Recent advances in artificial intelligence have opened up new possibilities for text analysis through generative models such as ChatGPT or Gemini. These models can not only synthesize and summarize textual data, but also explore themes, detect sentiment, and interpret trends in a more fluid and flexible way.
In this section, we explore how these tools can be used for text analysis.
TexteSense TexteSense is a custom GPT that I designed for French-speaking users who want to carry out in-depth text analysis. This model is optimized for tasks such as sentiment analysis and topic modeling, and it can process texts in both French and English while always returning the output in French. Features Sentiment analysis: identifies the emotional tone of a text (positive, negative, or neutral) and provides detailed explanations. Topic modeling: extracts the main themes from a text to provide a quick and relevant overview. Multilingual support: English texts are translated into French before analysis to keep the results consistent. Multiple document support: accepts text pasted directly into the chat box or uploaded files, whether single or multiple. Access link