Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385577346> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W4385577346 abstract "In the modern world, communication takes place over a large geographic region, and the Internet is expanding. Social media platforms enable text-based communication and human contact using either Emojis or text. The ability to express one’s emotions through emotion is crucial to human existence. Speaking, making gestures, showing facial expression, and writing in comments are all ways to express emotions. A fascinating field of study has just arisen, and researchers are delving deeper into a variety of sorts of analysis, with emotional analysis being the most popular. Emotional analysis comes in three flavours: positive, negative, and neutral. Giving computers the ability to perceive, comprehend, and elicit certain emotional traits in a manner similar to those of humans is the aim of emotional computingso that they can communicate naturally, amicably, vividly, and with the same emotional intelligence as people. The development goal of the next-generation computer is to figure out how to humanise it and adaptively create the cosiest discussion atmosphere for the dialogue objects. In today’s fiercely competitive business environment, gaining knowledge about consumer habits, wants, preferences, purchasing trends, and decision-making processes is crucial for brands and businesses. When determining the breadth and type of emotional analysis based on food reviews and feedback in e-commerce, our research will take a close look at the most often held points of view. A study on emotional analysis is required for social platforms because the information may become popular and have a big impact on social life. Emoji-based text-based emotion recognition is related to the NLP area (natural language processing). Additionally, we suggested the Adaboost algorithm as an approach to identifying emotion using only emojis. These techniques address the issue of identifying emotions both within and outside of sentences." @default.
- W4385577346 created "2023-08-05" @default.
- W4385577346 creator A5055274033 @default.
- W4385577346 creator A5068086826 @default.
- W4385577346 date "2023-05-25" @default.
- W4385577346 modified "2023-09-26" @default.
- W4385577346 title "Analysing the Emotions of Food Products Reviewsusing NLP and Adaboost Algorithm" @default.
- W4385577346 cites W2601994823 @default.
- W4385577346 cites W2792059071 @default.
- W4385577346 cites W2982579737 @default.
- W4385577346 cites W2999897215 @default.
- W4385577346 cites W3003815374 @default.
- W4385577346 cites W3157489682 @default.
- W4385577346 cites W3208938414 @default.
- W4385577346 cites W4226289402 @default.
- W4385577346 doi "https://doi.org/10.1109/accai58221.2023.10200516" @default.
- W4385577346 hasPublicationYear "2023" @default.
- W4385577346 type Work @default.
- W4385577346 citedByCount "0" @default.
- W4385577346 crossrefType "proceedings-article" @default.
- W4385577346 hasAuthorship W4385577346A5055274033 @default.
- W4385577346 hasAuthorship W4385577346A5068086826 @default.
- W4385577346 hasConcept C110875604 @default.
- W4385577346 hasConcept C136197465 @default.
- W4385577346 hasConcept C136764020 @default.
- W4385577346 hasConcept C154945302 @default.
- W4385577346 hasConcept C15744967 @default.
- W4385577346 hasConcept C162324750 @default.
- W4385577346 hasConcept C195704467 @default.
- W4385577346 hasConcept C202444582 @default.
- W4385577346 hasConcept C207347870 @default.
- W4385577346 hasConcept C21547014 @default.
- W4385577346 hasConcept C2778813691 @default.
- W4385577346 hasConcept C2779247141 @default.
- W4385577346 hasConcept C33923547 @default.
- W4385577346 hasConcept C41008148 @default.
- W4385577346 hasConcept C518677369 @default.
- W4385577346 hasConcept C66402592 @default.
- W4385577346 hasConcept C9652623 @default.
- W4385577346 hasConceptScore W4385577346C110875604 @default.
- W4385577346 hasConceptScore W4385577346C136197465 @default.
- W4385577346 hasConceptScore W4385577346C136764020 @default.
- W4385577346 hasConceptScore W4385577346C154945302 @default.
- W4385577346 hasConceptScore W4385577346C15744967 @default.
- W4385577346 hasConceptScore W4385577346C162324750 @default.
- W4385577346 hasConceptScore W4385577346C195704467 @default.
- W4385577346 hasConceptScore W4385577346C202444582 @default.
- W4385577346 hasConceptScore W4385577346C207347870 @default.
- W4385577346 hasConceptScore W4385577346C21547014 @default.
- W4385577346 hasConceptScore W4385577346C2778813691 @default.
- W4385577346 hasConceptScore W4385577346C2779247141 @default.
- W4385577346 hasConceptScore W4385577346C33923547 @default.
- W4385577346 hasConceptScore W4385577346C41008148 @default.
- W4385577346 hasConceptScore W4385577346C518677369 @default.
- W4385577346 hasConceptScore W4385577346C66402592 @default.
- W4385577346 hasConceptScore W4385577346C9652623 @default.
- W4385577346 hasLocation W43855773461 @default.
- W4385577346 hasOpenAccess W4385577346 @default.
- W4385577346 hasPrimaryLocation W43855773461 @default.
- W4385577346 hasRelatedWork W2748952813 @default.
- W4385577346 hasRelatedWork W2808800637 @default.
- W4385577346 hasRelatedWork W2899084033 @default.
- W4385577346 hasRelatedWork W3005503605 @default.
- W4385577346 hasRelatedWork W3032928500 @default.
- W4385577346 hasRelatedWork W3139257358 @default.
- W4385577346 hasRelatedWork W3182038225 @default.
- W4385577346 hasRelatedWork W3185877708 @default.
- W4385577346 hasRelatedWork W4213213868 @default.
- W4385577346 hasRelatedWork W4285325796 @default.
- W4385577346 isParatext "false" @default.
- W4385577346 isRetracted "false" @default.
- W4385577346 workType "article" @default.