Twitter Sentiment Analysis
13 papers with code • 0 benchmarks • 6 datasets
Twitter sentiment analysis is the task of performing sentiment analysis on tweets from Twitter.
Benchmarks
These leaderboards are used to track progress in Twitter Sentiment Analysis
Datasets
Twitter Sentiment Analysis
RETWEET
SentimentArcs: Sentiment Reference Corpus for Novels
Latest papers
HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis
ahmadmwali/semeval-afrisenti
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We present the findings of SemEval-2023 Task 12, a shared task on sentiment analysis for low-resource African languages using Twitter dataset.
Cryptocurrency Price Prediction using Twitter Sentiment Analysis
Aaron-Paul/Bitcoin-Price-Twitter-Sentiment-Analysis
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In this study, we develop an end-to-end model that can forecast the sentiment of a set of tweets (using a Bidirectional Encoder Representations from Transformers - based Neural Network Model) and forecast the price of Bitcoin (using Gated Recurrent Unit) using the predicted sentiment and other metrics like historical cryptocurrency price data, tweet volume, a user's following, and whether or not a user is verified.
AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages
These include 75 languages with at least one million speakers each.
n-stage Latent Dirichlet Allocation: A Novel Approach for LDA
In this article, the proposed n-stage LDA method, which can enable the LDA method to be used more effectively, is explained in detail.
Twitter Sentiment Analysis
Vedurumudi-Priyanka/Twitter-Sentiment-Analysis
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- 2021
In this report, address the problem of sentiment classification on the Twitter dataset.
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.
GRUBERT: A GRU-Based Method to Fuse BERT Hidden Layers for Twitter Sentiment Analysis
zuowenwang0000/grubert-a-gru-based-method-to-fuse-bert-hidden-layers
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Asian Chapter of the Association for Computational Linguistics 2020
In this work, we introduce a GRU-based architecture called GRUBERT that learns to map the different BERT hidden layers to fused embeddings with the aim of achieving high accuracy on the Twitter sentiment analysis task.
Offensive Language Analysis using Deep Learning Architecture
RyanOngAI/semeval-2019-task6
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Once we are happy with the quality of our input data, we proceed to choosing the optimal deep learning architecture for this task.
Comparative Studies of Detecting Abusive Language on Twitter
However, this dataset has not been comprehensively studied to its potential.
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.
