Twitter sentiment analysis for COVID-19 associated mucormycosis

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dc.contributor.authorSingh, Maneeten_US
dc.contributor.authorDhillon, Hennaav Kauren_US
dc.contributor.authorIchhpujani, Parulen_US
dc.contributor.authorIyengar, Sudarshanen_US
dc.contributor.authorKaur, Rishemjiten_US
dc.date.accessioned2023-08-25T06:33:00Z
dc.date.available2023-08-25T06:33:00Z
dc.date.issued2022-05
dc.description.abstractPurpose: COVID?19?associated mucormycosis (CAM) was a serious public health problem during the second wave of COVID?19 in India. We planned to analyze public perceptions by sentiment analysis of Twitter data regarding CAM. Methods: In this observational study, the application programming interface (API) provided by the Twitter platform was used for extracting real?time conversations by using keywords related to mucormycosis (colloquially known as “black fungus”), from May 3 to August 29, 2021. Lexicon?based sentiment analysis of the tweets was done using the Vader sentiment analysis tool. To identify the overall sentiment of a user on any given topic, an algorithm to label a user “k” based on their sentiments was used. Results: A total of 4,01,037 tweets were collected between May 3 and August 29, 2021, and the peak frequency of 1,60,000 tweets was observed from May 17 to May 23, 2021. Positive sentiment tweets constituted a larger share as compared to negative sentiment tweets, with weekly variations. A temporal analysis of the demand for utilities showed that the demand was high in the initial period but decreased with time, which was associated with the availability of resources. Conclusion: Sentiment analysis using Twitter data revealed that social media platforms are gaining popularity to express one’s emotions during the ongoing COVID?19 pandemic. In our study, time?based assessment of tweets showed a reduction over time in the frequency of negative sentiment tweets. The polarization in the retweet network of users, based on sentiment polarity, showed that the users were well connected, highlighting the fact that such issues bond our society rather than segregating it.en_US
dc.identifier.affiliationsDepartment of Computer Science and Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, Indiaen_US
dc.identifier.affiliationsDepartment of Ophthalmology, Government Medical College and Hospital, Chandigarh, Indiaen_US
dc.identifier.affiliationsPrincipal Scientist, CSIR-Central Scientific Instruments Organisation, Chandigarh, Indiaen_US
dc.identifier.affiliationsAcademy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, Indiaen_US
dc.identifier.citationSingh Maneet, Dhillon Hennaav Kaur, Ichhpujani Parul, Iyengar Sudarshan, Kaur Rishemjit. Twitter sentiment analysis for COVID-19 associated mucormycosis. Indian Journal of Ophthalmology. 2022 May; 70(5): 1773-1779en_US
dc.identifier.issn1998-3689
dc.identifier.issn0301-4738
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/224319
dc.languageenen_US
dc.publisherAll India Ophthalmological Societyen_US
dc.relation.issuenumber5en_US
dc.relation.volume70en_US
dc.source.urihttps://doi.org/10.4103/ijo.IJO_324_22en_US
dc.subjectAmphotericin Ben_US
dc.subjectCOVID?19en_US
dc.subjectCOVID?associated mucormycosisen_US
dc.subjectmucormycosisen_US
dc.subjectsentiment analysisen_US
dc.subjectTwitteren_US
dc.titleTwitter sentiment analysis for COVID-19 associated mucormycosisen_US
dc.typeJournal Articleen_US
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