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Full-Text Articles in Spatial Science
Centering Transgender Consumers In Conceptualizations Of Marketplace Marginalization And Digital Spaces, Beck Hansman, Jenna Drenten Ph.D.
Centering Transgender Consumers In Conceptualizations Of Marketplace Marginalization And Digital Spaces, Beck Hansman, Jenna Drenten Ph.D.
School of Business: Faculty Publications and Other Works
The purpose of this study is to center transgender consumers in the conceptualizations between marketplace marginalization and digital spaces. We examine trans-gender crowdfunding as a hashtag-bounded digital space created by and for the transgender community–namely, the #TransCrowdFund digital space on Twitter. We draw on trans digital geographies as a novel analytical lens to focus attention on transgender consumers' unique experiences in and between digital spaces. Through qualitative hashtag mapping, we analyzed a sample of 200 Twitter profiles and accompanying tweets drawn from individuals using the#TransCrowdFund hashtag. Findings suggest transgender consumers utilize crowdfunding as a hashtag-bounded digital space in three ways: …
Temporal And Spatiotemporal Investigation Of Tourist Attraction Visit Sentiment On Twitter, Jose J. Padilla, Hamdi Kavak, Christopher J. Lynch, Ross J. Gore, Saikou Y. Diallo
Temporal And Spatiotemporal Investigation Of Tourist Attraction Visit Sentiment On Twitter, Jose J. Padilla, Hamdi Kavak, Christopher J. Lynch, Ross J. Gore, Saikou Y. Diallo
VMASC Publications
In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists' emotions when visiting a city's tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and …
The Billion Object Platform (Bop): A System To Lower Barriers To Support Big, Streaming, Spatio-Temporal Data Sources, Devika Kakkar, Ben Lewis, David Smiley, Ariel Nunez
The Billion Object Platform (Bop): A System To Lower Barriers To Support Big, Streaming, Spatio-Temporal Data Sources, Devika Kakkar, Ben Lewis, David Smiley, Ariel Nunez
Free and Open Source Software for Geospatial (FOSS4G) Conference Proceedings
With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a big spatio-temporal data visualization platform called the Billion Object Platform or "BOP". The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. Since once archived, streaming data gets big fast, and since most GIS systems don't support interactive visualization of millions of objects, a new platform was needed. The BOP is loaded with the latest billion geo-tweets and is fed a real-time stream of about 1 million tweets per day. The CGA …