An Intelligent System to Protect Diabetic Patients from Misinformation on Twitter
Sharifah Alshehri1, Nourah Alessa2, Maryam Alhawiti3, Amal Majdua4, Resan Aljohani5, Nojood Aljehane6, Mohammed Alotaibi7
1Nourah Alessa, Faculty of Computers and Information Technology, University of Tabuk, Saudi Arabia.
2Maryam Alhawiti, Faculty of Computers and Information Technology, University of Tabuk, Saudi Arabia.
3Sharifah Alshehri, Faculty of Computers and Information Technology, University of Tabuk, Saudi Arabia.
4Amal Majdua, Faculty of Computers and Information Technology, University of Tabuk, Saudi Arabia.
5Resan Aljohani, Faculty of Computers and Information Technology, University of Tabuk, Saudi Arabia.
6Nojood Aljehane, Department of Computer Science, Faculty of Computers and Information Technology, University of Tabuk, Saudi Arabia.
7Mohammed Alotaibi, Department of Information Technology, Faculty of Computers & Information Technology, University of Tabuk, Saudi Arabia.
Manuscript received on 01 June 2023 | Revised Manuscript received on 17 June 2023 | Manuscript Accepted on 15 July 2023 | Manuscript published on 30 July 2023 | PP: 15-20 | Volume-12 Issue-8, July 2023 | Retrieval Number: 100.1/ijitee.H96400712823 | DOI: 10.35940/ijitee.H9640.0712823
Open Access | Editorial and Publishing Policies | Cite | Zenodo | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diabetes is a chronic disease requiring careful management and accurate health information access. Diabetic patients are particularly vulnerable to misinformation on social media, as they may be more likely to seek alternative treatments and self-medicate. This can have severe consequences for their health and well-being. Also, the spread of misinformation on social media, including Twitter, can negatively impact the health and treatment of diabetic patients. In this research, we propose developing an intelligent system to detect and mitigate the spread of misinformation about diabetes on the Twitter platform. The system will utilize artificial intelligence and natural language processing technologies to identify and classify tweets containing false information about diabetes. The proposed system has the potential to protect diabetic patients from the negative consequences of misinformation and support the provision of accurate health information on social media.
Keywords: Diabetes, Misinformation, Fake, NLP, Monitoring
Scope of the Article: Artificial Intelligence