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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 176–200 of 630 papers

TitleStatusHype
EmotiKLUE at IEST 2018: Topic-Informed Classification of Implicit EmotionsCode0
Arabizi sentiment analysis based on transliteration and automatic corpus annotation—0
Sentiment Classification towards Question-Answering with Hierarchical Matching Network—0
Attentive Gated Lexicon Reader with Contrastive Contextual Co-Attention for Sentiment Classification—0
Architecture of Text Mining Application in Analyzing Public Sentiments of West Java Governor Election using Naive Bayes Classification—0
Argumentation Mining: Exploiting Multiple Sources and Background Knowledge—0
Multi-label Classification of User Reactions in Online News—0
Stance Detection with Hierarchical Attention Network—0
YouTube AV 50K: An Annotated Corpus for Comments in Autonomous VehiclesCode0
Multimodal Named Entity Disambiguation for Noisy Social Media Posts—0
Disambiguating False-Alarm Hashtag Usages in Tweets for Irony Detection—0
Framework for Opinion Mining Approach to Augment Education System Performance—0
Addition of Code Mixed Features to Enhance the Sentiment Prediction of Song Lyrics—0
A Fine-grained Large-scale Analysis of Coreference Projection—0
SSN MLRG1 at SemEval-2018 Task 3: Irony Detection in English Tweets Using MultiLayer Perceptron—0
HashCount at SemEval-2018 Task 3: Concatenative Featurization of Tweet and Hashtags for Irony Detection—0
TAJJEB at SemEval-2018 Task 2: Traditional Approaches Just Do the Job with Emoji Prediction—0
Irony Detector at SemEval-2018 Task 3: Irony Detection in English Tweets using Word Graph—0
CENNLP at SemEval-2018 Task 2: Enhanced Distributed Representation of Text using Target Classes for Emoji Prediction Representation—0
EMA at SemEval-2018 Task 1: Emotion Mining for Arabic—0
CENTEMENT at SemEval-2018 Task 1: Classification of Tweets using Multiple Thresholds with Self-correction and Weighted Conditional Probabilities—0
Is Something Better than Nothing? Automatically Predicting Stance-based Arguments Using Deep Learning and Small Labelled Dataset—0
Nested Named Entity Recognition Revisited—0
A Corpus of English-Hindi Code-Mixed Tweets for Sarcasm DetectionCode0
Analysis of Inferences in Chinese for Opinion Mining—0
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