Twitter Sentiment Analysis Edit Task
Natural Language Processing • Sentiment Analysis
About
Twitter sentiment analysis is the task of performing sentiment analysis on tweets from Twitter.
Benchmarks
Subtasks
Datasets
Greatest papers with code
Comparative Studies of Detecting Abusive Language on Twitter
In this paper, we conduct the first comparative study of various learning models on Hate and Abusive Speech on Twitter, and discuss the possibility of using additional features and context data for improvements.
ABUSIVE LANGUAGE HATE SPEECH DETECTION TWITTER SENTIMENT ANALYSIS
BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMs
In this paper we describe our attempt at producing a state-of-the-art Twitter sentiment classifier using Convolutional Neural Networks (CNNs) and Long Short Term Memory (LSTMs) networks.
Ranked #1 on
Sentiment Analysis
on SemEval 2017 Task 4-A
Decision Stream: Cultivating Deep Decision Trees
Various modifications of decision trees have been extensively used during the past years due to their high efficiency and interpretability.
FEATURE SELECTION IMAGE CLASSIFICATION TWITTER SENTIMENT ANALYSIS
NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis
The first space is a bag-of-words model and has a Linear SVM as base classifier.
Offensive Language Analysis using Deep Learning Architecture
• RyanOngAI/semeval-2019-task6
• 
Once we are happy with the quality of our input data, we proceed to choosing the optimal deep learning architecture for this task.
Multitask Learning for Fine-Grained Twitter Sentiment Analysis
Traditional sentiment analysis approaches tackle problems like ternary (3-category) and fine-grained (5-category) classification by learning the tasks separately.
How Will Your Tweet Be Received? Predicting the Sentiment Polarity of Tweet Replies
As a strong baseline, we propose a two-stage DL-based method: first, we create automatically labeled training data by applying a standard sentiment classifier to tweet replies and aggregating its predictions for each original tweet; our rationale is that individual errors made by the classifier are likely to cancel out in the aggregation step.
Ranked #1 on
Tweet-Reply Sentiment Analysis
on RETWEET