Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 39 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 12 tok/s Pro
GPT-5 High 18 tok/s Pro
GPT-4o 91 tok/s Pro
Kimi K2 191 tok/s Pro
GPT OSS 120B 456 tok/s Pro
Claude Sonnet 4 34 tok/s Pro
2000 character limit reached

Research on the Application of Deep Learning-based BERT Model in Sentiment Analysis (2403.08217v1)

Published 13 Mar 2024 in cs.CL and cs.LG

Abstract: This paper explores the application of deep learning techniques, particularly focusing on BERT models, in sentiment analysis. It begins by introducing the fundamental concept of sentiment analysis and how deep learning methods are utilized in this domain. Subsequently, it delves into the architecture and characteristics of BERT models. Through detailed explanation, it elucidates the application effects and optimization strategies of BERT models in sentiment analysis, supported by experimental validation. The experimental findings indicate that BERT models exhibit robust performance in sentiment analysis tasks, with notable enhancements post fine-tuning. Lastly, the paper concludes by summarizing the potential applications of BERT models in sentiment analysis and suggests directions for future research and practical implementations.

Citations (13)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.