Urban Analytics: History, Trajectory, and Critique

• URL: http://arxiv.org/abs/2105.07020v1
• Date: Fri, 14 May 2021 18:20:50 GMT
• Title: Urban Analytics: History, Trajectory, and Critique
• Authors: Geoff Boeing, Michael Batty, Shan Jiang, Lisa Schweitzer
• Abstract summary: Urban analytics combines spatial analysis, statistics, computer science, and urban planning to understand and shape city futures. While promises better policymaking insights, concerns exist around its scope and impacts on privacy, ethics, and social control. This chapter reflects on the history and trajectory of urban analytics as a professional discipline.
• Score: 3.004202743783571
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Urban analytics combines spatial analysis, statistics, computer science, and urban planning to understand and shape city futures. While it promises better policymaking insights, concerns exist around its epistemological scope and impacts on privacy, ethics, and social control. This chapter reflects on the history and trajectory of urban analytics as a scholarly and professional discipline. In particular, it considers the direction in which this field is going and whether it improves our collective and individual welfare. It first introduces early theories, models, and deductive methods from which the field originated before shifting toward induction. It then explores urban network analytics that enrich traditional representations of spatial interaction and structure. Next it discusses urban applications of spatiotemporal big data and machine learning. Finally, it argues that privacy and ethical concerns are too often ignored as ubiquitous monitoring and analytics can empower social repression. It concludes with a call for a more critical urban analytics that recognizes its epistemological limits, emphasizes human dignity, and learns from and supports marginalized communities.

Related papers

• InclusiViz: Visual Analytics of Human Mobility Data for Understanding and Mitigating Urban Segregation [41.758626973743525]
  InclusiViz is a novel visual analytics system for multi-level analysis of urban segregation. We developed a deep learning model to predict mobility patterns across social groups using environmental features, augmented with explainable AI. The system integrates innovative visualizations that allow users to explore segregation patterns from broad overviews to fine-grained detail.
  arXiv  Detail & Related papers  (2025-01-07T07:50:36Z)
• Towards Asimov's Psychohistory: Harnessing Topological Data Analysis, Artificial Intelligence and Social Media data to Forecast Societal Trends [0.0]
  In the age of big data and advanced computational methods, the prediction of large-scale social behaviors is becoming increasingly feasible. This paper consists of a theoretical exploration of the integration of computational power and mathematical frameworks. I argue that these tools provide unprecedented clarity into the dynamics of large communities.
  arXiv  Detail & Related papers  (2024-07-03T18:44:36Z)
• Unified Data Management and Comprehensive Performance Evaluation for Urban Spatial-Temporal Prediction [Experiment, Analysis & Benchmark] [78.05103666987655]
  This work addresses challenges in accessing and utilizing diverse urban spatial-temporal datasets. We introduceatomic files, a unified storage format designed for urban spatial-temporal big data, and validate its effectiveness on 40 diverse datasets. We conduct extensive experiments using diverse models and datasets, establishing a performance leaderboard and identifying promising research directions.
  arXiv  Detail & Related papers  (2023-08-24T16:20:00Z)
• Beyond case studies: Teaching data science critique and ethics through sociotechnical surveillance studies [0.0]
  Ethics have become an urgent concern for data science research, practice, and instruction in the wake of growing critique of algorithms and systems showing that they reinforce structural oppression. We designed a data science ethics course that spoke to the social phenomena at the root of critical data studies through analysis of a pressing sociotechnical system: surveillance systems. Students developed critical analysis skills that allowed them to investigate surveillance systems of their own and identify their benefits, harms, main proponents, those who resist them.
  arXiv  Detail & Related papers  (2023-05-03T20:24:42Z)
• Self-supervised Hypergraph Representation Learning for Sociological Analysis [52.514283292498405]
  We propose a fundamental methodology to support the further fusion of data mining techniques and sociological behavioral criteria. First, we propose an effective hypergraph awareness and a fast line graph construction framework. Second, we propose a novel hypergraph-based neural network to learn social influence flowing from users to users.
  arXiv  Detail & Related papers  (2022-12-22T01:20:29Z)
• Data analytics on key indicators for the city's urban services and dashboards for leadership and decision-making [0.0]
  Dashboards may collect, display, analyze, and provide information on regional performance to help smart cities development have sustainability. This chapter culminates Data Analytics on key indicators for the city's urban services and dashboards for leadership and decision-making.
  arXiv  Detail & Related papers  (2022-12-01T19:05:16Z)
• Causal Reasoning Meets Visual Representation Learning: A Prospective Study [117.08431221482638]
  Lack of interpretability, robustness, and out-of-distribution generalization are becoming the challenges of the existing visual models. Inspired by the strong inference ability of human-level agents, recent years have witnessed great effort in developing causal reasoning paradigms. This paper aims to provide a comprehensive overview of this emerging field, attract attention, encourage discussions, bring to the forefront the urgency of developing novel causal reasoning methods.
  arXiv  Detail & Related papers  (2022-04-26T02:22:28Z)
• Didn't see that coming: a survey on non-verbal social human behavior forecasting [47.99589136455976]
  Non-verbal social human behavior forecasting has increasingly attracted the interest of the research community in recent years. Its direct applications to human-robot interaction and socially-aware human motion generation make it a very attractive field. We define the behavior forecasting problem for multiple interactive agents in a generic way that aims at unifying the fields of social signals prediction and human motion forecasting.
  arXiv  Detail & Related papers  (2022-03-04T18:25:30Z)
• Automatic Gaze Analysis: A Survey of DeepLearning based Approaches [61.32686939754183]
  Eye gaze analysis is an important research problem in the field of computer vision and Human-Computer Interaction. There are several open questions including what are the important cues to interpret gaze direction in an unconstrained environment. We review the progress across a range of gaze analysis tasks and applications to shed light on these fundamental questions.
  arXiv  Detail & Related papers  (2021-08-12T00:30:39Z)
• Automatic Extraction of Urban Outdoor Perception from Geolocated Free-Texts [1.8419317899207144]
  We propose an automatic and generic approach to extract people's perceptions. We exemplify our approach in the context of urban outdoor areas in Chicago, New York City and London. We show that our approach can be helpful to better understand urban areas considering different perspectives.
  arXiv  Detail & Related papers  (2020-10-13T14:59:46Z)
• Urban Sensing based on Mobile Phone Data: Approaches, Applications and Challenges [67.71975391801257]
  Much concern in mobile data analysis is related to human beings and their behaviours. This work aims to review the methods and techniques that have been implemented to discover knowledge from mobile phone data.
  arXiv  Detail & Related papers  (2020-08-29T15:14:03Z)
• City limits in the age of smartphones and urban scaling [0.0]
  Urban planning still lacks appropriate standards to define city boundaries across urban systems. ICT provide the potential to portray more accurate descriptions of the urban systems. We apply computational techniques over a large volume of mobile phone records to define urban boundaries.
  arXiv  Detail & Related papers  (2020-05-06T17:31:21Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.