Attitudes of Crohn's disease patients: Infodemiology case study and sentiment analysis of facebook and twitter posts

JMIR Public Health and Surveillance

Volumn 3, Issue 3, 2017, Pages

  Roccetti, Marco ^a   Marfia, Gustavo ^a   Salomoni, Paola ^a   Prandi, Catia ^b   Zagari, Rocco Maurizio ^a   Kengni, Faustine Linda Gningaye ^a   Bazzoli, Franco ^a   Montagnani, Marco ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

^b MADEIRA INTERACTIVE TECHNOLOGIES INSTITUTE   (Portugal)

Author keywords

Consumer health information; Health information systems; Public health informatics; Social networking

Indexed keywords

EID: 85046503101     PISSN: None     EISSN: 23692960     Source Type: Journal    
DOI: 10.2196/publichealth.7004     Document Type: Article

References (46)

1. Fox S, Duggan M. Pew Research Center. 2013. Health online 2013 URL:http://www.pewinternet.org/files/old-media/Files/ Reports/PIP_HealthOnline.pdf [accessed 2017-07-18] [WebCite Cache ID 6s3KK1rUX]
2. Scanfeld D, Scanfeld V, Larson E. Dissemination of health information through social networks: twitter and antibiotics. Am J Infect Control 2010 Apr;38(3):182-188. [doi: 10.1016/j.ajic.2009.11.004]
3. Cline R, Haynes KM. Consumer health information seeking on the Internet: the state of the art. Health Educ Res 2001 Dec;16(6):671-692. [Medline: 11780707]
4. Stellefson M, Chaney B, Barry AE, Chavarria E, Tennant B, Walsh-Childers K, et al. Web 2.0 chronic disease self-management for older adults: a systematic review. J Med Internet Res 2013 Feb;15(2):e35 [FREE Full text] [doi: 10.2196/jmir.2439] [Medline: 23410671]
5. Blog.google. I'm Feeling Yucky:(searching for symptoms on google URL:https://blog.google/products/search/ im-feeling-yucky-searching-for-symptoms/ [accessed 2017-04-18] [WebCite Cache ID 6poMo7QTV]
6. White RW, Tatonetti NP, Shah NH, Altman RB, Horvitz E. Web-scale pharmacovigilance: listening to signals from the crowd. J Am Med Inform Assoc 2013 May 01;20(3):404-408 [FREE Full text] [doi: 10.1136/amiajnl-2012-001482] [Medline: 23467469]
7. Eysenbach G. Infodemiology and infoveillance: framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. J Med Internet Res 2009;11(1):e11 [FREE Full text] [doi: 10.2196/jmir.1157] [Medline: 19329408]
8. Eysenbach G. Infodemiology: tracking flu-related searches on the web for syndromic surveillance. AMIA Annu Symp Proc 2006:244-248 [FREE Full text] [Medline: 17238340]
9. Chew C, Eysenbach G. Pandemics in the age of twitter: content analysis of tweets during the 2009 H1N1 outbreak. PLoS One 2010 Nov 29;5(11):e14118 [FREE Full text] [doi: 10.1371/journal.pone.0014118] [Medline: 21124761]
10. Gittelman S, Lange V, Gotway CC, Okoro CA, Lieb E, Dhingra SS, et al. A new source of data for public health surveillance: facebook likes. J Med Internet Res 2015;17(4):e98 [FREE Full text] [doi: 10.2196/jmir.3970] [Medline: 25895907]
11. Matsuda S, Aoki K, Tomizawa S, Sone M, Tanaka R, Kuriki H, et al. Analysis of patient narratives in disease blogs on the internet: an exploratory study of social pharmacovigilance. JMIR Public Health Surveill 2017 Feb 24;3(1):e10 [FREE Full text] [doi: 10.2196/publichealth.6872] [Medline: 28235749]
12. Nguyen QC, Li D, Meng H, Kath S, Nsoesie E, Li F, et al. Building a national neighborhood dataset from geotagged twitter data for indicators of happiness, diet, and physical activity. JMIR Public Health Surveill 2016 Oct 17;2(2):e158 [FREE Full text] [doi: 10.2196/publichealth.5869] [Medline: 27751984]
13. Ling R, Lee J. Disease monitoring and health campaign evaluation using google search activities for HIV and AIDS, stroke, colorectal cancer, and marijuana use in Canada: a retrospective observational study. JMIR Public Health Surveill 2016 Oct 12;2(2):e156 [FREE Full text] [doi: 10.2196/publichealth.6504] [Medline: 27733330]
14. Delir HP, Kang Y, Buchbinder R, Burstein F, Whittle S. Investigating subjective experience and the influence of weather among individuals with fibromyalgia: a content analysis of twitter. JMIR Public Health Surveill 2017 Jan 19;3(1):e4 [FREE Full text] [doi: 10.2196/publichealth.6344] [Medline: 28104577]
15. Koschack J, Weibezahl L, Friede T, Himmel W, Makedonski P, Grabowski J. Scientific versus experiential evidence: discourse analysis of the chronic cerebrospinal venous insufficiency debate in a multiple sclerosis forum. J Med Internet Res 2015 Jul 01;17(7):e159 [FREE Full text] [doi: 10.2196/jmir.4103] [Medline: 26133525]
16. Hamad EO, Savundranayagam MY, Holmes JD, Kinsella EA, Johnson AM. Toward a mixed-methods research approach to content analysis in the digital age: the combined content-analysis model and its applications to health care twitter feeds. J Med Internet Res 2016 Mar 08;18(3):e60 [FREE Full text] [doi: 10.2196/jmir.5391] [Medline: 26957477]
17. Thatcher A, Wretschko G, Fridjhon. Online flow experiences, problematic Internet use and internet procrastination. Comput Human Behav 2008 Sep;24(5):2236-2254. [doi: 10.1016/j.chb.2007.10.008]
18. Roccetti M, Casari A, Marfia G, August). Inside chronic autoimmune disease communities: a social networks perspective to Crohn's patient behavior and medical information. 2015 Presented at: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015; August 25-28, 2015; Paris, France p. 1089-1096. [doi: 10.1145/2808797.2808813]
19. Roccetti M, Prandi C, Salomoni P, Marfia G. Unleashing the true potential of social networks: confirming infliximab medical trials through facebook posts. Netw Model Anal Health Inform Bioinforma 2016;5:15. [doi: 10.1007/s13721-016-0122-9]
20. Bramer M. Principles of Data Mining. London: Springer; 2016.
21. Fayyad U, Piatetsky-Shapiro G, Smyth P. Knowledge discovery and data mining: towards a unifying framework. In: KDD'96 Proceedings of the Second International Conference on Knowledge Discovery and Data Mining. 1996 Presented at: Second International Conference on Knowledge Discovery and Data Mining; August 02-04, 1996; Portland, Oregon p. 82-88.
22. Lee K, Caverlee J, Webb S. Uncovering social spammers: social honeypots + machine learning. In: SIGIR '10 Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval.: ACM; 2010 Presented at: The 33rd international ACM SIGIR conference on Research development in information retrieval; July 19-23, 2010; Geneve, Switzerland p. 435-442. [doi: 10.1145/1835449.1835522]
23. Stringhini G, Kruegel C, Vigna G. Detecting spammers on social networks. In: ACSAC '10 Proceedings of the 26th Annual Computer Security Applications Conference. 2010 Presented at: The 26th annual computer security applications conference; December 06-10, 2010; Austin, TX p. 1-9. [doi: 10.1145/1920261.1920263]
24. Zhou X, Menche J, Barabási A, Sharma A. Human symptoms-disease network. Nat Commun 2014 Jun 26;5:4212. [doi: 10.1038/ncomms5212] [Medline: 24967666]
25. Koh H, Tan G. Data mining applications in healthcare. J Healthc Inf Manag 2005;19(2):64-72. [Medline: 15869215]
26. Milley A. Healthcare and data mining. Health Management Technology 2000;21(8):44-47.
27. Blei D. Probabilistic topic models. Commun ACM 2012;55(4):77. [doi: 10.1145/2133806.2133826]
28. Aggarwal C, Zhai C. Mining text data. In: Springer Science & Business Media. Berlin/Heidelberg, Germany: Springer Science & Business Media; 2012.
29. Cambria E. Affective computing and sentiment analysis. IEEE Intell Syst 2016 Mar;31(2):102-107. [doi: 10.1109/MIS.2016.31]
30. Smailovic J, Grcar M, Lavrac N, Žnidarši M. Predictive sentiment analysis of tweets: a stock market application. In: Holzinger A, Pasi G, editors. Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data. Berlin, Heidelberg: Springer; 2013.
31. Duh MS, Cremieux P, Audenrode MV, Vekeman F, Karner P, Zhang H, et al. Can social media data lead to earlier detection of drug-related adverse events? Pharmacoepidemiol Drug Saf 2016 Dec;25(12):1425-1433 [FREE Full text] [doi: 10.1002/pds.4090] [Medline: 27601271]
32. Fang X, Zhan J. Sentiment analysis using product review data. J Big Data 2015 Jun 16;2(1):1. [doi: 10.1186/s40537-015-0015-2]
33. Medhat W, Hassan A, Korashy H. Sentiment analysis algorithms and applications: a survey. Ain Shams Eng J 2014 Dec;5(4):1093-1113. [doi: 10.1016/j.asej.2014.04.011]
34. Wilson T, Hoffmann P, Somasundaran S, Kessler J, Wiebe J, Choi Y, et al. OpinionFinder: a system for subjectivity analysis. In: HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations. 2005 Presented at: HLT/EMNLP on Interactive Demonstrations; October 07, 2005; Vancouver, Canada p. 34-35. [doi: 10.3115/1225733.1225751]
35. Baldridge J. Apache. 2017. The opennlp project URL:http://opennlp.apache.org/index.html [accessed 2017-04-18] [WebCite Cache ID 6poN28Vpm]
36. Manning C, Surdeanu M, Bauer J, Finkel J, Bethard S, McClosky D. The Stanford CoreNLP natural language processing toolkit. 2014 Presented at: Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations; June 23-24, 2014; Baltimore, MD p. 55-60.
37. Bollen J, Mao H, Zeng X. Twitter mood predicts the stock market. Journal of Computational Science 2011 Mar;2(1):1-8. [doi: 10.1016/j.jocs.2010.12.007]
38. Hosmer J, Lemeshow S, Sturdivant RX. Applied logistic regression. Hoboken, NJ: John Wiley & Sons; 2013.
39. Allen I, Seaman C. ASQ. 2007. Likert scales and data analyses URL:http://asq.org/quality-progress/2007/07/statistics/ likert-scales-and-data-analyses.html?s=qp [accessed 2017-07-18] [WebCite Cache ID 6s3b9uZhh]
40. Duggan M, Ellison N, Lampe C, Lenhart A, Madden M. Pew Research Center. 2015. Social media update 2014 URL:http:/ /www.pewinternet.org/files/2015/01/PI_SocialMediaUpdate20144.pdf [accessed 2017-07-18] [WebCite Cache ID 6s3bJPKYZ]
41. Blomberg J, Burrell M, Guest G. An ethnographic approach to design. In: The human-computer interaction handbook. New Jersey: Lawrence Erlbaum Associates, Inc; 2002:964-986.
42. Roccetti M, Marfia G, Salomoni P, Prandi C, Zagari R, Gningaye F, et al. Unibo. 2017. Infliximab related facebook posts URL:http://www.cs.unibo.it/~marfia/Lista-Posts.docx [accessed 2017-05-16] [WebCite Cache ID 6qVFMOfZJ]
43. Eysenbach G, Wyatt J. Using the internet for surveys and health research. J Med Internet Res 2002 Nov;4(2):E13 [FREE Full text] [doi: 10.2196/jmir.4.2.e13] [Medline: 12554560]
44. Eysenbach G. Medicine 2.0: social networking, collaboration, participation, apomediation, and openness. J Med Internet Res 2008;10(3):e22 [FREE Full text] [doi: 10.2196/jmir.1030] [Medline: 18725354]
45. Colombel J, Loftus E, Tremaine W, Egan L, Harmsen WS, Schleck C, et al. The safety profile of infliximab in patients with Crohn's disease: the Mayo clinic experience in 500 patients. Gastroenterology 2004 Jan;126(1):19-31. [Medline: 14699483]
46. Caspersen S, Elkjaer M, Riis L, Pedersen N, Mortensen C, Jess T, Danish Crohn Colitis Database. Infliximab for inflammatory bowel disease in Denmark 1999-2005: clinical outcome and follow-up evaluation of malignancy and mortality. Clin Gastroenterol Hepatol 2008 Nov;6(11):1212-7; quiz 1176. [doi: 10.1016/j.cgh.2008.05.010] [Medline: 18848503]