Abstract
City connectivity is an important measurement in characterizing human dynamics from regional to international scales. World City Network has been built based on companies' communication. The interactions between spatial and social dimensions of cities have both conceptual and practical significance. To further expand the studies of inter-city network in the big social data context, this research builds a network at the county level using digital footprints from Twitter users. Retrieving geotags from Twitter users, we identify the connection strength of each pair of counties based on the amounts of shared users who leave digital footprints on both counties. Using the shared user amount as the weighted link and each county as the node, we build a county-to-county user flow network. Various network structures have been detected at the state level. In addition, by creating a direct flow chain, we can identify influential counties and its hinterland. This network demonstrates how human mobility operate across various spatial settings and distances. Results of this study can be used in transportation planning, regional planning and metropolitan management.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility, PredictGIS 2018 |
| Editors | Akihito Sudo, Lau Hoong Chin, Takahiro Yabe, Xuan Song, Yoshihide Sekimoto |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 25-31 |
| Number of pages | 7 |
| ISBN (Electronic) | 9781450360425 |
| DOIs | |
| State | Published - Nov 6 2018 |
| Event | 2nd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility, PredictGIS 2018 - Seattle, United States Duration: Nov 6 2018 → … |
Publication series
| Name | Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility, PredictGIS 2018 |
|---|
Conference
| Conference | 2nd ACM SIGSPATIAL International Workshop on Prediction of Human Mobility, PredictGIS 2018 |
|---|---|
| Country/Territory | United States |
| City | Seattle |
| Period | 11/6/18 → … |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Computer Science Applications
- Control and Systems Engineering
- Transportation
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