Subjectivity Analysis
A related task to sentiment analysis is the subjectivity analysis with the goal of labeling an opinion as either subjective or objective.
State-of-the-art leaderboards
| Trend | Dataset | Best Method | Paper title | Paper | Code | Compare |
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Greatest papers with code
Universal Sentence Encoder
• facebookresearch/InferSent
• 
For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.
SOTA for Text Classification on TREC-6
SEMANTIC TEXTUAL SIMILARITY SENTENCE EMBEDDINGS SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS TEXT CLASSIFICATION TRANSFER LEARNING WORD EMBEDDINGS
Learning to Generate Reviews and Discovering Sentiment
ICLR 2018
• openai/generating-reviews-discovering-sentiment
•
We explore the properties of byte-level recurrent language models.
#3 best model for
Subjectivity Analysis
on SUBJ
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms
Many deep learning architectures have been proposed to model the compositionality in text sequences, requiring a substantial number of parameters and expensive computations.
#4 best model for
Text Classification
on Yahoo! Answers
DOCUMENT CLASSIFICATION NAMED ENTITY RECOGNITION (NER) SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS WORD EMBEDDINGS
Investigating Capsule Networks with Dynamic Routing for Text Classification
EMNLP 2018
• andyweizhao/capsule_text_classification
• 
In this study, we explore capsule networks with dynamic routing for text classification.
#3 best model for
Sentiment Analysis
on MR
MULTI-LABEL TEXT CLASSIFICATION SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS TEXT CLASSIFICATION
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
We present EDA: easy data augmentation techniques for boosting performance on text classification tasks.
SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS TEXT CLASSIFICATION
All-but-the-Top: Simple and Effective Postprocessing for Word Representations
The postprocessing is empirically validated on a variety of lexical-level intrinsic tasks (word similarity, concept categorization, word analogy) and sentence-level tasks (semantic textural similarity and { text classification}) on multiple datasets and with a variety of representation methods and hyperparameter choices in multiple languages; in each case, the processed representations are consistently better than the original ones.
#6 best model for
Sentiment Analysis
on MR
SENTIMENT ANALYSIS SUBJECTIVITY ANALYSIS TEXT CLASSIFICATION
MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos
• soujanyaporia/multimodal-sentiment-analysis
This paper introduces to the scientific community the first opinion-level annotated corpus of sentiment and subjectivity analysis in online videos called Multimodal Opinion-level Sentiment Intensity dataset (MOSI).
Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning
• pliang279/MFN
•
In this paper, we propose the Gated Multimodal Embedding LSTM with Temporal Attention (GME-LSTM(A)) model that is composed of 2 modules.
Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web
WS 2018 • DeFacto/WebCredibility
To this aim, an important step to detect fake-news is to have access to a credibility score for a given information source.
The Evolution of Sentiment Analysis - A Review of Research Topics, Venues, and Top Cited Papers
Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area.