Latest Articles for Sentiment Analysis

Study reveals improved sentiment analysis through local LLMs and majority voting.

A framework for improving AI sentiment analysis in healthcare conversations.

Examining biases in sentiment analysis models used in political research.

Discover how deep learning aids economists in analyzing complex data.

Exploring how transformers analyze sentiments in text, such as movie reviews.

This article examines the impact of training methods on multilingual language model performance.

Examining how language models analyze shifts in word meanings.

New methods for personalizing AI language models are essential for user diversity.

A new dataset reveals public political sentiments during elections in Bangladesh.

This article explores how LLMs enhance sentiment analysis for predicting currency prices.

This study examines LLM performance on lengthy texts and offers improvement strategies.

The study highlights challenges LLMs face with low-resource languages.

A new method enhances interaction among language models, improving task efficiency.

Learn how businesses can analyze social media to better understand customer interests.

A new tool aids in analyzing deletion discussions on Wikipedia.

A novel approach merges multitask learning and generative adversarial networks for NLP tasks.

BnSentMix provides a comprehensive resource for Bengali-English sentiment analysis.

A new approach improves sentiment analysis using market-based datasets.

This study reveals insights into public attitudes toward vaccination using social media data.

A study on sentiment analysis and the effectiveness of language models.

Examining Sinophobic sentiments and their growth during the pandemic.

InkubaLM aims to improve language processing for underrepresented African languages.

This study reviews Google Translate's effectiveness in translating Mandarin texts to English.

Analyzing how positive news affects company stock prices and their networks.

Exploring how AI handles missing information in multimodal learning.

Introducing LowREm, a tool for enhancing word embeddings in underrepresented languages.

Examining how developer feelings affect the quality of machine learning code.

Learn how merging AI models can improve processing speed and reduce complexity.

This guide reviews methods for predicting stock prices in India using various models.

This study enhances sentiment analysis through zero-shot methods across multiple languages.

Researchers use language models to assist in sentiment analysis for code-mixed text.

Researchers develop models to detect bias in political news.

FASSILA dataset aims to combat misinformation and analyze sentiments in Algerian dialect.

A look into using technology to combat cyberbullying on social media.

Introducing a new benchmark for testing financial language models in English and Chinese.

Discover how TDA enhances understanding in language analysis.

Examining the limitations of LLMs in analyzing sentiments from text and images.

MOSABench enhances multi-object sentiment analysis in AI technology.

New benchmark boosts evaluation of Nepali language models with expanded tasks.

Discover how new methods improve sentiment analysis efficiency and accuracy.