FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4286009750> ?p ?o ?g. }

• W4286009750 endingPage "8" @default.
• W4286009750 startingPage "1" @default.
• W4286009750 abstract "Film is an essential expression of a country's cultural soft power in terms of cross-cultural exchange. In addition, film is also the most direct and favourable means of communication. Along with the expansion and development of the Chinese film market, outstanding animation films have emerged in recent years. Animated films have both artistic and commercial properties and can not only have a cultural impact but can also contribute to economic growth. For this reason, our country is now paying more and more attention to the development of animated films. Specifically, animated films not only represent a country's cultural soft power and national image, but they are also a symbol of the strength of a country's cultural industry. As a reflection and extension of China's culture and ideology, animated films play an important role in enhancing cultural confidence and cultural export. In recent years, China's economy has shown a steady and sustained growth trend. At the same time, with the rapid development of internet technology, social networking has gradually penetrated into all aspects of people's lives. Various social networking forums, websites, and sites have emerged. While satisfying a wide range of needs, they also provide information on product reviews, social reviews, and service reviews. These reviews contain feedback from the reviewer about the subject of the review. Tapping into the emotions in these reviews can provide consumers with shopping references and help businesses to optimise their products and improve their business strategies. With the help of modern internet technology and information technology, the modern movie industry, such as Cat's Eye Movies and other internet entertainment service platforms, has developed a model of online ticketing, offline movie viewing, and online reviews and feedback. The content of the reviews on these movie websites fully reflects the attitudinal views of the movie-going community. These reviews play a decisive role in the box office and the further spread of culture. As a result, in order to better understand the audience's emotional tendencies and needs, it is necessary to carry out sentiment analysis and deep semantic mining of animated film reviews. As the evaluation of film works considers many factors and is complex and variable, the choice of model is crucial in the process of sentiment analysis. Machine learning models represented by deep neural networks are more tolerant of sentence noise and have strong information discrimination and feature self-learning capabilities. As a result, intelligent machine learning is more advantageous for sentiment classification tasks. This study is a combination of textual data mining and statistical analysis from the perspective of viewers' comments to study the online reviews of animation films from different countries. At the same time, this research hopes to uncover meaningful information from the film reviews and the gap between Chinese and other countries' animation films, in order to provide a little help for the rise of domestic animation films." @default.
• W4286009750 created "2022-07-21" @default.
• W4286009750 creator A5007971077 @default.
• W4286009750 creator A5018493626 @default.
• W4286009750 creator A5064548129 @default.
• W4286009750 creator A5071068810 @default.
• W4286009750 date "2022-07-20" @default.
• W4286009750 modified "2023-09-30" @default.
• W4286009750 title "Sentiment Analysis of Animated Film Reviews Using Intelligent Machine Learning" @default.
• W4286009750 cites W2581007101 @default.
• W4286009750 cites W2586757216 @default.
• W4286009750 cites W2598930435 @default.
• W4286009750 cites W2600147483 @default.
• W4286009750 cites W2615182107 @default.
• W4286009750 cites W2627045032 @default.
• W4286009750 cites W2741968387 @default.
• W4286009750 cites W2743671341 @default.
• W4286009750 cites W2773275680 @default.
• W4286009750 cites W2922114517 @default.
• W4286009750 cites W2926264417 @default.
• W4286009750 cites W2964280771 @default.
• W4286009750 cites W2966501701 @default.
• W4286009750 cites W2977454001 @default.
• W4286009750 cites W2993843842 @default.
• W4286009750 cites W3011627019 @default.
• W4286009750 cites W3037041048 @default.
• W4286009750 cites W3042911113 @default.
• W4286009750 cites W3048066448 @default.
• W4286009750 cites W3112717615 @default.
• W4286009750 cites W3116298595 @default.
• W4286009750 cites W3125845910 @default.
• W4286009750 cites W3127961343 @default.
• W4286009750 cites W3134570971 @default.
• W4286009750 cites W3211904197 @default.
• W4286009750 cites W4200258695 @default.
• W4286009750 cites W4220946742 @default.
• W4286009750 cites W4225901288 @default.
• W4286009750 cites W4226277040 @default.
• W4286009750 cites W4245416552 @default.
• W4286009750 cites W2950516111 @default.
• W4286009750 doi "https://doi.org/10.1155/2022/8517205" @default.
• W4286009750 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35909842" @default.
• W4286009750 hasPublicationYear "2022" @default.
• W4286009750 type Work @default.
• W4286009750 citedByCount "0" @default.
• W4286009750 crossrefType "journal-article" @default.
• W4286009750 hasAuthorship W4286009750A5007971077 @default.
• W4286009750 hasAuthorship W4286009750A5018493626 @default.
• W4286009750 hasAuthorship W4286009750A5064548129 @default.
• W4286009750 hasAuthorship W4286009750A5071068810 @default.
• W4286009750 hasBestOaLocation W42860097501 @default.
• W4286009750 hasConcept C110875604 @default.
• W4286009750 hasConcept C121684516 @default.
• W4286009750 hasConcept C136764020 @default.
• W4286009750 hasConcept C144133560 @default.
• W4286009750 hasConcept C158071213 @default.
• W4286009750 hasConcept C162853370 @default.
• W4286009750 hasConcept C17744445 @default.
• W4286009750 hasConcept C178601582 @default.
• W4286009750 hasConcept C191935318 @default.
• W4286009750 hasConcept C199539241 @default.
• W4286009750 hasConcept C2524010 @default.
• W4286009750 hasConcept C2780378061 @default.
• W4286009750 hasConcept C33923547 @default.
• W4286009750 hasConcept C41008148 @default.
• W4286009750 hasConcept C502989409 @default.
• W4286009750 hasConcept C90673727 @default.
• W4286009750 hasConcept C94625758 @default.
• W4286009750 hasConceptScore W4286009750C110875604 @default.
• W4286009750 hasConceptScore W4286009750C121684516 @default.
• W4286009750 hasConceptScore W4286009750C136764020 @default.
• W4286009750 hasConceptScore W4286009750C144133560 @default.
• W4286009750 hasConceptScore W4286009750C158071213 @default.
• W4286009750 hasConceptScore W4286009750C162853370 @default.
• W4286009750 hasConceptScore W4286009750C17744445 @default.
• W4286009750 hasConceptScore W4286009750C178601582 @default.
• W4286009750 hasConceptScore W4286009750C191935318 @default.
• W4286009750 hasConceptScore W4286009750C199539241 @default.
• W4286009750 hasConceptScore W4286009750C2524010 @default.
• W4286009750 hasConceptScore W4286009750C2780378061 @default.
• W4286009750 hasConceptScore W4286009750C33923547 @default.
• W4286009750 hasConceptScore W4286009750C41008148 @default.
• W4286009750 hasConceptScore W4286009750C502989409 @default.
• W4286009750 hasConceptScore W4286009750C90673727 @default.
• W4286009750 hasConceptScore W4286009750C94625758 @default.
• W4286009750 hasFunder F4320321376 @default.
• W4286009750 hasLocation W42860097501 @default.
• W4286009750 hasLocation W42860097502 @default.
• W4286009750 hasLocation W42860097503 @default.
• W4286009750 hasOpenAccess W4286009750 @default.
• W4286009750 hasPrimaryLocation W42860097501 @default.
• W4286009750 hasRelatedWork W1979439403 @default.
• W4286009750 hasRelatedWork W2094607796 @default.
• W4286009750 hasRelatedWork W2174438959 @default.
• W4286009750 hasRelatedWork W2350086902 @default.
• W4286009750 hasRelatedWork W2543545203 @default.
• W4286009750 hasRelatedWork W281246900 @default.
• W4286009750 hasRelatedWork W4206062546 @default.

• next