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- Creators: Arizona State University
Description
Images are ubiquitous in communicating complex information about the future. From political messages to extreme weather warnings, they generate understanding, incite action, and inform expectations with real impact today. The future has come into sharp focus in recent years. Issues like climate change, gene editing, and smart cities are pushing policy makers, scientists, and designers to rethink how society plans and prepares for tomorrow. While academic and practice communities have increasingly turned their gaze toward the future, little attention is paid to how it is depicted and even less to the role visualization technologies play in depicting it. Visualization technologies are those that transform non-visual information into 2D or 3D imagery and generate depictions of certain phenomena, real or perceived. This research helps to fill this gap by examining the role visualization technologies play in how individuals know and make decisions about the future.
This study draws from three phases of research set in the context of urban development, where images of the future are generated by architects and circulated by built environment professionals to affect client and public decision-making. I begin with a systematic review of professional design literature to identify norms related to visualization. I then conduct in-depth interviews with expert architects to draw out how visualization technologies are used to influence client decision-making. I dive into how different tools manage the future and generate different forms of certainty, uncertainty, persuasion, and risk. Complementing the review and interviews is a case study on ASU at Mesa City Center, a development project aimed at revitalizing downtown Mesa, Arizona. Analysis highlights how project-specific visual tools affect decision-making and the role that client imagination and inference play in understanding and preference. This research unpacks the social, technical, and emotional knowledge embedded in visualization technologies and reveals how they affect decision-making. Information about the future is uniquely mediated by each technology with decision-making bound up in larger sociopolitical processes aimed at reducing uncertainty, building trust, and managing expectations. This suggests that the visual tools we use to depict the future are much more dynamic and influential than they are given credit for.
This study draws from three phases of research set in the context of urban development, where images of the future are generated by architects and circulated by built environment professionals to affect client and public decision-making. I begin with a systematic review of professional design literature to identify norms related to visualization. I then conduct in-depth interviews with expert architects to draw out how visualization technologies are used to influence client decision-making. I dive into how different tools manage the future and generate different forms of certainty, uncertainty, persuasion, and risk. Complementing the review and interviews is a case study on ASU at Mesa City Center, a development project aimed at revitalizing downtown Mesa, Arizona. Analysis highlights how project-specific visual tools affect decision-making and the role that client imagination and inference play in understanding and preference. This research unpacks the social, technical, and emotional knowledge embedded in visualization technologies and reveals how they affect decision-making. Information about the future is uniquely mediated by each technology with decision-making bound up in larger sociopolitical processes aimed at reducing uncertainty, building trust, and managing expectations. This suggests that the visual tools we use to depict the future are much more dynamic and influential than they are given credit for.
ContributorsSelkirk, Kaethe (Author) / Selin, Cynthia (Thesis advisor) / Wylie, Ruth (Committee member) / Boradkar, Prasad (Committee member) / Arizona State University (Publisher)
Created2019
Description
ABSTRACT
The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.
The cold and the flu are two of the most prevalent diseases in the world. Many over the counter (OTC) medications have been created to combat the symptoms of these illnesses. Some medications take a holistic approach by claiming to alleviate a wide range of symptoms, while others target a specific symptom. As these medications become more ubiquitous within the United State of America (USA), consumers form associations and mental models about the cold/flu field. The goal of Study 1 was to build a Pathfinder network based on the associations consumers make between cold/flu symptoms and medications. 100 participants, 18 years or older, fluent in English, and residing in the USA, completed a survey about the relatedness of cold/flu symptoms to OTC medications. They rated the relatedness on a scale of 1 (highly unrelated) to 7 (highly related) and those rankings were used to build a Pathfinder network that represented the average of those associations. Study 2 was conducted to validate the Pathfinder network. A different set of 90 participants with the same restrictions as those in Study 1 completed a matching associations test. They were prompted to match symptoms and medications they associated closely with each other. Results showered a significant negative correlation between the geodetic distance (the number of links between objects in the Pathfinder network) separating symptoms and medications and frequency of pairing symptoms with medication. This provides evidence of the validity of the Pathfinder network. It was also seen that, higher the relatedness rating between symptoms and medications in Study 1, higher the frequency of pairing symptom to medication in Study 2, and the more directly linked those symptoms and medications were in the Pathfinder network. This network can inform pharmaceutical companies about which symptoms they most closely associate with, who their competitors are, what symptoms they can dominate, and how to market their medications more effectively.
ContributorsTendolkar, Tanvi Gopal (Author) / Branaghan, Russell (Thesis advisor) / Chiou, Erin (Committee member) / Craig, Scotty (Committee member) / Arizona State University (Publisher)
Created2020
Description
When looking at drawings of graphs, questions about graph density, community structures, local clustering and other graph properties may be of critical importance for analysis. While graph layout algorithms have focused on minimizing edge crossing, symmetry, and other such layout properties, there is not much known about how these algorithms relate to a user’s ability to perceive graph properties for a given graph layout. This study applies previously established methodologies for perceptual analysis to identify which graph drawing layout will help the user best perceive a particular graph property. A large scale (n = 588) crowdsourced experiment is conducted to investigate whether the perception of two graph properties (graph density and average local clustering coefficient) can be modeled using Weber’s law. Three graph layout algorithms from three representative classes (Force Directed - FD, Circular, and Multi-Dimensional Scaling - MDS) are studied, and the results of this experiment establish the precision of judgment for these graph layouts and properties. The findings demonstrate that the perception of graph density can be modeled with Weber’s law. Furthermore, the perception of the average clustering coefficient can be modeled as an inverse of Weber’s law, and the MDS layout showed a significantly different precision of judgment than the FD layout.
ContributorsSoni, Utkarsh (Author) / Maciejewski, Ross (Thesis advisor) / Kobourov, Stephen (Committee member) / Sefair, Jorge (Committee member) / Arizona State University (Publisher)
Created2018