This document discusses multimodal sentiment analysis using TensorFlow. It introduces early work on sentiment analysis and the need to analyze images on social media. A Tumblr dataset is described containing posts with images and text for analyzing sentiment. The neural network architecture combines visual analysis and natural language processing in a multimodal neural network called DeepSentiment. Results show the network can be trained with TensorFlow Dataset and evaluate sentiment, identify words associated with emotions, and cluster emotions in a circumplex model.

1. Multimodal Sentiment
Analysis with TensorFlow

2. 1. Introduction

3. Early work on Sentiment Analysis
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4. What about images on social media?
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5. 2. Multimodal dataset

6. Tumblr dataset
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7. Example of a Tumblr post
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8. Dataset description
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9. 3. Neural network architecture

10. Visual analysis
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11. Natural language processing
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12. DeepSentiment: a multimodal neural network (1)
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13. DeepSentiment: a multimodal neural network (2)
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14. Training with TensorFlow Dataset
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15. 4. Results

16. Evaluation
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17. Top words associated with each emotion
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18. Circumplex model of emotions (1)
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19. Circumplex model of emotions (2)
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20. Hierarchical clustering of emotions
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21. Thank you!

22. References
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