<p>This study compared five chatbots for sentiment analysis: ChatGPT, Google Gemini, Bing, Claude, and LLaMA, evaluating their performance in various dimensions, such as accuracy analysis, capacity for understanding context, personalization, security, and privacy, with the purpose of recognizing the strengths and limitations of each chatbot in particular situations. Google Gemini stood out for its high accuracy in sentiment analysis and contextual understanding, with Claude standing out for security and bias management. ChatGPT stood out for its customization and support in multiple languages. Bing demonstrated strength in integration and speed, although with lower accuracy in the study of emotions. LLaMA distinguished itself for its effectiveness in research contexts and mobile uses, although it showed an interior accuracy. Claude excels in terms of data security and bias management, whereas ChatGPT excels in personalization. Bing stands out for its integration and speed, while LLaMA is more effective in research contexts. In neutral emotion management, Google Gemini stands out. In language diversity, Google Gemini excels with support for over 100 different languages, while ChatGPT effectively adapts to several multilingual contexts. Research is recommended on neutral emotion management, multimodal capacity, and adaptation to diverse cultural and linguistic contexts.</p>

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Comparative study of chatbots for sentiment analysis

  • Brayan Salomon Ortiz Quispe,
  • Andy Misael Tafur Gomez,
  • Emigdio Antonio Alfaro Paredes

摘要

This study compared five chatbots for sentiment analysis: ChatGPT, Google Gemini, Bing, Claude, and LLaMA, evaluating their performance in various dimensions, such as accuracy analysis, capacity for understanding context, personalization, security, and privacy, with the purpose of recognizing the strengths and limitations of each chatbot in particular situations. Google Gemini stood out for its high accuracy in sentiment analysis and contextual understanding, with Claude standing out for security and bias management. ChatGPT stood out for its customization and support in multiple languages. Bing demonstrated strength in integration and speed, although with lower accuracy in the study of emotions. LLaMA distinguished itself for its effectiveness in research contexts and mobile uses, although it showed an interior accuracy. Claude excels in terms of data security and bias management, whereas ChatGPT excels in personalization. Bing stands out for its integration and speed, while LLaMA is more effective in research contexts. In neutral emotion management, Google Gemini stands out. In language diversity, Google Gemini excels with support for over 100 different languages, while ChatGPT effectively adapts to several multilingual contexts. Research is recommended on neutral emotion management, multimodal capacity, and adaptation to diverse cultural and linguistic contexts.