title: Seeking insights about cycling mood disorders via anonymized search logs.
abstract: BACKGROUND
  Mood disorders affect a significant portion of the general population. Cycling mood disorders are characterized by intermittent episodes (or events) of the disease.
  
  
  OBJECTIVE
  Using anonymized Web search logs, we identify a population of people with significant interest in mood stabilizing drugs (MSD) and seek evidence of mood swings in this population.
  
  
  METHODS
  We extracted queries to the Microsoft Bing search engine made by 20,046 Web searchers over six months, separately explored searcher demographics using data from a large external panel of users, and sought supporting information from people with mood disorders via a survey. We analyzed changes in information needs over time relative to searches on MSD.
  
  
  RESULTS
  Queries for MSD focused on side effects and their relation to the disease. We found evidence of significant changes in search behavior and interests coinciding with days that MSD queries are made. These include large increases (>100%) in the access of nutrition information, commercial information, and adult materials. A survey of patients diagnosed with mood disorders provided evidence that repeated queries on MSD may come with exacerbations of mood disorder. A classifier predicting the occurrence of such queries one day before they are observed obtains strong performance (AUC=0.78).
  
  
  CONCLUSIONS
  Observed patterns in search behavior align with known behaviors and those highlighted by survey respondents. These observations suggest that searchers showing intensive interest in MSD may be patients who have been prescribed these drugs. Given behavioral dynamics, we surmise that the days on which MSD queries are made may coincide with commencement of mania or depression. Although we do not have data on mood changes and whether users have been diagnosed with bipolar illness, we see evidence of cycling in people who show interest in MSD and further show that we can predict impending shifts in behavior and interest.
authors.affiliation: Microsoft Research, Herzeliya, Israel. eladyt@yahoo.com.
authors.forename: Elad
authors.initials: E
authors.lastname: Yom-Tov
authors.forename: Ryen W
authors.initials: RW
authors.lastname: White
authors.forename: Eric
authors.initials: E
authors.lastname: Horvitz
mesh_terms: D000328:Adult; D001714:Bipolar Disorder / Q000188:drug therapy* / Q000453:epidemiology; D003625:Data Collection; D006801:Humans; D020407:Internet / Q000706:statistics & numerical data*; D011619:Psychotropic Drugs / Q000627:therapeutic use*; D057386:Search Engine
chemical_list: D011619:Psychotropic Drugs
keywords: bipolar disorder; information retrieval; machine learning; mood disorders