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Title: Scrutinising medical practitioners' Twitter feeds: an analysis

Authors: Arushi Jain; Vishal Bhatnagar; Nilanjan Dey; Amira S. Ashour; Fuqian Shi

Addresses: Indian Institute of Technology, Dhanbad, Jharkhand, India ' Ambedkar Institute of Advanced Communication Technologies and Research, Geeta Colony, Delhi, India ' Techno India College of Technology, Kolkata, West Bengal, India ' Tanta University, Gharbia Governorate, Egypt ' Wenzhou Medical University, Wenzhou City, 325035, China

Abstract: Mining of social media data has found widespread applications in recent times. Twitter feeds and Facebook posts are being used to device product marketing strategies, sentiment analysis, financial predictions and forebode alarming situations. Twitter feeds analysis can be applied for analysing the behaviour and experiences of medical practitioners. Doctors' informal conversations on Twitter can provide deep insights about their work experiences, their concerns about the profession, their feelings - pathos or excitement they feel - and the affecting conditions. In the present work, Twitter feed of doctors along with the Twitter hashtags are used to collect data from tweets with hashtags such as #DoctorProblems. Afterward, data analysis was performed to determine the major problems faced by the members of the medical fraternity. These problems were categorised into five main categories. The multi-label na

Keywords: big data; Hadoop distributed file system; HDFS; MapReduce; naïve Bayes multi-label classifier; Tweets; evaluation-based measure; label-based measure.

DOI: 10.1504/IJITM.2023.130063

International Journal of Information Technology and Management, 2023 Vol.22 No.1/2, pp.127 - 139

Accepted: 05 May 2019
Published online: 05 Apr 2023 *

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