Crowd-based urban characterization: extracting crowd behavioral patterns in urban areas from Twitter

By Shoko Wakamiya, Ryong Lee, Kazutoshi Sumiya. 2011

57 citations recorded by the source corpus.

Subfields: Geography, Planning and Development, Ocean Engineering, Transportation

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Geography, Planning and Development

1. Jürgen Pfeffer

In Transportation

1. Kathleen M. Carley
2. Chun How Tan
3. Kenneth Joseph
4. Huan Liu
5. Bryan Perozzi
6. Charu C. Aggarwal

Citations in the corpus

• Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose (2013, background): “In (Wakamiya, Lee, and Sumiya 2011) the authors try to classify towns based upon the content of the geotagged tweets that originate from within the town.”
• Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition (2012, background): “This section presents previous work that has focused on spatiotemporal and event related social media analysis.”
• Beyond "local", "categories" and "friends": clustering foursquare users with latent "topics" (2012, background): “Data drawn from mobile devices on the whereabouts of their users has led to an influx of interesting findings in explaining patterns of human mobility [6, 17, 5], predicting friendship on social networking sites based on location data [23, 20], and better understanding different aspects of cities, b”