Mining Urban Perceptions from Social Media Data
Date
2020-04
Authors
Liu, Yu
Yuan, Yihong
Zhang, Fan
Journal Title
Journal ISSN
Volume Title
Publisher
University of Maine
Abstract
This vision paper summaries the methods of using social media data (SMD) to measure urban perceptions. We highlight two major types of data sources (i.e., texts and imagery) and two corresponding techniques (i.e., natural language processing and computer vision). Recognizing the data quality issues of SMD, we propose three criteria for improving the reliability of SMD-based studies. In addition, integrating multi-source data is a promising approach to mitigating the data quality problems.
Description
Keywords
urban perceptions, place, data quality, natural language processing, computer vision, social media data, Geography and Environmental Studies
Citation
Liu, Y., Yuan, Y., & Zhang, F. (2020). Mining urban perceptions from social media data. Journal of Spatial Information Science, 2020(20), pp. 51–55.
Rights
Rights Holder
© 2020 The Authors.
Rights License
This work is licensed under a Creative Commons Attribution 3.0 Unported License.