HCJun 8, 2021
Cartographic Design of Cultural MapsEdyta Paulina Bogucka, Marios Constantinides, Luca Maria Aiello et al.
Throughout history, maps have been used as a tool to explore cities. They visualize a city's urban fabric through its streets, buildings, and points of interest. Besides purely navigation purposes, street names also reflect a city's culture through its commemorative practices. Therefore, cultural maps that unveil socio-cultural characteristics encoded in street names could potentially raise citizens' historical awareness. But designing effective cultural maps is challenging, not only due to data scarcity but also due to the lack of effective approaches to engage citizens with data exploration. To address these challenges, we collected a dataset of 5,000 streets across the cities of Paris, Vienna, London, and New York, and built their cultural maps grounded on cartographic storytelling techniques. Through data exploration scenarios, we demonstrated how cultural maps engage users and allow them to discover distinct patterns in the ways these cities are gender-biased, celebrate various professions, and embrace foreign cultures.
HCJun 8, 2021
Streetonomics: Quantifying Culture Using Street NamesMelanie Bancilhon, Marios Constantinides, Edyta Paulina Bogucka et al.
Quantifying a society's value system is important because it suggests what people deeply care about -- it reflects who they actually are and, more importantly, who they will like to be. This cultural quantification has been typically done by studying literary production. However, a society's value system might well be implicitly quantified based on the decisions that people took in the past and that were mediated by what they care about. It turns out that one class of these decisions is visible in ordinary settings: it is visible in street names. We studied the names of 4,932 honorific streets in the cities of Paris, Vienna, London and New York. We chose these four cities because they were important centers of cultural influence for the Western world in the 20th century. We found that street names greatly reflect the extent to which a society is gender biased, which professions are considered elite ones, and the extent to which a city is influenced by the rest of the world. This way of quantifying a society's value system promises to inform new methodologies in Digital Humanities; makes it possible for municipalities to reflect on their past to inform their future; and informs the design of everyday's educational tools that promote historical awareness in a playful way.
HCOct 25, 2020
Let's Gamble: How a Poor Visualization Can Elicit Risky BehaviorMelanie Bancilhon, Zhengliang Liu, Alvitta Ottley
Data visualizations are standard tools for assessing and communicating risks. However, it is not always clear which designs are optimal or how encoding choices might influence risk perception and decision-making. In this paper, we report the findings of a large-scale gambling game that immersed participants in an environment where their actions impacted their bonuses. Participants chose to either enter a lottery or receive guaranteed monetary gains based on five common visualization designs. By measuring risk perception and observing decision-making, we showed that icon arrays tended to elicit economically sound behavior. We also found that people were more likely to gamble when presented area proportioned triangle and circle designs. Using our results, we model risk perception and discuss how our findings can improve visualization selection.
HCOct 8, 2020
Did You Get The Gist Of It? Understanding How Visualization Impacts Decision-MakingMelanie Bancilhon, Alvitta Ottley
As visualization researchers evaluate the impact of visualization design on decision-making, they often hold a one-dimensional perspective on the cognitive processes behind making a decision. Several psychological and economical researchers have shown that to make decisions, people rely on quantitative reasoning as well as gist-based intuition -- two systems that operate in parallel. In this position paper, we discuss decision theories and provide suggestions to bridge the gap between the evaluation of decision-making in visualization and psychology research. The goal is to question the limits of our knowledge and to advocate for a more nuanced understanding of decision-making with visualization.
HCSep 13, 2020
Expectation Versus Reality: The Failed Evaluation of a Mixed-Initiative Visualization SystemSunwoo Ha, Adam Kern, Melanie Bancilhon et al.
Our research aimed to present the design and evaluation of a mixed-initiative system that aids the user in handling complex datasets and dense visualization systems. We attempted to demonstrate this system with two trials of an online between-groups, two-by-two study, measuring the effects of this mixed-initiative system on user interactions and system usability. However, due to flaws in the interface design and the expectations that we put on users, we were unable to show that the adaptive system had an impact on user interactions or system usability. In this paper, we discuss the unexpected findings that we found from our "failed" experiments and examine how we can learn from our failures to improve further research.
HCOct 22, 2019
Let's Gamble: Uncovering the Impact of Visualization on Risk Perception and Decision-MakingMelanie Bancilhon, Zhengliang Liu, Alvitta Ottley
Data visualizations are standard tools for assessing and communicating risks. However, it is not always clear which designs are optimal or how encoding choices might influence risk perception and decision-making. In this paper, we report the findings of a large-scale gambling game that immersed participants in an environment where their actions impacted their bonuses. Participants chose to either enter a draw or receive guaranteed monetary gains based on five common visualization designs. By measuring risk perception and observing decision-making, we showed that icon arrays tended to elicit economically sound behavior. We also found that people were more likely to gamble when presented area proportioned triangle and circle designs. Using our results, we model risk perception and decisions for each visualization and provide a ranking to improve visualization selection.