Journal
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
Volume 54, Issue -, Pages 240-254Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.compenvurbsys.2015.09.001
Keywords
Areas of interest; AOI; Social media; Flickr; DBSCAN; Chi-shape; Tag extraction; Photo analysis; Data mining
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Urban areas of interest (AOI) refer to the regions within an urban environment that attract people's attention. Such areas often have high exposure to the general public, and receive a large number of visits. As a result, urban AOI can reveal useful information for city planners, transportation analysts, and location-based service providers to plan new business, extend existing infrastructure, and so forth. Urban AOI exist in people's perception and are defined by behaviors. However, such perception was rarely captured until the Social Web information technology revolution. Social media data record the interactions between users and their surrounding environment, and thus have the potential to uncover interesting urban areas and their underlying spatiotemporal dynamics. This paper presents a coherent framework for extracting and understanding urban AOI based on geotagged photos. Six different cities from six different countries have been selected for this study, and Flickr photo data covering these cities in the past ten years (2004-2014) have been retrieved. We identify. AOI using DBSCAN clustering algorithm, understand AOI by extracting distinctive textual tags and preferable photos, and discuss the spatiotemporal dynamics as well as some insights derived from-the AOI An interactive prototype has also been implemented as a proof-of-concept. While Flickr data have been used in this study, the presented framework can also be applied to other geotagged photos. (C) 2015 Elsevier Ltd. All rights reserved.
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