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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
Annotating Attribution Relations in Arabic—0
SenSALDO: Creating a Sentiment Lexicon for Swedish—0
`Aye' or `No'? Speech-level Sentiment Analysis of Hansard UK Parliamentary Debate Transcripts—0
Scalable Visualisation of Sentiment and Stance—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
Lingmotif-lex: a Wide-coverage, State-of-the-art Lexicon for Sentiment Analysis—0
A Japanese Corpus for Analyzing Customer Loyalty Information—0
BlogSet-BR: A Brazilian Portuguese Blog Corpus—0
A Multi- versus a Single-classifier Approach for the Identification of Modality in the Portuguese Language—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
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
IJCNLP-2017 Task 3: Review Opinion Diversification (RevOpiD-2017)—0
CIAL at IJCNLP-2017 Task 2: An Ensemble Valence-Arousal Analysis System for Chinese Words and Phrases—0
THU\_NGN at IJCNLP-2017 Task 2: Dimensional Sentiment Analysis for Chinese Phrases with Deep LSTM—0
Visual and Textual Sentiment Analysis Using Deep Fusion Convolutional Neural Networks—0
Multi-Channel Lexicon Integrated CNN-BiLSTM Models for Sentiment Analysis—0
Extracting and Understanding Contrastive Opinion through Topic Relevant Sentences—0
Modelling Representation Noise in Emotion Analysis using Gaussian Processes—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
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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