ESTEEM: A Novel Framework for Qualitatively Evaluating and Visualizing Spatiotemporal Embeddings in Social Media

Analyzing and visualizing large amounts of social media communications and contrasting short-term conversation changes over time and geolocations is extremely important for commercial and government applications. Earlier approaches for largescale text stream summarization used dynamic topic models and trending words. Instead, we rely on text embeddingslow-dimensional word representations in a continuous vector space where similar words are embedded nearby each other.