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Social and Behavioral Sciences Commons™
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Articles 1 - 4 of 4
Full-Text Articles in Social and Behavioral Sciences
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Journal of Spatial Information Science
In a typical data collection process, a surveyed spatial object is annotated upon creation, and is classified based on its attributes. This annotation can also be guided by textual definitions of objects. However, interpretations of such definitions may differ among people, and thus result in subjective and inconsistent classification of objects. This problem becomes even more pronounced if the cultural and linguistic differences are considered. As a solution, this paper investigates the role of topology as the defining characteristic of a class of spatial objects. We propose a data mining approach based on frequent itemset mining to learn patterns in …
Twitter Location (Sometimes) Matters: Exploring The Relationship Between Georeferenced Tweet Content And Nearby Feature Classes, Stefan Hahmann, Ross S. Purves, Dirk Burghardt
Twitter Location (Sometimes) Matters: Exploring The Relationship Between Georeferenced Tweet Content And Nearby Feature Classes, Stefan Hahmann, Ross S. Purves, Dirk Burghardt
Journal of Spatial Information Science
In this paper, we investigate whether microblogging texts (tweets) produced on mobile devices are related to the geographical locations where they were posted. For this purpose, we correlate tweet topics to areas. In doing so, classified points of interest from OpenStreetMap serve as validation points. We adopted the classification and geolocation of these points to correlate with tweet content by means of manual, supervised, and unsupervised machine learning approaches. Evaluation showed the manual classification approach to be highest quality, followed by the supervised method, and that the unsupervised classification was of low quality. We found that the degree to which …
Mining Sensor Datasets With Spatiotemporal Neighborhoods, Michael Patrick Mcguire, Vandana Janeja, Aryya Gangopadhyay
Mining Sensor Datasets With Spatiotemporal Neighborhoods, Michael Patrick Mcguire, Vandana Janeja, Aryya Gangopadhyay
Journal of Spatial Information Science
Many spatiotemporal data mining methods are dependent on how relationships between a spatiotemporal unit and its neighbors are defined. These relationships are often termed the neighborhood of a spatiotemporal object. The focus of this paper is the discovery of spatiotemporal neighborhoods to find automatically spatiotemporal sub-regions in a sensor dataset. This research is motivated by the need to characterize large sensor datasets like those found in oceanographic and meteorological research. The approach presented in this paper finds spatiotemporal neighborhoods in sensor datasets by combining an agglomerative method to create temporal intervals and a graph-based method to find spatial neighborhoods within …
Exploring Place Through User-Generated Content: Using Flickr Tags To Describe City Cores, Livia Hollenstein, Ross Purves
Exploring Place Through User-Generated Content: Using Flickr Tags To Describe City Cores, Livia Hollenstein, Ross Purves
Journal of Spatial Information Science
Terms used to describe city centers, such as Downtown, are key concepts in everyday or vernacular language. Here, we explore such language by harvesting georeferenced and tagged metadata associated with 8 million Flickr images and thus consider how large numbers of people name city core areas. The nature of errors and imprecision in tagging and georeferencing are quantified, and automatically generated precision measures appear to mirror errors in the positioning of images. Users seek to ascribe appropriate semantics to images, though bulk-uploading and bulk-tagging may introduce bias. Between 0.5--2% of tags associated with georeferenced images analyzed describe city core areas …