Revealing Multiplexity of Information-based City Relationships Using Collocation Analysis
Visiting speaker
Tongjing Wang
PhD Candidate, Utrecht University
Past Talk
Hybrid
Tuesday
Dec 5, 2023
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3:30 pm
EST
Virtual
177 Huntington Ave.
11th floor
Devon House
58 St Katharine's Way
London E1W 1LP, UK
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Cities are related in many ways and the importance of their relationships is well acknowledged. However, most accessible city relational data is geolocation-based and limited within city scales. The broader scope of digital information-based intercity relationships is often overlooked due to the difficulties of extracting and quantifying such relationships. One promising approach to tackle this challenge is collocation analysis, which uses the higher-than-usual co-occurrence of placenames in text to proxy the strength of relationships between cities. This presentation aims to explore the contributions collocation analysis can offer in city network studies. It will first present a lexicon-based collocation analysis method capable of uncovering the multidimensions of city connections, and then will showcase how the collocation results can shed light on informing regional planning policy. To conclude, the presentation will demonstrate the complexities and dynamics of information-based city relationships by extracting collocation results from texts of various languages, genres, and time periods.
About the speaker
About the speaker
Tongjing Wang is a Ph.D. candidate in the Economic Geography section of the Human Geography and Spatial Planning Department at Utrecht University in The Netherlands and an affiliated student at the Multimedia Computing group at Delft University of Technology. His Ph.D. research focuses on developing text-mining methods to capture information-based intercity relationships and analyze these relationships using network analysis to gain insights for city and regional planning. He is currently a visiting scholar at The NULab for Texts, Maps, and Networks at Northeastern University, supported by the EU-funded H2020 MSCA RISE TREND.
Tongjing Wang is a Ph.D. candidate in the Economic Geography section of the Human Geography and Spatial Planning Department at Utrecht University in The Netherlands and an affiliated student at the Multimedia Computing group at Delft University of Technology. His Ph.D. research focuses on developing text-mining methods to capture information-based intercity relationships and analyze these relationships using network analysis to gain insights for city and regional planning. He is currently a visiting scholar at The NULab for Texts, Maps, and Networks at Northeastern University, supported by the EU-funded H2020 MSCA RISE TREND.