Consistency of Social Sensing Signatures Across Major US Cities

Aiman Soliman; Kiumars Soltani; Anand Padmanabhan; Shaowen Wang

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arXiv · 1609.04373

Consistency of Social Sensing Signatures Across Major US Cities

Aiman Soliman·Kiumars Soltani·Anand Padmanabhan·Shaowen Wang

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Abstract

Previous studies have shown that Twitter users have biases to tweet from certain locations, locational bias, and during certain hours, temporal bias. We used three years of geolocated Twitter Data to quantify these biases and test our central hypothesis that Twitter users biases are consistent across US cities. Our results suggest that temporal and locational bias of Twitter users are inconsistent between three US metropolitan cities. We derive conclusions about the role of the complexity of the underlying data producing process on its consistency and argue for the potential research avenue for Geospatial Data Science to test and quantify these inconsistencies in the class of organically evolved Big Data.

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Aiman Soliman, Kiumars Soltani, Anand Padmanabhan, Shaowen Wang. 2016-09-14. Consistency of Social Sensing Signatures Across Major US Cities. https://arxiv.org/abs/1609.04373

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