulting subgroup structure.
  
  
  RESULTS
  The analysis of modularity identified five main subgroups in the BlueBoard community. Registration date was found to be the largest contributor to the modularity outcome as observed by multinomial logistic regression. The addition of this variable to the final model containing all other factors improved its classification accuracy by 46.3%, that is, from 37.9% to 84.2%. Further investigation of this variable revealed that the most active and central users registered significantly earlier than the median registration time in each group.
  
  
  CONCLUSIONS
  The five subgroups resembled five generations of BlueBoard in distinct eras that transcended discussion about different mental health issues. This finding may be due to the activity of highly engaged and central users who communicate with many other users. Future research should seek to determine the generalizability of this finding and investigate the role that highly active and central users may play in the formation of this phenomenon.
authors.affiliation: National Institute for Mental Health Research, Research School of Population Health, The Australian National University, Acton, Australia. Bradley.Carron-Arthur@anu.edu.au.
authors.forename: Bradley
authors.identifier: http://orcid.org/0000-0001-6853-7902
authors.initials: B
authors.lastname: Carron-Arthur
authors.forename: Julia
authors.identifier: http://orcid.org/0000-0001-9910-0455
authors.initials: J
authors.lastname: Reynolds
authors.forename: Kylie
authors.identifier: http://orcid.org/0000-0003-4160-492X
authors.initials: K
authors.lastname: Bennett
authors.forename: Anthony
authors.identifier: http://orcid.org/0000-0002-0399-4798
authors.initials: A
authors.lastname: Bennett
authors.forename: John Alastair
authors.identifier: http://orcid.org/0000-0002-0668-5982
authors.initials: JA
authors.lastname: Cunningham
authors.forename: Kathleen Margaret
authors.identifier: http://orcid.org/0000-0003-1556-0708
authors.initials: KM
authors.lastname: Griffiths
keywords: internet; mental health; modularity; social network; super user; support group