Attitudes of Crohn's Disease Patients: Infodemiology Case Study and Sentiment Analysis of Facebook and Twitter Posts

Overview

Journal JMIR Public Health Surveill

Publisher JMIR Publications

Date 2017 Aug 11

PMID 28793981

Citations 30

Authors

Marco Roccetti

Gustavo Marfia

Paola Salomoni

Catia Prandi

Rocco Maurizio Zagari

Faustine Linda Gningaye Kengni

Franco Bazzoli

Marco Montagnani

Affiliations

Soon will be listed here.

Abstract

Background: Data concerning patients originates from a variety of sources on social media.

Objective: The aim of this study was to show how methodologies borrowed from different areas including computer science, econometrics, statistics, data mining, and sociology may be used to analyze Facebook data to investigate the patients' perspectives on a given medical prescription.

Methods: To shed light on patients' behavior and concerns, we focused on Crohn's disease, a chronic inflammatory bowel disease, and the specific therapy with the biological drug Infliximab. To gain information from the basin of big data, we analyzed Facebook posts in the time frame from October 2011 to August 2015. We selected posts from patients affected by Crohn's disease who were experiencing or had previously been treated with the monoclonal antibody drug Infliximab. The selected posts underwent further characterization and sentiment analysis. Finally, an ethnographic review was carried out by experts from different scientific research fields (eg, computer science vs gastroenterology) and by a software system running a sentiment analysis tool. The patient feeling toward the Infliximab treatment was classified as positive, neutral, or negative, and the results from computer science, gastroenterologist, and software tool were compared using the square weighted Cohen's kappa coefficient method.

Results: The first automatic selection process returned 56,000 Facebook posts, 261 of which exhibited a patient opinion concerning Infliximab. The ethnographic analysis of these 261 selected posts gave similar results, with an interrater agreement between the computer science and gastroenterology experts amounting to 87.3% (228/261), a substantial agreement according to the square weighted Cohen's kappa coefficient method (w2K=0.6470). A positive, neutral, and negative feeling was attributed to 36%, 27%, and 37% of posts by the computer science expert and 38%, 30%, and 32% by the gastroenterologist, respectively. Only a slight agreement was found between the experts' opinion and the software tool.

Conclusions: We show how data posted on Facebook by Crohn's disease patients are a useful dataset to understand the patient's perspective on the specific treatment with Infliximab. The genuine, nonmedically influenced patients' opinion obtained from Facebook pages can be easily reviewed by experts from different research backgrounds, with a substantial agreement on the classification of patients' sentiment. The described method allows a fast collection of big amounts of data, which can be easily analyzed to gain insight into the patients' perspective on a specific medical therapy.

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