title: Automatic extraction and identification of users' responses in Facebook medical quizzes.
abstract: BACKGROUND
  In the last few years the use of social media in medicine has grown exponentially, providing a new area of research based on the analysis and use of Web 2.0 capabilities. In addition, the use of social media in medical education is a subject of particular interest which has been addressed in several studies. One example of this application is the medical quizzes of The New England Journal of Medicine (NEJM) that regularly publishes a set of questions through their Facebook timeline.
  
  
  OBJECTIVE
  We present an approach for the automatic extraction of medical quizzes and their associated answers on a Facebook platform by means of a set of computer-based methods and algorithms.
  
  
  METHODS
  We have developed a tool for the extraction and analysis of medical quizzes stored on Facebook timeline at the NEJM Facebook page, based on a set of computer-based methods and algorithms using Java. The system is divided into two main modules: Crawler and Data retrieval.
  
  
  RESULTS
  The system was launched on December 31, 2014 and crawled through a total of 3004 valid posts and 200,081 valid comments. The first post was dated on July 23, 2009 and the last one on December 30, 2014. 285 quizzes were analyzed with 32,780 different users providing answers to the aforementioned quizzes. Of the 285 quizzes, patterns were found in 261 (91.58%). From these 261 quizzes where trends were found, we saw that users follow trends of incorrect answers in 13 quizzes and trends of correct answers in 248.
  
  
  CONCLUSIONS
  This tool is capable of automatically identifying the correct and wrong answers to a quiz provided on Facebook posts in a text format to a quiz, with a small rate of false negative cases and this approach could be applicable to the extraction and analysis of other sources after including some adaptations of the information on the Internet.
authors.affiliation: ETS de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus de Montegancedo, Boadilla del Monte, 28660 Madrid, Spain. Electronic address: alejandro.rodriguezg@upm.es.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Rodríguez-González
authors.affiliation: Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcon, 28223 Madrid, Spain. Electronic address: ernestina.menasalvas@upm.es.
authors.forename: Ernestina
authors.initials: E
authors.lastname: Menasalvas Ruiz
authors.affiliation: Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute (IMIM) - Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona (PRBB), Dr. Aiguader, 8808003 Barcelona, Spain. Electronic address: mmayer@imim.es.
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Mayer Pujadas
mesh_terms: D001331:Automation; D003625:Data Collection; D004501:Education, Medical / Q000379:methods*; D006801:Humans; D020407:Internet; D061108:Social Media
keywords: Data retrieval; Facebook; Health-related websites; Medical quizzes