No abstract

Blogs, internet forums, social networks, and micro-blogging sites are some of the growing number of places where users can voice their opinions. Opinions on any given product, issue, service, or idea are contained in data, making them a valuable resource in their own right. Popular social networking services like Twitter, Facebook, and Google+ allows expressing views on a variety of topics, participating in discussions, or sending messages to a global user. Twitter sentiment analysis has received a lot of attention recently.Sentiment analysis is finding how a person feels about a topic from their written response about it and it can be separated into positive and negative through its use. Doing so enables to classify the tweets made by a user in to appropriate classification category based on which some decisions can be made. The literature proposed approaches to develop the classifiers on the Twitter datasets. Operations, including tokenization, stop-word removal, and stemming will be performed. NLP converts the text to a machine-readable representation. Artificial Intelligence (AI) combines NLP data to evaluate if a situation is positive or negative. The document’s subjectivity can be identified using ML and NLP techniques to categorize them in to positive, neutral, or negative. Performing sentiment analysis in Twitter data can be tedious due to limited size, unstructured nature, misspellings, slang, and abbreviations. For this task, a Tweet Analyzing Model for Cluster Set Optimization with Unique Identifier Tagging (TAM-CSO-UIT) was built using prospects to determine positive or negative sentiment in tweets obtained from Twitter. This approach assigns a +ve/-ve value to each entry in the Tweet database based on probability assignment using n-gram model. To perform this effectively the tweet dataset is considered as a sliding window of length L. The proposed model accurately analyses and classifies the tweets.

Background: Monkeypox has been declared as a Public Health Emergency of International Concern (PHEIC) by the WHO Director General (WHO-DG). Most of the G20 nations have reported Monkeypox outbreak. Policies developed and implemented in G20 countries for the prevention and control of monkeypox preparedness and response have global consequences. This rapid review aimed to map the monkeypox prevention and control policies planned and implemented in G20 nations in line with temporary recommendations issued by the WHO-DG. Methods: We mapped monkeypox prevention and control policies in G20 nations based on the WHO-DG recommendations. Medline (through PubMed), Scopus, and ProQuest Health and Medical Complete were searched to understand G20 preventative, diagnostic, and therapeutic policies. We also performed an extensive gray literature search through the Ministry of Health websites and newspaper through Google.  The documents/ studies that had an information on prevention, control and management guidelines/policies and published through journal, news articles and health ministry websites of G20 nations on monkeypox were included. We excluded the editorials, opinion, and perspective papers and studies published prior to May 6, 2022. Results: We obtained 671 articles with 10 articles included in the review. Additionally, we identified 55 documents from the gray literature. We included national guidelines of the 18 countries on the control, prevention, and management of monkeypox. National guidelines were compared with the WHO guidelines in terms of implementing coordinated response, engaging and protecting communities, surveillance and public health measures and international travel, clinical management and infection, prevention and control (IPC) measures and medical countermeasures research. Depending on the availability of resources, some recommendations are followed by nations while others are not. Conclusions: Coordinated response among states is key to contain the transmission of monkeypox. To bring a coordinated response, G20 nations are following temporary recommendations that are context specific to their nation.