Matches in SemOpenAlex for { <https://semopenalex.org/work/W3131975632> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W3131975632 abstract "Sentiment analysis is a case of natural language processing that extracts the sentiment of people about any specific service, product, or the topic. Users spend a considerable amount of time scrolling through social media feeds to find something relatable, either emotionally or as a problem in their daily life that they want to solve. By analyzing the content produced by social media users, we can know if his opinion is relatively optimistic, neutral, or pessimistic about the subject – that varies from a service, news, a movie, etc. There are multiple approaches for sentiment analysis; first, there’s the Machine learning with its numerous methods that can be either supervised or unsupervised. Second, the Lexicon-based approach. Third, the combination of the two approaches – which is called a hybrid. Also, there are other approaches that we can add to get a more optimized result, such as working on improving text preprocessing techniques or by adding Fuzzy Logic approach and subjectivity detection." @default.
- W3131975632 created "2021-03-01" @default.
- W3131975632 creator A5051043130 @default.
- W3131975632 creator A5079736273 @default.
- W3131975632 creator A5084184064 @default.
- W3131975632 date "2021-01-01" @default.
- W3131975632 modified "2023-10-16" @default.
- W3131975632 title "Sentiment Analysis. A Comparative of Machine Learning and Fuzzy Logic in the Study Case of Brexit Sentiment on Social Media" @default.
- W3131975632 cites W1264135555 @default.
- W3131975632 cites W1692844682 @default.
- W3131975632 cites W1970104171 @default.
- W3131975632 cites W1979432867 @default.
- W3131975632 cites W2012070465 @default.
- W3131975632 cites W2079325629 @default.
- W3131975632 cites W2276215713 @default.
- W3131975632 cites W2417173111 @default.
- W3131975632 cites W2464619766 @default.
- W3131975632 cites W2580352794 @default.
- W3131975632 cites W2587838525 @default.
- W3131975632 cites W2714880811 @default.
- W3131975632 cites W2775040700 @default.
- W3131975632 cites W2802821787 @default.
- W3131975632 cites W2887856105 @default.
- W3131975632 cites W2917610441 @default.
- W3131975632 cites W2996665118 @default.
- W3131975632 cites W3007003543 @default.
- W3131975632 cites W422930727 @default.
- W3131975632 cites W4245152641 @default.
- W3131975632 doi "https://doi.org/10.1007/978-3-030-66840-2_9" @default.
- W3131975632 hasPublicationYear "2021" @default.
- W3131975632 type Work @default.
- W3131975632 sameAs 3131975632 @default.
- W3131975632 citedByCount "0" @default.
- W3131975632 crossrefType "book-chapter" @default.
- W3131975632 hasAuthorship W3131975632A5051043130 @default.
- W3131975632 hasAuthorship W3131975632A5079736273 @default.
- W3131975632 hasAuthorship W3131975632A5084184064 @default.
- W3131975632 hasConcept C105639569 @default.
- W3131975632 hasConcept C111472728 @default.
- W3131975632 hasConcept C119857082 @default.
- W3131975632 hasConcept C136764020 @default.
- W3131975632 hasConcept C138885662 @default.
- W3131975632 hasConcept C144133560 @default.
- W3131975632 hasConcept C154945302 @default.
- W3131975632 hasConcept C204321447 @default.
- W3131975632 hasConcept C2524010 @default.
- W3131975632 hasConcept C2776469822 @default.
- W3131975632 hasConcept C2778121359 @default.
- W3131975632 hasConcept C2910001868 @default.
- W3131975632 hasConcept C33923547 @default.
- W3131975632 hasConcept C34736171 @default.
- W3131975632 hasConcept C41008148 @default.
- W3131975632 hasConcept C518677369 @default.
- W3131975632 hasConcept C58166 @default.
- W3131975632 hasConcept C66402592 @default.
- W3131975632 hasConcept C90673727 @default.
- W3131975632 hasConcept C9992130 @default.
- W3131975632 hasConceptScore W3131975632C105639569 @default.
- W3131975632 hasConceptScore W3131975632C111472728 @default.
- W3131975632 hasConceptScore W3131975632C119857082 @default.
- W3131975632 hasConceptScore W3131975632C136764020 @default.
- W3131975632 hasConceptScore W3131975632C138885662 @default.
- W3131975632 hasConceptScore W3131975632C144133560 @default.
- W3131975632 hasConceptScore W3131975632C154945302 @default.
- W3131975632 hasConceptScore W3131975632C204321447 @default.
- W3131975632 hasConceptScore W3131975632C2524010 @default.
- W3131975632 hasConceptScore W3131975632C2776469822 @default.
- W3131975632 hasConceptScore W3131975632C2778121359 @default.
- W3131975632 hasConceptScore W3131975632C2910001868 @default.
- W3131975632 hasConceptScore W3131975632C33923547 @default.
- W3131975632 hasConceptScore W3131975632C34736171 @default.
- W3131975632 hasConceptScore W3131975632C41008148 @default.
- W3131975632 hasConceptScore W3131975632C518677369 @default.
- W3131975632 hasConceptScore W3131975632C58166 @default.
- W3131975632 hasConceptScore W3131975632C66402592 @default.
- W3131975632 hasConceptScore W3131975632C90673727 @default.
- W3131975632 hasConceptScore W3131975632C9992130 @default.
- W3131975632 hasLocation W31319756321 @default.
- W3131975632 hasOpenAccess W3131975632 @default.
- W3131975632 hasPrimaryLocation W31319756321 @default.
- W3131975632 hasRelatedWork W11033076 @default.
- W3131975632 hasRelatedWork W11244355 @default.
- W3131975632 hasRelatedWork W11991885 @default.
- W3131975632 hasRelatedWork W3484117 @default.
- W3131975632 hasRelatedWork W7737393 @default.
- W3131975632 hasRelatedWork W7939015 @default.
- W3131975632 hasRelatedWork W8321499 @default.
- W3131975632 hasRelatedWork W9292421 @default.
- W3131975632 hasRelatedWork W13002482 @default.
- W3131975632 hasRelatedWork W4233260 @default.
- W3131975632 isParatext "false" @default.
- W3131975632 isRetracted "false" @default.
- W3131975632 magId "3131975632" @default.
- W3131975632 workType "book-chapter" @default.