repository for geography work and other things completed by kufre u.
In their (2017) work, Wu, Wood, Fisher, and Lindsey evaluate the viability of using geotagged posts from social media, particularly Flickr and Twitter, as proxies for urban trail use. The City of Minneapolis was used as the study area of this research. This study leans towards the deductive, first presenting the question of whether social media can be used to estimate trail traffic and then going on to answering the question through research, concluding that although the correlation between social media posts and trail use is weak, social media can still be used for general planning (p. 802).
Wu et al. used the application program interfaces (APIs) of Twitter and Flickr to query for geotagged images posted during 2013, utilizing the latitude/longitude coordinates associated with the posts for analysis (p. 792). The parameters used for these queries are not described in this article nor are the program(s) used to interact with the APIs listed. A GIS was used to create 200-foot buffers along 80 miles of trails split into mile-long segments and the number of photos contained within these buffers were counted (p.792). Proxies for trail demand were created based on the unique combinations of users and the date which they posted an image or tweet (p. 792-3). These counts were then compared to estimates of trail traffic reported previous studies and statistical models were used to see if there was any correlation between social media data. STATA was used for all statistical models (p.794). The previous studies used data from the trail traffic monitoring program in Minneapolis. This program was started by the University of Minnesota, the Minneapolis Park and Recreation Board, and the Minneapolis Department of Public Works and used guidelines from the Federal Highway Administration (p. 793).
Whether this research is both reproducible and replicable is debatable. The fact that Wu et al. were able to “[follow] methods developed by Wood et al. (2011) and used by Keeler et al. (2015)” may hinge on the fact that Spencer A. Wood, a contributor in this (2017) study, was involved in both previous studies where Twitter and Flickr geolocation data were extracted and implemented in geographic analyses (p. 792). This study still was, however, the replication of past research. The article mentions that the InVEST Visitation model is used for spatial queries with the geotagged Flickr photos, though is not clear to me if these spatial queries were also used with the Twitter data and the extent to which they were used. A clear description of how the data was extracted from the Twitter and Flickr APIs as well as the data used in the study would make study reproducible, though the question of whether it is replicable remains. It is possible to get data through Twitter and Flickr APIs and use OpenStreetMap to get the trails to make buffers around, though getting data for trail traffic estimates to compare against the geotagged posts may prove to be difficult. If one wishes only to complete the first half of study and create proxies for trail demand, the work of Wu et al. could be replicable.
Wu, X., Wood, S. A., Fisher, D., & Lindsey, G. (2017). Photos, tweets, and trails: Are social media proxies for urban trail use?. Journal of Transport and Land Use, 10(1). https://doi.org/10.5198/jtlu.2017.1130