{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:28:05Z","timestamp":1724459285938},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685335","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,22]]},"abstract":"<jats:p>Long COVID is a disease that makes it hard for patients to get an official diagnosis while it impacts their quality of life. Many people are turning to social networks such as Facebook, WhatsApp, Twitter (now X) to express their opinions and feelings regarding Long COVID. In this paper, positive (or neutral) and negative text messages in the Greek language, posted on the Twitter platform in 2022, regarding Long COVID are analyzed and popular discussion topics are extracted. Analysis revealed that when topic modelling follows sentiment analysis more coherent topics are created. Furthermore, ChatGPT is used to assign a label to each topic that, in turn, is assessed by a human expert.<\/jats:p>","DOI":"10.3233\/shti240821","type":"book-chapter","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:52:13Z","timestamp":1724410333000},"source":"Crossref","is-referenced-by-count":0,"title":["Greek Tweets on Long COVID: Topic Modelling Following Sentiment Analysis and ChatGPT Interpretation"],"prefix":"10.3233","author":[{"given":"Afroditi","family":"Katika","sequence":"first","affiliation":[{"name":"Department of Nursing, National and Kapodistrian University of Athens, Athens Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emmanouil","family":"Zoulias","sequence":"additional","affiliation":[{"name":"Department of Nursing, National and Kapodistrian University of Athens, Athens Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vassiliki","family":"Koufi","sequence":"additional","affiliation":[{"name":"Department of Digital Systems, School of Information and Communication Technologies, University of Piraeus, Piraeus Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Flora","family":"Malamateniou","sequence":"additional","affiliation":[{"name":"Department of Nursing, National and Kapodistrian University of Athens, Athens Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Digital Health and Informatics Innovations for Sustainable Health Care Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240821","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:52:13Z","timestamp":1724410333000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240821"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,22]]},"ISBN":["9781643685335"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240821","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,22]]}}}