Matches in SemOpenAlex for { <https://semopenalex.org/work/W2081320655> ?p ?o ?g. }
Showing items 1 to 54 of
54
with 100 items per page.
- W2081320655 abstract "In this paper,we propose a probabilistic modeling framework,called Author-Topic-Sentiment Mixture(ATSM) model,which based on Latent Dirichlet Allocation (LDA) to include authorship information and sentiments information.The proposed model can reveal the sentimenttopic and author’s sentiment.Each author associated with a distribution of the sentiment-topics,and each sentiment-topic is associated with a distribution of the words.Unlike other approaches to sentiment classification which often require labeled corpora or sentiment seed words,the proposed ATSM model is unsupervised .We show sentiment-topics recovered and the author’s distribution of sentiment-topic by the ATSM model.We compare the performance with two other generative models for documents :LDA and ATM,and illustrative a possible application of the ATSM. Keywords-LDA; author-topic; ATSM; Sentiment analysis; probabilistic topic models;Gibbs sampling; LDA" @default.
- W2081320655 created "2016-06-24" @default.
- W2081320655 creator A5008082945 @default.
- W2081320655 creator A5020902076 @default.
- W2081320655 date "2014-01-01" @default.
- W2081320655 modified "2023-09-23" @default.
- W2081320655 title "Author-Topic-Sentiment Mixture(ATSM) model for Author's Sentiment Analysis" @default.
- W2081320655 cites W1880262756 @default.
- W2081320655 cites W2108420397 @default.
- W2081320655 cites W2110591510 @default.
- W2081320655 cites W2116330964 @default.
- W2081320655 cites W2129294185 @default.
- W2081320655 cites W2140124448 @default.
- W2081320655 cites W2170913717 @default.
- W2081320655 cites W2951278869 @default.
- W2081320655 doi "https://doi.org/10.2991/csss-14.2014.20" @default.
- W2081320655 hasPublicationYear "2014" @default.
- W2081320655 type Work @default.
- W2081320655 sameAs 2081320655 @default.
- W2081320655 citedByCount "0" @default.
- W2081320655 crossrefType "proceedings-article" @default.
- W2081320655 hasAuthorship W2081320655A5008082945 @default.
- W2081320655 hasAuthorship W2081320655A5020902076 @default.
- W2081320655 hasBestOaLocation W20813206551 @default.
- W2081320655 hasConcept C154945302 @default.
- W2081320655 hasConcept C204321447 @default.
- W2081320655 hasConcept C23123220 @default.
- W2081320655 hasConcept C2522767166 @default.
- W2081320655 hasConcept C41008148 @default.
- W2081320655 hasConcept C66402592 @default.
- W2081320655 hasConceptScore W2081320655C154945302 @default.
- W2081320655 hasConceptScore W2081320655C204321447 @default.
- W2081320655 hasConceptScore W2081320655C23123220 @default.
- W2081320655 hasConceptScore W2081320655C2522767166 @default.
- W2081320655 hasConceptScore W2081320655C41008148 @default.
- W2081320655 hasConceptScore W2081320655C66402592 @default.
- W2081320655 hasLocation W20813206551 @default.
- W2081320655 hasLocation W20813206552 @default.
- W2081320655 hasOpenAccess W2081320655 @default.
- W2081320655 hasPrimaryLocation W20813206551 @default.
- W2081320655 hasRelatedWork W2024691726 @default.
- W2081320655 hasRelatedWork W2326619756 @default.
- W2081320655 hasRelatedWork W2376314740 @default.
- W2081320655 hasRelatedWork W2384888906 @default.
- W2081320655 hasRelatedWork W2901590103 @default.
- W2081320655 hasRelatedWork W2909085234 @default.
- W2081320655 hasRelatedWork W3015597294 @default.
- W2081320655 hasRelatedWork W3027466640 @default.
- W2081320655 hasRelatedWork W3107474891 @default.
- W2081320655 hasRelatedWork W4312833533 @default.
- W2081320655 isParatext "false" @default.
- W2081320655 isRetracted "false" @default.
- W2081320655 magId "2081320655" @default.
- W2081320655 workType "article" @default.