Matthew Tenney

University of Toronto | U of T · Department of Geography

In this paper, we critically explore the interplay of algorithms and civic participation in visions of a city governed by equation, sensor and tweet. We begin by discussing the rhetoric surrounding techno-enabled paths to participatory democracy. This leads to us interrogating how the city is impacted by a discourse that promises to harness social/...

This paper presents a crowd sensing system (CSS) that captures geospatial social media topics and allows the review of results. Using Web-resources derived from social media platforms, the CSS uses a spatially-situated social network graph to harvest user-generated content from selected organizations and members of the public. This allows ‘passivel...

This dissertation explores the concepts of coded engagement as they relate to the role of citizens’ ability to participate in smart cities. Coded engagement is what we call the perspective of citizen-as-sensor in the smart city, as it meets the ubiquitous world of interconnected sensing-technologies and big data. Because of the perceived difficulti...

In this paper, the policies, projects, and promises of “smart” initiatives at the City of Toronto are evaluated, as they manifest through a technological convergence between local government services and an increased focus on citizen services through data‐driven mediums. Through direct participant observation and formal interviews, a robust underst...

This paper presents a crowd sensing system (CSS) that captures geospatial social media topics and allows the review of results. Using Web-resources derived from social media platforms, the CSS uses a spatially-situated social network graph to harvest user-generated content from selected organizations and members of the public. This allows ‘passivel...

Social media has an increasingly important role for facilitating communication between governments and citizens. These streams of geosocial data can shed light on people’s traditions, sentiments, and behavior at an unprecedented scales. However, such large datasets bring challenges to analysis using conventional methodologies and tools. We use Twit...

We propose a crowd sensing system to capture certain dynamics of public participation in a city. Crowd sensing systems (CSS) attempt to capture the opinions of local publics from web- resources. We define our CSS using a spatially-situated social network graph where users along with different variables, such as time, location, social interaction,...

Geocollective is a proof-of-concept project composed of largely open-source software; forming back-end tools required for the collection, processing, and basic scientific analysis of content collected from the Internet. Social media, mobile-technologies, and user-generated content of all kinds have piqued the interest of many social science researc...

The OpenStreetMap (OSM) project represents one of the more popular volunteered geographic information (VGI) projects in the world. This contributed spatial data is used to create global maps that are free to use and edit by anyone. The research presented here, focuses on a systematic quality analysis for Canadian OpenStreetMap data and explores rel...

This thesis is an attempt to integrate contending cognitive approaches to modeling wayfinding behavior. The primary goal is to create a plausible model for exploration tasks within indoor environments. This conceptual model can be extended for practical applications in the design, planning, and social sciences. Using empirical evidence a cognitive...