Mapping Urban Identity: A Spatial Semantic Graph-Based Approach for Digital Footprint Analysis in Contemporary Sociocultural Contexts

Venue: ACL

Reason for rejection: Despite its interdisciplinary potential, the paper required substantial revisions to its writing, motivation, problem formulation, method description, comparison with prior work and empirical evaluation to establish its novelty and effectiveness.

Abstract

This paper addresses the contemporary challenges of identity in the context of “fluid modernity,” focusing on the sociocultural and territorial aspects influenced by globalization. The authors propose a spatial semantic graph-based method to analyze unstructured textual data from social media and other sources to identify and understand local identity in urban environments. The method involves locality extraction through street and road network graphs, and semantic content extraction using keyword analysis. The spatial and semantic graphs are then merged, allowing for various analytical methods. The study aims to contribute to the understanding of local identity formation, taking into account both spatial and semantic dimensions. The proposed method is applied to a dataset from social network VK, and the paper discusses the results, highlighting communities and specific cases. The authors acknowledge the limitations of the current approach, emphasizing the need for further refinement in identifying toponyms and improving the semantic analysis for more nuanced insights into the identified entities. The paper concludes by discussing the potential applications and implications of the developed method in studying urban identity and events.