Geotagging One Hundred Million Twitter Accounts with Total Variation Minimization

Geographically annotated social media is extremely valuable for modern information retrieval. However, when researchers can only access publicly-visible data, one quickly finds that social media users rarely publish location information. In this work, we provide a method which can geolocate the overwhelming majority of active Twitter users, independent of their location sharing preferences, using only publicly-visible Twitter data. Our method infers an unknown user's location by examining their friend's locations. We frame the geotagging problem as an optimization over a social network with a total variation-based objective and provide a scalable and distributed algorithm for its solution. Furthermore, we show how a robust estimate of the geographic dispersion of each user's ego network can be used as a per-user accuracy measure which is effective at removing outlying errors. Leave-many-out evaluation shows that our method is able to infer location for 101,846,236 Twitter users at a median error of 6.38 km, allowing us to geotag over 80\% of public tweets.Comment: 9 pages, 8 figures, accepted to IEEE BigData 2014, Compton, Ryan, David Jurgens, and David Allen. "Geotagging one hundred million twitter accounts with total variation minimization." Big Data (Big Data), 2014 IEEE International Conference on. IEEE, 201

Depicting urban boundaries from a mobility network of spatial interactions: A case study of Great Britain with geo-located Twitter data

Existing urban boundaries are usually defined by government agencies for administrative, economic, and political purposes. Defining urban boundaries that consider socio-economic relationships and citizen commute patterns is important for many aspects of urban and regional planning. In this paper, we describe a method to delineate urban boundaries based upon human interactions with physical space inferred from social media. Specifically, we depicted the urban boundaries of Great Britain using a mobility network of Twitter user spatial interactions, which was inferred from over 69 million geo-located tweets. We define the non-administrative anthropographic boundaries in a hierarchical fashion based on different physical movement ranges of users derived from the collective mobility patterns of Twitter users in Great Britain. The results of strongly connected urban regions in the form of communities in the network space yield geographically cohesive, non-overlapping urban areas, which provide a clear delineation of the non-administrative anthropographic urban boundaries of Great Britain. The method was applied to both national (Great Britain) and municipal scales (the London metropolis). While our results corresponded well with the administrative boundaries, many unexpected and interesting boundaries were identified. Importantly, as the depicted urban boundaries exhibited a strong instance of spatial proximity, we employed a gravity model to understand the distance decay effects in shaping the delineated urban boundaries. The model explains how geographical distances found in the mobility patterns affect the interaction intensity among different non-administrative anthropographic urban areas, which provides new insights into human spatial interactions with urban space.Comment: 32 pages, 7 figures, International Journal of Geographic Information Scienc

Mapping an ancient historian in a digital age: the Herodotus Encoded Space-Text-Image Archive (HESTIA)

HESTIA (the Herodotus Encoded Space-Text-Imaging Archive) employs the latest digital technology to develop an innovative methodology to the study of spatial data in Herodotus' Histories. Using a digital text of Herodotus, freely available from the Perseus on-line library, to capture all the place-names mentioned in the narrative, we construct a database to house that information and represent it in a series of mapping applications, such as GIS, GoogleEarth and GoogleMap Timeline. As a collaboration of academics from the disciplines of Classics, Geography, and Archaeological Computing, HESTIA has the twin aim of investigating the ways geography is represented in the Histories and of bringing Herodotus' world into people's homes

Mapping environmental injustices: pitfalls and potential of geographic information systems in assessing environmental health and equity.

Geographic Information Systems (GIS) have been used increasingly to map instances of environmental injustice, the disproportionate exposure of certain populations to environmental hazards. Some of the technical and analytic difficulties of mapping environmental injustice are outlined in this article, along with suggestions for using GIS to better assess and predict environmental health and equity. I examine 13 GIS-based environmental equity studies conducted within the past decade and use a study of noxious land use locations in the Bronx, New York, to illustrate and evaluate the differences in two common methods of determining exposure extent and the characteristics of proximate populations. Unresolved issues in mapping environmental equity and health include lack of comprehensive hazards databases; the inadequacy of current exposure indices; the need to develop realistic methodologies for determining the geographic extent of exposure and the characteristics of the affected populations; and the paucity and insufficiency of health assessment data. GIS have great potential to help us understand the spatial relationship between pollution and health. Refinements in exposure indices; the use of dispersion modeling and advanced proximity analysis; the application of neighborhood-scale analysis; and the consideration of other factors such as zoning and planning policies will enable more conclusive findings. The environmental equity studies reviewed in this article found a disproportionate environmental burden based on race and/or income. It is critical now to demonstrate correspondence between environmental burdens and adverse health impacts--to show the disproportionate effects of pollution rather than just the disproportionate distribution of pollution sources

Mapping for the Masses: Accessing Web 2.0 through Crowdsourcing

The authors describe how we are harnessing the power of web 2.0 technologies to create new approaches to collecting, mapping, and sharing geocoded data. The authors begin with GMapCreator that lets users fashion new maps using Google Maps as a base. The authors then describe MapTube that enables users to archive maps and demonstrate how it can be used in a variety of contexts to share map information, to put existing maps into a form that can be shared, and to create new maps from the bottom-up using a combination of crowdcasting, crowdsourcing, and traditional broadcasting. The authors conclude by arguing that such tools are helping to define a neogeography that is essentially "mapping for the masses,'' while noting that there are many issues of quality, accuracy, copyright, and trust that will influence the impact of these tools on map-based communication