Matches in SemOpenAlex for { <https://semopenalex.org/work/W4363673359> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W4363673359 endingPage "6404" @default.
- W4363673359 startingPage "6404" @default.
- W4363673359 abstract "The COVID-19 outbreak is a disastrous event that has elevated many psychological problems such as lack of employment and depression given abrupt social changes. Simultaneously, psychologists and social scientists have drawn considerable attention towards understanding how people express their sentiments and emotions during the pandemic. With the rise in COVID-19 cases with strict lockdowns, people expressed their opinions publicly on social networking platforms. This provides a deeper knowledge of human psychology at the time of disastrous events. By applying user-produced content on social networking platforms such as Twitter, the sentiments and views of people are analyzed to assist in introducing awareness campaigns and health intervention policies. The modern evolution of artificial intelligence (AI) and natural language processing (NLP) mechanisms has revealed remarkable performance in sentimental analysis (SA). This study develops a new Marine Predator Optimization with Natural Language Processing for Twitter Sentiment Analysis (MPONLP-TSA) for the COVID-19 Pandemic. The presented MPONLP-TSA model is focused on the recognition of sentiments that exist in the Twitter data during the COVID-19 pandemic. The presented MPONLP-TSA technique undergoes data preprocessing to convert the data into a useful format. Furthermore, the BERT model is used to derive word vectors. To detect and classify sentiments, a bidirectional recurrent neural network (BiRNN) model is utilized. Finally, the MPO algorithm is exploited for optimal hyperparameter tuning process, and it assists in enhancing the overall classification performance. The experimental validation of the MPONLP-TSA approach can be tested by utilizing the COVID-19 tweets dataset from the Kaggle repository. A wide comparable study reported a better outcome of the MPONLP-TSA method over current approaches." @default.
- W4363673359 created "2023-04-11" @default.
- W4363673359 creator A5053107720 @default.
- W4363673359 creator A5063895155 @default.
- W4363673359 creator A5066659990 @default.
- W4363673359 creator A5066744726 @default.
- W4363673359 creator A5068901793 @default.
- W4363673359 creator A5082306325 @default.
- W4363673359 creator A5084013473 @default.
- W4363673359 date "2023-04-09" @default.
- W4363673359 modified "2023-10-13" @default.
- W4363673359 title "Sustainable Artificial Intelligence-Based Twitter Sentiment Analysis on COVID-19 Pandemic" @default.
- W4363673359 cites W2319453305 @default.
- W4363673359 cites W3003618396 @default.
- W4363673359 cites W3011104345 @default.
- W4363673359 cites W3016994297 @default.
- W4363673359 cites W3025444948 @default.
- W4363673359 cites W3088268279 @default.
- W4363673359 cites W3092062385 @default.
- W4363673359 cites W3094733139 @default.
- W4363673359 cites W3103462848 @default.
- W4363673359 cites W3123995725 @default.
- W4363673359 cites W3127056209 @default.
- W4363673359 cites W3132251507 @default.
- W4363673359 cites W3146682110 @default.
- W4363673359 cites W3188846905 @default.
- W4363673359 cites W3192946602 @default.
- W4363673359 cites W3193706068 @default.
- W4363673359 cites W3211363741 @default.
- W4363673359 cites W4214494063 @default.
- W4363673359 cites W4224283955 @default.
- W4363673359 cites W4280625387 @default.
- W4363673359 cites W4293093826 @default.
- W4363673359 doi "https://doi.org/10.3390/su15086404" @default.
- W4363673359 hasPublicationYear "2023" @default.
- W4363673359 type Work @default.
- W4363673359 citedByCount "1" @default.
- W4363673359 crossrefType "journal-article" @default.
- W4363673359 hasAuthorship W4363673359A5053107720 @default.
- W4363673359 hasAuthorship W4363673359A5063895155 @default.
- W4363673359 hasAuthorship W4363673359A5066659990 @default.
- W4363673359 hasAuthorship W4363673359A5066744726 @default.
- W4363673359 hasAuthorship W4363673359A5068901793 @default.
- W4363673359 hasAuthorship W4363673359A5082306325 @default.
- W4363673359 hasAuthorship W4363673359A5084013473 @default.
- W4363673359 hasBestOaLocation W43636733591 @default.
- W4363673359 hasConcept C10551718 @default.
- W4363673359 hasConcept C119857082 @default.
- W4363673359 hasConcept C136764020 @default.
- W4363673359 hasConcept C142724271 @default.
- W4363673359 hasConcept C154945302 @default.
- W4363673359 hasConcept C204321447 @default.
- W4363673359 hasConcept C2522767166 @default.
- W4363673359 hasConcept C2779134260 @default.
- W4363673359 hasConcept C3008058167 @default.
- W4363673359 hasConcept C34736171 @default.
- W4363673359 hasConcept C41008148 @default.
- W4363673359 hasConcept C50644808 @default.
- W4363673359 hasConcept C518677369 @default.
- W4363673359 hasConcept C524204448 @default.
- W4363673359 hasConcept C66402592 @default.
- W4363673359 hasConcept C71924100 @default.
- W4363673359 hasConcept C89623803 @default.
- W4363673359 hasConceptScore W4363673359C10551718 @default.
- W4363673359 hasConceptScore W4363673359C119857082 @default.
- W4363673359 hasConceptScore W4363673359C136764020 @default.
- W4363673359 hasConceptScore W4363673359C142724271 @default.
- W4363673359 hasConceptScore W4363673359C154945302 @default.
- W4363673359 hasConceptScore W4363673359C204321447 @default.
- W4363673359 hasConceptScore W4363673359C2522767166 @default.
- W4363673359 hasConceptScore W4363673359C2779134260 @default.
- W4363673359 hasConceptScore W4363673359C3008058167 @default.
- W4363673359 hasConceptScore W4363673359C34736171 @default.
- W4363673359 hasConceptScore W4363673359C41008148 @default.
- W4363673359 hasConceptScore W4363673359C50644808 @default.
- W4363673359 hasConceptScore W4363673359C518677369 @default.
- W4363673359 hasConceptScore W4363673359C524204448 @default.
- W4363673359 hasConceptScore W4363673359C66402592 @default.
- W4363673359 hasConceptScore W4363673359C71924100 @default.
- W4363673359 hasConceptScore W4363673359C89623803 @default.
- W4363673359 hasIssue "8" @default.
- W4363673359 hasLocation W43636733591 @default.
- W4363673359 hasOpenAccess W4363673359 @default.
- W4363673359 hasPrimaryLocation W43636733591 @default.
- W4363673359 hasRelatedWork W2252197266 @default.
- W4363673359 hasRelatedWork W2382928216 @default.
- W4363673359 hasRelatedWork W2517235427 @default.
- W4363673359 hasRelatedWork W2562617836 @default.
- W4363673359 hasRelatedWork W2944636446 @default.
- W4363673359 hasRelatedWork W3148756070 @default.
- W4363673359 hasRelatedWork W3192794374 @default.
- W4363673359 hasRelatedWork W4205350312 @default.
- W4363673359 hasRelatedWork W4362613237 @default.
- W4363673359 hasRelatedWork W4379932966 @default.
- W4363673359 hasVolume "15" @default.
- W4363673359 isParatext "false" @default.
- W4363673359 isRetracted "false" @default.
- W4363673359 workType "article" @default.