{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T16:17:19Z","timestamp":1790957839683,"version":"4.1.0"},"reference-count":107,"publisher":"JMIR Publications Inc.","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Nowadays, the use of social media is part of daily life, with more and more people, including governments and health organizations, using at least one platform regularly. Social media enables users to interact among large groups of people that share the same interests and suffer the same afflictions. Notably, these channels promote the ability to find and share information about health and medical conditions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to characterize the bowel disease (BD) community on Twitter, in particular how patients understand, discuss, feel, and react to the condition. The main questions were as follows: Which are the main communities and most influential users?; Where are the main content providers from?; What are the key biomedical and scientific topics under discussion? How are topics interrelated in patient communications?; How do external events influence user activity?; What kind of external sources of information are being promoted?<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>To answer these questions, a dataset of tweets containing terms related to BD conditions was collected from February to August 2018, accounting for a total of 24,634 tweets from 13,295 different users. Tweet preprocessing entailed the extraction of textual contents, hyperlinks, hashtags, time, location, and user information. Missing and incomplete information about the user profiles was completed using different analysis techniques. Semantic tweet topic analysis was supported by a lexicon-based entity recognizer. Furthermore, sentiment analysis enabled a closer look into the opinions expressed in the tweets, namely, gaining a deeper understanding of patients\u2019 feelings and experiences.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Health organizations received most of the communication, whereas BD patients and experts in bowel conditions and nutrition were among those tweeting the most. In general, the BD community was mainly discussing symptoms, BD-related diseases, and diet-based treatments. Diarrhea and constipation were the most commonly mentioned symptoms, and cancer, anxiety disorder, depression, and chronic inflammations were frequently part of BD-related tweets. Most patient tweets discussed the bad side of BD conditions and other related conditions, namely, depression, diarrhea, and fibromyalgia. In turn, gluten-free diets and probiotic supplements were often mentioned in patient tweets expressing positive emotions. However, for the most part, tweets containing mentions to foods and diets showed a similar distribution of negative and positive sentiments because the effects of certain food components (eg, fiber, iron, and magnesium) were perceived differently, depending on the state of the disease and other personal conditions of the patients. The benefits of medical cannabis for the treatment of different chronic diseases were also highlighted.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study evidences that Twitter is becoming an influential space for conversation about bowel conditions, namely, patient opinions about associated symptoms and treatments. So, further qualitative and quantitative content analyses hold the potential to support decision making among health-related stakeholders, including the planning of awareness campaigns.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/12610","type":"journal-article","created":{"date-parts":[[2019,4,26]],"date-time":"2019-04-26T19:15:36Z","timestamp":1556306136000},"page":"e12610","source":"Crossref","is-referenced-by-count":55,"title":["Using Twitter to Understand the Human Bowel Disease Community: Exploratory Analysis of Key Topics"],"prefix":"10.2196","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1349-6562","authenticated-orcid":false,"given":"Mart\u00edn","family":"P\u00e9rez-P\u00e9rez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6740-3742","authenticated-orcid":false,"given":"Gael","family":"P\u00e9rez-Rodr\u00edguez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3943-8013","authenticated-orcid":false,"given":"Florentino","family":"Fdez-Riverola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8401-5362","authenticated-orcid":false,"given":"An\u00e1lia","family":"Louren\u00e7o","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2019,8,15]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","DOI":"10.2307\/j.ctt1g69z35","author":"Miller, D","year":"2016","journal-title":"How the World Changed Social Media"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/HICSS.2014.219"},{"key":"ref3","unstructured":"SmithAAndersonMPew Research Center2018Social Media Use in 2018 https:\/\/www.pewinternet.org\/2018\/03\/01\/social-media-use-in-2018\/"},{"key":"ref4","unstructured":"European Commission2017Eurostat Regional Yearbook: 2017 Edition https:\/\/ec.europa.eu\/eurostat\/statistics-explained\/index.php\/Eurostat_regional_yearbook"},{"key":"ref5","doi-asserted-by":"crossref","DOI":"10.3726\/978-1-4539-1170-9","author":"Weller, K","year":"2014","journal-title":"Twitter and Society"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.1933"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2005.01.001"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2015.01.014"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2009.10.003"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2004.04.011"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1093\/ibd\/izy280"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.4137\/CGast.S12731"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1053\/j.gastro.2011.10.001"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.15585\/mmwr.mm6619a9"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1186\/s13075-017-1251-y"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.7072"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.3298"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.9266"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.2196\/diabetes.6256"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1097\/MIB.0000000000000713"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.9870"},{"key":"ref22","unstructured":"YamamotoYTwitter4J20182018-07-10Twitter4J - 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