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New article on estimating transport demand from Twitter data

Yuan Liao, Sonia Yeh, and Jorge Gil have published a new article in the journal Transportation, looking at the feasibility of using geolocations of social media data (Twitter) for travel demand estimation. They have examined the effects of data sparsity, spatial scale, sampling methods, and sample size on the resulting Origin Destination matrices, when compared to "ground truth" data from the Swedish travel survey and the Sampers transport model.

Find out more here: https://link.springer.com/article/10.1007/s11116-021-10171-x


Similarity between matrices, a SpSSIM and b KL divergence, as a function of the number of geotagged tweets.

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