The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
The Livehoods Project: Utilizing Social Media to Understand the Dynamics of a City
Open accessAbstract
Studying the social dynamics of a city on a large scale has tra- ditionally been a challenging endeavor, requiring long hours of observation and interviews, usually resulting in only a par- tial depiction of reality. At the same time, the boundaries of municipal organizational units, such as neighborhoods and districts, are largely statically defined by the city government and do not always reflect the character of life in these ar- eas. To address both difficulties, we introduce a clustering model and research methodology for studying the structure and composition of a city based on the social media its res- idents generate. We use data from approximately 18 million check-ins collected from users of a location-based online so- cial network. The resulting clusters, which we call Livehoods, are representations of the dynamic urban areas that comprise the city. We take an interdisciplinary approach to validating these clusters, interviewing 27 residents of Pittsburgh, PA, to see how their perceptions of the city project onto our findings there. Our results provide strong support for the discovered clusters, showing how Livehoods reveal the distinctly charac- terized areas of the city and the forces that shape them.
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Exploring Millions of Footprints in Location Sharing Services
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Urban Computing: Concepts, Methodologies, and Applications
Zheng, Y., Capra, L., Wolfson, O., & Yang, H. (2014) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2629592 · Cited by 1,507
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
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Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763
Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data
Liu, Y., Sui, Z., Kang, C., & Gao, Y. (2014) · PLoS ONE · doi:10.1371/journal.pone.0086026 · Cited by 393
Exploiting Geographical Neighborhood Characteristics for Location Recommendation
Liu, Y., Wei, W., Sun, A., & Miao, C. (2014) · Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management · doi:10.1145/2661829.2662002 · Cited by 345
Metadata
- Authors
- Cranshaw, J., Schwartz, R., Hong, J., & Sadeh, N.
- Venue
- Proceedings of the International AAAI Conference on Web and Social Media
- Published
- 2021-08-03
- Volume
- 6
- Issue
- 1
- Pages
- 58-65
- ISSN
- 2162-3449 (ISSN-L)
- 2334-0770
- OpenAlex
- W2164061616
- Cited by
- 565
- References
- 18
- FWCI
- 34.57
- Type
- conference paper
- Language
- en
- Open access
- diamond
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