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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 201–250 of 630 papers

TitleStatusHype
BlogSet-BR: A Brazilian Portuguese Blog Corpus—0
Annotating Attribution Relations in Arabic—0
`Aye' or `No'? Speech-level Sentiment Analysis of Hansard UK Parliamentary Debate Transcripts—0
SenSALDO: Creating a Sentiment Lexicon for Swedish—0
Lingmotif-lex: a Wide-coverage, State-of-the-art Lexicon for Sentiment Analysis—0
Analysis of Inferences in Chinese for Opinion Mining—0
Scalable Visualisation of Sentiment and Stance—0
A Multi- versus a Single-classifier Approach for the Identification of Modality in the Portuguese Language—0
Corpus Building and Evaluation of Aspect-based Opinion Summaries from Tweets in Spanish—0
Complex and Precise Movie and Book Annotations in French Language for Aspect Based Sentiment Analysis—0
A Deep Neural Network based Approach for Entity Extraction in Code-Mixed Indian Social Media Text—0
PoSTWITA-UD: an Italian Twitter Treebank in Universal Dependencies—0
A Japanese Corpus for Analyzing Customer Loyalty Information—0
Structured Output Learning with Abstention: Application to Accurate Opinion Prediction—0
Discovering Bayesian Market Views for Intelligent Asset AllocationCode0
Mining Public Opinion about Economic Issues: Twitter and the U.S. Presidential Election—0
SentiPers: A Sentiment Analysis Corpus for PersianCode0
Public Apologies in India - Semantics, Sentiment and Emotion—0
Comparative Opinion Mining: A Review—0
THU\_NGN at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases with Deep LSTM—0
CIAL at IJCNLP-2017 Task 2: An Ensemble Valence-Arousal Analysis System for Chinese Words and Phrases—0
IJCNLP-2017 Task 3: Review Opinion Diversification (RevOpiD-2017)—0
Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional Neural Networks—0
Extracting and Understanding Contrastive Opinion through Topic Relevant Sentences—0
Modelling Representation Noise in Emotion Analysis using Gaussian Processes—0
Leveraging Auxiliary Tasks for Document-Level Cross-Domain Sentiment Classification—0
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
Multi-Channel Lexicon Integrated CNN-BiLSTM Models for Sentiment Analysis—0
NoReC: The Norwegian Review CorpusCode0
Investigating Opinion Mining through Language Varieties: a Case Study of Brazilian and European Portuguese tweets—0
A study on irony within the context of 7x1-PT corpus—0
Expert Opinion Extraction from a Biomedical Database—0
Annotating Italian Social Media Texts in Universal Dependencies—0
Natural Language Processing in Political Campaigns—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
Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy—0
Sentiment Lexicon Construction with Representation Learning Based on Hierarchical Sentiment SupervisionCode0
oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain—0
Opinion Mining in Social Networks versus Electoral Polls—0
Capturing User and Product Information for Document Level Sentiment Analysis with Deep Memory Network—0
Toward Stance Classification Based on Claim Microstructures—0
Mining fine-grained opinions on closed captions of YouTube videos with an attention-RNNCode0
SVNIT @ SemEval 2017 Task-6: Learning a Sense of Humor Using Supervised Approach—0
ELiRF-UPV at SemEval-2017 Task 4: Sentiment Analysis using Deep Learning—0
OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based Model—0
Deep Learning Models For Multiword Expression Identification—0
CrystalNest at SemEval-2017 Task 4: Using Sarcasm Detection for Enhancing Sentiment Classification and Quantification—0
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