Spatial Articulations of Race, Desire, and Belonging in Western North Carolina

The sociocultural mythology of the South homogenizes it as a site of abjection. To counter the regionalist discourse, the dissertation intersects queer sexualities with gender and race and focuses on exploring identity and spatial formation among Black lesbian and queer women. The dissertation seeks to challenge the monolith of the South and place the region into multiple contexts and to map Black geographies through an intentional intersectional account of Black queer women. The dissertation utilizes qualitative research methods to ascertain understandings of lived experiences in the production of space. The dissertation argues that an idea of Progress has been indoctrinated as a synonym for the lgbtq civil rights movement and subsequently provides an analysis of progress discourses and queer sexualities and political campaigns of equality in the South. Analyses revealed different ways to situate progress utilizing the public contributions of three Black women interviewed for the dissertation. Moreover, the dissertation utilizes six Black queer and lesbian women to explain the multifarious nature of identities and their construction in place. Black queer and lesbian women produce spaces that deconstruct the normativity of stasis and physicality, and the dissertation explores the consequential realities of being a body in space. These consequences are particularly highlighted in the dissertation by discussions of the processes of racialization in the bounded and unbounded senses of space and place and the impacts of religious institutions, specifically Christianity. The dissertation concluded that no space is without complication. Other considerations should be made in the advancement of alleviating oppression deeply embedded in United States landscapes. Black women’s geographies offer epistemological and ontological renderings that enrich analyses of space, place, and landscape. The dissertation also concludes that Black women’s bodies represent sites for the production of geographic knowledge through narrating their spaces of material trajectories of interlocking, multiscalar lives.

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.