Abstract: The present disclosure relates to methods for analyzing social media data using various techniques, including classifying at least one contagious phenomenon propagating on a network, providing stance detection based on the social media data, clustering the social media data, and/or generating and analyzing knowledge graph embeddings using the social media data.

Abstract: Computer based techniques for clustering social media data based on the semantic content can include: obtaining social media data representing a plurality of social media posts from a plurality of social media platforms; processing each particular social media post of the plurality of social media posts utilizing a machine learning model to generate a vector, representative of the content, corresponding to an embedding of the particular social media post in an embedding space; generating, based on the embedding space, a plurality of clusters utilizing a clustering algorithm, each cluster including social media posts that have related content; generating, for at least one cluster of the plurality of clusters, a visualization representative of the related content of the social media posts in the at least one cluster; and outputting the visualization to a user computing device.

Abstract: The present disclosure relates to methods for analyzing social media data using various techniques, including classifying at least one contagious phenomenon propagating on a network, providing stance detection based on the social media data, clustering the social media data, and/or generating and analyzing knowledge graph embeddings using the social media data.