Explainable Artificial Intelligence (XAI) means making Artificial Intelligence systems (AI) more transparent, such that their decisions can be understood.
Here, deep learning is used to classify a chosen text as positive, negative or neutral, on the basis of it's content. After the classification, a method called LRP (Layer-wise Relevance Propagation) is applied to explain why the deep learning system came to it's decision, making it an XAI system instead of a black-box system.
The LRP implementation is based on the following papers:
https://doi.org/10.1371/journal.pone.0130140
https://doi.org/10.18653/v1/W17-5221
And the functions are based on implementations from Layer-wise Relevance Propagation (LRP) for LSTMs: