In our paper "Sentiment analysis and image classification in social networks with zero-shot deep learning: applications in tourism", we propose a methodology for the detection of tourist places of interest through the combined use of images and text from social networks. For that purpose, we will be assisted by pre-trained neural networks for image classification and sentiment analysis. The result is frequency information of types of places according to a tourism-specific taxonomy combined with user sentiment indicators, which is potentially relevant information for tourism analysts.

In this github repository, you will find the code and datasets that we used in our work.