The power of #physiotherapy: a social media hashtag investigation on X (formerly Twitter)

Author:

Mondal Himel1ORCID,Mickael Michel-Edwar2ORCID,Matin Maima2ORCID,Hrg Dalibor3ORCID,Smith Marc A.4ORCID,Matin Farhan Bin5ORCID,Stoyanov Jivko6ORCID,Parvanov Emil D.7ORCID,Atanasov Atanas G.8ORCID

Affiliation:

1. Department of Physiology, All India Institute of Medical Sciences, Deoghar, Jharkhand 814152, India

2. Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, 05-552 Magdalenka, Poland

3. Independent researcher, 42000 Varazdin, Croatia

4. Social Media Research Foundation, Redwood City, CA 94061-2206, USA

5. Department of Pharmacy, East West University, Aftabnagar, Dhaka 1212, Bangladesh

6. Swiss Paraplegic Research, 6207 Nottwil, Switzerland; Institute of Social and Preventive Medicine, University of Bern, Mittelstrasse 43, 3012 Bern, Switzerland

7. Department of Translational Stem Cell Biology, Research Institute of the Medical University of Varna, 9002 Varna, Bulgaria; Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, 1090 Vienna, Austria

8. Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, 05-552 Magdalenka, Poland; Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, 1090 Vienna, Austria

Abstract

Aim: The social media platform X, formerly known as Twitter, has emerged as a significant hub for healthcare-related conversations and sharing information. This study aims to investigate the impact and reach of the #physiotherapy hashtag on the X platform. Methods: We collected and analyzed tweets containing the hashtag #physiotherapy posted between September 1, 2022, and September 1, 2023. Data was retrieved from X using the Fedica analytics platform on October 26, 2023. The data were analyzed and expressed in number and percentage and categorical data were tested by chi-square test. Results: Over the course of one year, a total of 57,788 tweets were shared using #physiotherapy by 21,244 users, generating a remarkable 108,743,911 impressions. On average, there were 6 tweets posted per day (with a range from 3 to 9). Among the users, the majority (42%) had between 100 and 1000 followers, while 31.6% had fewer than 100 followers. The top three countries contributing to #physiotherapy tweets were the UK (29.9%), India (23.75%), and the USA (11.85%). An analysis of sentiment revealed that 84% of the tweets had a neutral tone, while 9% were positive and 7% were negative (P < 0.0001). Conclusions: The examination of tweets related to #physiotherapy unveiled a vibrant global dialogue, with active engagement from diverse backgrounds. Notably, contributions from the UK, India, and the USA were prominent.

Publisher

Open Exploration Publishing

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3