Social Media have increasingly provided data about the movement of people in cities making them useful in understanding the daily life of people in different geographies.Particularly useful for travel analysis is when...Social Media have increasingly provided data about the movement of people in cities making them useful in understanding the daily life of people in different geographies.Particularly useful for travel analysis is when Social Media users allow(voluntarily or not)tracing their movement using geotagged information of their communication with these online platforms.In this paper we use geotagged tweets from 10 cities in the European Union and United States of America to extract spatiotemporal patterns,study differences and commonalities among these cities,and explore the nature of user location recurrence.The analysis here shows the distinction between residents and tourists is fundamental for the development of city-wide models.Identification of repeated rates of location(recurrence)can be used to define activity spaces.Differences and similarities across different geographies emerge from this analysis in terms of local distributions but also in terms of the worldwide reach among the cities explored here.The comparison of the temporal signature between geotagged and non-geotagged tweets also shows similar temporal distributions that capture in essence city rhythms of tweets and activity spaces.展开更多
基金partially funded by the DAAD Project(No.57474280)Verkehr-SuTra:Technologies for Sustainable Transportation,within the Programme:A New Passage to India—Deutsch-Indische Hochschulkooperationen ab 2019the German Federal Ministry of Education and Research,Bundesministerium für Bildung und Forschung(BMBF),project FuturTrans:Indo-German Collaborative Research Center on Intelligent Transportation Systemsby the European Union's Horizon 2020 research and innovation programme under grant agreement No.815069(project MOMENTUM(Modelling Emerging Transport Solutions for Urban Mobility)).
文摘Social Media have increasingly provided data about the movement of people in cities making them useful in understanding the daily life of people in different geographies.Particularly useful for travel analysis is when Social Media users allow(voluntarily or not)tracing their movement using geotagged information of their communication with these online platforms.In this paper we use geotagged tweets from 10 cities in the European Union and United States of America to extract spatiotemporal patterns,study differences and commonalities among these cities,and explore the nature of user location recurrence.The analysis here shows the distinction between residents and tourists is fundamental for the development of city-wide models.Identification of repeated rates of location(recurrence)can be used to define activity spaces.Differences and similarities across different geographies emerge from this analysis in terms of local distributions but also in terms of the worldwide reach among the cities explored here.The comparison of the temporal signature between geotagged and non-geotagged tweets also shows similar temporal distributions that capture in essence city rhythms of tweets and activity spaces.
