Day: 21 October 2015
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Exploring spatiotemporal and semantic clusters of Twitter data using unsupervised neural networks
The investigation of human activity patterns from location-based social networks like Twitter is a promising example of how to infer relationships and latent information for the characterization of urban structures. While there is a growing research body performing spatial analysis on social media data, the high dimensionality, complexity and granularity of social media information still…