Testing the Use of Crowdsourced Information: Case Study of Bike-Share Infrastructure Planning in Cincinnati, Ohio

Considering the power of web-based tools for crowdsourcing, planning organizations are increasingly using these technologies to gather ideas and preferences from the public. These technologies often generate substantial, unstructured data about public needs. However, our understanding of the use of crowdsourced information in planning is still limited. Focusing on the City of Cincinnati Bike-share planning as a case study, this article explores the challenges and considerations of using crowdsourced information. Employing mixed analysis methods, the article analyzes participant suggestions and examines whether and how those suggestions were incorporated into the bike-share plan. Interpretive analysis of interviews provided insights about suggestions that were used in the final plan. The results highlight organizational opportunities and limitations. A variety of organizational factors affected the utility of crowdsourced information in Cincinnati bike-share plan. These include the capability of the planning organizations to analyze data and facilitate participation, and the perception of planners about the value of crowdsourced information and local knowledge

Public participation in the Geoweb era: Geosocial media use in local government

Advances in spatially enabled information and communication technologies (ICTs) have provided governments with the potential to enhance public participation and to collaborate with citizens. This dissertation critically assesses this potential and identifies the opportunities and challenges for local governments to embark on emerging geo-enabled practices. This dissertation first proposes a new typology for classifying geo-enabled practices related to public participation (termed here as geo-participation) and demonstrates the emerging opportunities presented by geo-participation to improve government-citizen collaboration and government operations. This dissertation then provides in-depth examinations of geosocial media as an exemplar geo-participation practice. The first empirical study assesses the potential of repurposing geosocial media data to gauge public opinions. The study suggests that geosocial media can help identify geographies of public perceptions concerning public facilities and services and have the potential to complement other methods of gauging public sentiment. The second empirical study assesses the usefulness of geosocial media for sharing non-emergency issues and identifies an important opportunity of enabling citizen collaboration for reporting and sharing non-emergency issues. Altogether, this dissertation makes several conceptual, empirical, and practical contributions to local government adoption of geo-participation. Conceptually, the proposed typology lays the foundation for researching and implementing geo-participation practices. Empirically, this dissertation tells a story of opportunities and challenges that sheds light on how local governments may adopt geosocial media to solicit citizen input and enable new forms of government-citizen interaction. Practically, this dissertation develops a tool for processing text-based citizen input and models of implementing geosocial media reporting that can help local government develop proper strategies of adopting geosocial media

Testing the Use of Crowdsourced Information: Case Study of Bike-Share Infrastructure Planning in Cincinnati, Ohio

Considering the power of web-based tools for crowdsourcing, planning organizations are increasingly using these technologies to gather ideas and preferences from the public. These technologies often generate substantial, unstructured data about public needs. However, our understanding of the use of crowdsourced information in planning is still limited. Focusing on the City of Cincinnati Bike-share planning as a case study, this article explores the challenges and considerations of using crowdsourced information. Employing mixed analysis methods, the article analyzes participant suggestions and examines whether and how those suggestions were incorporated into the bike-share plan. Interpretive analysis of interviews provided insights about suggestions that were used in the final plan. The results highlight organizational opportunities and limitations. A variety of organizational factors affected the utility of crowdsourced information in Cincinnati bike-share plan. These include the capability of the planning organizations to analyze data and facilitate participation, and the perception of planners about the value of crowdsourced information and local knowledge

Infill Planner: A geo-questionnaire to gather public input on infill developments

Urban infill and intensification planning strategies aim to lead toward more efficient use urban land and ultimately urban forms that more sustainable and offer citizens improved quality of life. Due to the potential impacts of introducing change into established neighborhoods, the implementation of these planning strategies is not straightforward. Urban infill strategies often elicit public reactions, either positively or negatively, which ultimately influence the successes or failures of infill projects. Local knowledge and public input must therefore be considered during these planning processes. Map-based tools are increasingly being adopted to solicit public input in urban planning. However, the varying designs and implementation of these tools outpaces planning research. A research gap relating to what works, how and in which context therefore exists. This thesis seeks to understand how the public considers both site (i.e., property) and situation (i.e., neighborhood) factors when considering potential infill developments. Infill Planner, a web-based tool that combines interactive maps and questionnaires, was developed to allow participants to designate future land uses for potential infill development sites. The tool was tested in a simulated urban infill planning process for selected sites in the City of Stratford, Ontario. Despite the simulated nature of the planning exercise, the research contributes to our understanding of how individuals use map-based data and tools when considering the site-specific and neighbourhood level implications of infill developments. Lessons from the design and implementation testing as well as implications for planning practice and academia, are also discussed

Empowering users to communicate their preferences to machine learning models in Visual Analytics

Recent visual analytic (VA) systems rely on machine learning (ML) to allow users to perform a variety of data analytic tasks, e.g., biologists clustering genome samples, medical practitioners predicting the diagnosis for a new patient, ML practitioners tuning models' hyperparameter settings, etc. These VA systems support interactive construction of models to people (I call them power users) with a diverse set of expertise in ML; from non-experts, to intermediates, to expert ML users. Through my research, I designed and developed VA systems for power users empowering them to communicate their preferences to interactively construct machine learning models for their analytical tasks. In this process, I design algorithms to incorporate user interaction data in machine learning modeling pipelines. Specifically, I deployed and tested (e.g., task completion times, user satisfaction ratings, success rate in finding user-preferred models, model accuracies) two main interaction techniques, multi-model steering, and interactive objective functions to facilitate specification of user goals and objectives to underlying model(s) in VA. However, designing these VA systems for power users poses various challenges, such as addressing diversity in user expertise, metric selection, user modeling to automatically infer preferences, evaluating the success of these systems, etc. Through this work I contribute a set of VA systems that support interactive construction and selection of supervised and unsupervised models using tabular data. In addition, I also present results/findings from a design study of interactive ML in a specific domain with real users and real data.Ph.D

Organizational strategy, technology and public participation in municipal planning

Research focused on public participation in municipal planning typically seeks to evaluate and improve methods for integrating community input into planning decision processes. Research in the use of information and communication technologies (ICTs) to enhance citizen engagement includes, for example, visual or geographical forms of engagement as well as approaches for adapting social technologies to public discursive methods. The continued development of social technologies coupled with increasingly large streams of citizen-generated data intensify both the potential and the perils of ICTs in public participation. Direct, real-time citizen communications lies in stark contrast to the increasing noise and information density in citizen communications and municipal data collection, for example. Such trends create dichotomies and emerging complexities that require new perspectives and models for examining the potential and barriers for citizen engagement in municipal planning decision processes. This research advances academic discourse surrounding public participation in municipal government by examining the organizational role and perspectives of municipal leaders. Key-informant interviews were conducted with 23 municipal leaders in Ontario, Canada. The findings informed the development of an inter-disciplinary component model that positions public participation as a strategic imperative. The component model was applied as a framework to generate insights from a second phase of research, namely a survey of municipal leaders across Canada. The survey findings identify broad deficiencies in municipal participatory capacity, as indicated by significant gaps between, for example, municipal leadership vision for an active, informed public in contrast to municipal structures, processes, analyses, and technologies in support of the vision. Finally, visualization methods were used to identify gaps and opportunities in municipal participatory capacity, and to compare the results across different types and sizes of Canadian municipalities. The organizational component model and visualization tools for public participation capacity developed in this thesis illustrate the interplay between structural organizational factors, managerial behaviors, and ICTs related to municipal public participation. These contributions suggest new approaches for municipal planners faced with the challenges of enhancing public participation capacity within their increasingly complex and information-rich contexts.

Oportunidades de los datos geolocalizados de Twitter en el estudio de la movilidad metropolitana

El crecimiento de las áreas metropolitanas y la especialización de zonas urbanas en áreas de trabajo o residencia han conllevado el aumento de la cantidad, longitud y duración de los viajes que se realizan diariamente. Es necesario contar con datos constantes que proporcionen información actualizada sobre las características espaciales y temporales de la movilidad metropolitana. En las últimas décadas han aparecido una serie de fuentes de datos vinculadas a las Tecnologías de la Información y la Comunicación, que permiten recoger una gran cantidad de datos de forma rápida y frecuente, y en algunos casos, a bajo coste. Estos datos suelen contar con una alta resolución espacio-temporal, son fáciles de actualizar, y permiten la monitorización de patrones de movilidad metropolitana a tiempo casi real. Entre las nuevas fuentes de datos destacan las redes sociales, plataformas donde los usuarios de internet se comunican y comparten ideas, opiniones, e información..

Understanding Public Opinions from Geosocial Media

Increasingly, social media data are linked to locations through embedded GPS coordinates. Many local governments are showing interest in the potential to repurpose these firsthand geo-data to gauge spatial and temporal dynamics of public opinions in ways that complement information collected through traditional public engagement methods. Using these geosocial data is not without challenges since they are usually unstructured, vary in quality, and often require considerable effort to extract information that is relevant to local governments’ needs from large data volumes. Understanding local relevance requires development of both data processing methods and their use in empirical studies. This paper addresses this latter need through a case study that demonstrates how spatially-referenced Twitter data can shed light on citizens’ transportation and planning concerns. A web-based toolkit that integrates text processing methods is used to model Twitter data collected for the Region of Waterloo (Ontario, Canada) between March 2014 and July 2015 and assess citizens’ concerns related to the planning and construction of a new light rail transit line. The study suggests that geosocial media can help identify geographies of public perceptions concerning public facilities and services and have potential to complement other methods of gauging public sentiment

Understanding Public Opinions from Geosocial Media

Increasingly, social media data are linked to locations through embedded GPS coordinates. Many local governments are showing interest in the potential to repurpose these firsthand geo-data to gauge spatial and temporal dynamics of public opinions in ways that complement information collected through traditional public engagement methods. Using these geosocial data is not without challenges since they are usually unstructured, vary in quality, and often require considerable effort to extract information that is relevant to local governments’ needs from large data volumes. Understanding local relevance requires development of both data processing methods and their use in empirical studies. This paper addresses this latter need through a case study that demonstrates how spatially-referenced Twitter data can shed light on citizens’ transportation and planning concerns. A web-based toolkit that integrates text processing methods is used to model Twitter data collected for the Region of Waterloo (Ontario, Canada) between March 2014 and July 2015 and assess citizens’ concerns related to the planning and construction of a new light rail transit line. The study suggests that geosocial media can help identify geographies of public perceptions concerning public facilities and services and have potential to complement other methods of gauging public sentiment