title: Investigating Subjective Experience and the Influence of Weather Among Individuals With Fibromyalgia: A Content Analysis of Twitter.
abstract: BACKGROUND
  Little is understood about the determinants of symptom expression in individuals with fibromyalgia syndrome (FMS). While individuals with FMS often report environmental influences, including weather events, on their symptom severity, a consistent effect of specific weather conditions on FMS symptoms has yet to be demonstrated. Content analysis of a large number of messages by individuals with FMS on Twitter can provide valuable insights into variation in the fibromyalgia experience from a first-person perspective.
  
  
  OBJECTIVE
  The objective of our study was to use content analysis of tweets to investigate the association between weather conditions and fibromyalgia symptoms among individuals who tweet about fibromyalgia. Our second objective was to gain insight into how Twitter is used as a form of communication and expression by individuals with fibromyalgia and to explore and uncover thematic clusters and communities related to weather.
  
  
  METHODS
  Computerized sentiment analysis was performed to measure the association between negative sentiment scores (indicative of severe symptoms such as pain) and coincident environmental variables. Date, time, and location data for each individual tweet were used to identify corresponding climate data (such as temperature). We used graph analysis to investigate the frequency and distribution of domain-related terms exchanged in Twitter and their association strengths. A community detection algorithm was applied to partition the graph and detect different communities.
  
  
  RESULTS
  We analyzed 140,432 tweets related to fibromyalgia from 2008 to 2014. There was a very weak positive correlation between humidity and negative sentiment scores (r=.009, P=.001). There was no significant correlation between other environmental variables and negative sentiment scores. The graph analysis showed that "pain" and "chronicpain" were the most frequently used terms. The Louvain method identified 6 communities. Community 1 was related to feelings and symptoms at the time (subjective experience). It also included a list of weather-related terms such as "weather," "cold," and "rain."
  
  
  CONCLUSIONS
  According to our results, a uniform causal effect of weather variation on fibromyalgia symptoms at the group level remains unlikely. Any impact of weather on fibromyalgia symptoms may vary geographically or at an individual level. Future work will further explore geographic variation and interactions focusing on individual pain trajectories over time.
authors.affiliation: Faculty of Information Technology, Monash University, Melbourne, Australia.
authors.forename: Pari
authors.identifier: http://orcid.org/0000-0001-9922-1214
authors.initials: P
authors.lastname: Delir Haghighi
authors.affiliation: Faculty of Information Technology, Monash University, Melbourne, Australia.
authors.forename: Yong-Bin
authors.identifier: http://orcid.org/0000-0002-0120-2582
authors.initials: YB
authors.lastname: Kang
authors.affiliation: Monash Department of Clinical Epidemiology, Monash University, Melbourne, Australia.
authors.forename: Rachelle
authors.identifier: http://orcid.org/0000-0002-0597-0933
authors.initials: R
authors.lastname: Buchbinder
authors.affiliation: Faculty of Information Technology, Monash University, Melbourne, Australia.
authors.forename: Frada
authors.identifier: http://orcid.org/0000-0001-8258-0878
authors.initials: F
authors.lastname: Burstein
authors.affiliation: The Queen Elizabeth Hospital, Adelaide, Australia.
authors.forename: Samuel
authors.identifier: http://orcid.org/0000-0001-7417-7691
authors.initials: S
authors.lastname: Whittle
keywords: Twitter messaging; fibromyalgia; infodemiology; pain; sentiment analysis; social networks; weather