Public perspectives of monkeypox in Twitter: A social media analysis using machine learning
Ramadan Abdelmoez Farahat, Mohammed Abdelwahab Yassin, Jaffar A. Al‐Tawfiq, Cosmin A. Bejan, Basel Abdelazeem
Abstract
ahead', 'turn', 'break', 'tired', 'politician', 'supply', 'surpass'). Note: They were ordered according to their frequency.(D).Prevalence of selected emotion keywords from the NRC lexicon across the 12 topics generated by the LDA model, showing that positive and negative emotions -fear, anger, anticip, trust, surprise, sadness, disgust, and joy -were the most common in the 12 topics.TABLE 1.The distribution of the 12 topics with the top 30 most relevant words.
Topics & Concepts
MonkeypoxSocial mediaPublic healthData scienceVirologyComputer scienceWorld Wide WebMedicineBiologyBiochemistryVacciniaGeneNursingRecombinant DNAPoxvirus research and outbreaksVirology and Viral DiseasesPlant Virus Research Studies