Multimodal Sentiment Analysis Dataset

Dataset Description:

• Images: The dataset includes high-quality images of various animals and objects, covering 100 distinct classes.
• Text Descriptions: Each image is accompanied by a textual description that provides context and details about the image.
• Sentiment Labels: The text descriptions are annotated with sentiment labels, indicating the emotional tone (positive, negative, or neutral) associated with the content.

Applications:

• Image Classification: Train models to classify images into one of the 100 predefined classes.
• Sentiment Analysis: Analyze the sentiment expressed in the text descriptions to determine the emotional tone.
• Image Captioning: Develop models that generate descriptive captions for images based on the provided text and sentiment information.

Use Cases:

• Enhance user experience in social media platforms by integrating sentiment analysis with image recognition.
• Improve content recommendation systems by understanding the emotional context of images and their descriptions.
• Develop advanced AI models that can interpret and respond to both visual and textual inputs in a cohesive manner.