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Sentiment Analysis

1592 directly classified papers

Papers per year

Papers

Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised EMNLP 2018
Deep learning for language understanding of mental health concepts derived from Cognitive Behavioural Therapy EMNLP 2018
On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis EMNLP 2018
Joint Learning for Targeted Sentiment Analysis EMNLP 2018
Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study EMNLP 2018
Syntactical Analysis of the Weaknesses of Sentiment Analyzers EMNLP 2018
SiTAKA at SemEval-2017 Task 4: Sentiment Analysis in Twitter Based on a Rich Set of Features SEMEVAL 2017
A Cognition Based Attention Model for Sentiment Analysis EMNLP 2017
Tweester at SemEval-2017 Task 4: Fusion of Semantic-Affective and pairwise classification models for sentiment analysis in Twitter SEMEVAL 2017
OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random Fields SEMEVAL 2017
TWINA at SemEval-2017 Task 4: Twitter Sentiment Analysis with Ensemble Gradient Boost Tree Classifier SEMEVAL 2017
SentiME++ at SemEval-2017 Task 4: Stacking State-of-the-Art Classifiers to Enhance Sentiment Classification SEMEVAL 2017
UW-FinSent at SemEval-2017 Task 5: Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation SEMEVAL 2017
TakeLab at SemEval-2017 Task 5: Linear aggregation of word embeddings for fine-grained sentiment analysis of financial news SEMEVAL 2017
Sentiment Intensity Ranking among Adjectives Using Sentiment Bearing Word Embeddings EMNLP 2017
SentiHeros at SemEval-2017 Task 5: An application of Sentiment Analysis on Financial Tweets SEMEVAL 2017
INF-UFRGS at SemEval-2017 Task 5: A Supervised Identification of Sentiment Score in Tweets and Headlines SEMEVAL 2017
Computational Sarcasm EMNLP 2017
Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm EMNLP 2017
ConStance: Modeling Annotation Contexts to Improve Stance Classification EMNLP 2017
Sentiment Lexicon Expansion Based on Neural PU Learning, Double Dictionary Lookup, and Polarity Association EMNLP 2017
Refining Word Embeddings for Sentiment Analysis EMNLP 2017
Capturing User and Product Information for Document Level Sentiment Analysis with Deep Memory Network EMNLP 2017
IBA-Sys at SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News SEMEVAL 2017
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models ACL 2017