Mining urban perceptions from social media data
Keywords:social media data, urban perceptions, place, data quality, natural language processing, computer vision
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.
Copyright (c) 2020 Yu Liu, Yihong Yuan, Fan Zhang
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