Latest Articles for Sentiment Analysis

Analyzing how generative AI is reported in global news from 2018 to 2023.

Exploring how gestures and expressions enhance our understanding of spoken language.

Examining the impact of sentiment analysis on Bengali identities and biases.

Automated tools often misjudge African American English, leading to unfair treatment online.

A study on reducing noise in Bangla texts for better sentiment analysis.

Exploring how sentiment analysis connects food, health, and personal well-being.

Leveraging language models to identify false information in news articles.

Discover how language models are reshaping financial analysis and decision-making.

Combining models improves sentiment analysis accuracy significantly.

New method improves sentence embeddings using multiple prompts for better accuracy.

Exploring how AraPoemBERT enhances Arabic poetry analysis.

A chatbot helps elderly users feel connected and less lonely through engaging conversations.

A new model improves how we analyze public sentiment from tweets.

Combining stress index and news sentiment for smarter investment decisions.

Personal Name Compounds reflect public sentiment toward prominent figures in Germany.

This study focuses on refining smaller language models for South Slavic languages.

A study on how Slovene media depicts Syrian and Ukrainian migrants.

A new approach using RGCNs improves sentiment classification from text data.

Researchers tackle spelling variations to improve NLP performance in Nigerian Pidgin.

A new dataset combines user reviews and images to study hotel sentiments in Vietnam.

Analyzing public views on wildlife is key for conservation efforts worldwide.

A new method uses machine learning to analyze online reviews effectively.

SaudiBERT enhances analysis of the Saudi dialect in digital communications.

A study on analyzing viewer reactions to short video content.

This study examines how context shapes emotional expression in online discussions about depression.

This model improves sentiment analysis accuracy and efficiency for online comments.

Study assesses seven LLMs on sentiment analysis in mixed-language WhatsApp chats.

This study examines how AI predicts sentiment using confusing features.

This article analyzes the performance of fine-tuned models versus generative AI in text classification tasks.

New methods improve speed and accuracy in sentiment analysis.

Names from different countries impact how classifiers interpret social media content.

Integrating graph knowledge improves performance in low-resource languages using language adapters.

A novel method combining news insights with stock price forecasts.

A new method improves emotion recognition even with incomplete data.

Introducing DictaLM 2.0 and DictaLM 2.0-Instruct for improved Hebrew language processing.

A model analyzes user interactions and sentiments in climate change discussions.

This study examines how weather affects emotions expressed on Twitter in the UK.

Study analyzes text classification methods for subjective and objective content in five languages.

A new approach helps models adjust to unpredictable data environments effectively.

This study examines how SBP's tone affects stock market performance in Pakistan.