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Opinion Mining

Identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral (Source: Oxford Languages)

Image Source: Deep learning for sentiment analysis: A survey

Papers

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Showing 226–250 of 630 papers

TitleStatusHype
MTNA: A Neural Multi-task Model for Aspect Category Classification and Aspect Term Extraction On Restaurant Reviews—0
Text Sentiment Analysis based on Fusion of Structural Information and Serialization Information—0
TOTEMSS: Topic-based, Temporal Sentiment Summarisation for Twitter—0
Leveraging Auxiliary Tasks for Document-Level Cross-Domain Sentiment Classification—0
Review highlights: opinion mining on reviews: a hybrid model for rule selection in aspect extractionCode1
NoReC: The Norwegian Review CorpusCode0
A study on irony within the context of 7x1-PT corpus—0
Investigating Opinion Mining through Language Varieties: a Case Study of Brazilian and European Portuguese tweets—0
Expert Opinion Extraction from a Biomedical Database—0
Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy—0
Opinion Mining in Social Networks versus Electoral Polls—0
Annotating Italian Social Media Texts in Universal Dependencies—0
Natural Language Processing in Political Campaigns—0
oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain—0
Mining Argumentative Structure from Natural Language text using Automatically Generated Premise-Conclusion Topic Models—0
Unsupervised Detection of Argumentative Units though Topic Modeling Techniques—0
Toward Stance Classification Based on Claim Microstructures—0
Capturing User and Product Information for Document Level Sentiment Analysis with Deep Memory Network—0
Sentiment Lexicon Construction with Representation Learning Based on Hierarchical Sentiment SupervisionCode0
Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNNCode0
TwiSe at SemEval-2017 Task 4: Five-point Twitter Sentiment Classification and Quantification—0
ELiRF-UPV at SemEval-2017 Task 4: Sentiment Analysis using Deep Learning—0
OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields—0
NRU-HSE at SemEval-2017 Task 4: Tweet Quantification Using Deep Learning Architecture—0
Deep Learning Models For Multiword Expression Identification—0
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