Modeling Human Visual Search Performance on Realistic Webpages Using Analytical and Deep Learning Methods

Modeling visual search not only offers an opportunity to predict the usability of an interface before actually testing it on real users, but also advances scientific understanding about human behavior. In this work, we first conduct a set of analyses on a large-scale dataset of visual search tasks on realistic webpages. We then present a deep neural network that learns to predict the scannability of webpage content, i.e., how easy it is for a user to find a specific target. Our model leverages both heuristic-based features such as target size and unstructured features such as raw image pixels. This approach allows us to model complex interactions that might be involved in a realistic visual search task, which can not be easily achieved by traditional analytical models. We analyze the model behavior to offer our insights into how the salience map learned by the model aligns with human intuition and how the learned semantic representation of each target type relates to its visual search performance.Comment: the 2020 CHI Conference on Human Factors in Computing System

Social Interaction, Observational Learning, and Privacy: the "Do Not Call" Registry

Many empirical studies have inferred contagion in behavior from a correlation between individual behavior and the behavior of others in the same social group, rather than from any direct evidence. The correlation has been variously attributed to social interaction, word of mouth communication, and observational learning. As Manski (1993) famously observed, such correlation might be explained by peer group influence, but also, similar responses to common environmental changes. More generally, correlation in behavior raises two questions – how information is transmitted and why individuals follow the choices of others. We address these questions in the context of subscriptions to the U.S. "do not call" registry in June-August 2003. Using a rich set of data culled from multiple sources, including longitudinal observations of household choice, we are able to separately identify -- Methods by which information is transmitted – social interaction and news media; -- Reasons why households follow the choices of others – observational learning and telemarketing diversion, and the impact of household heterogeneity on such learning and diversion. Among methods of information transmission, social interaction was relatively more important than news media. Among reasons for contagion, telemarketing diversion was relatively more important than observational learning, while the extent of learning decreased with social heterogeneity.

Either, Or. Exploration of an Emerging Decision Theory.

A novel decision theory is emerging out of sparse findings in economics, mathematics and, most importantly, psychology and computational cognitive science. It rejects a fundamental assumption of the theory of rational decision-making, namely, that uncertain belief rests on independent assessment of utility and probability, and includes envisioning possibilities within its scope. Several researchers working with these premises, independently of one another, arrived at the conclusion that decision is made by highlighting the positive features of the alternative that will be chosen while opposing it to a loosing alternative, whose unpleasant aspects have been stressed. This article frames together contributions from different disciplines, often unknown to one another, with the hope of improving the coordination of research efforts. Furthermore, it discusses the status of the novel theory with respect to our current idea of rationality.Rationality; Shackle; Shafer; Search for Dominant Structure; Differentiation -- Consolidation; Constraint Satisfaction Networks; Construction of Narratives

Dynamic Construction of Stimulus Values in the Ventromedial Prefrontal Cortex

Signals representing the value assigned to stimuli at the time of choice have been repeatedly observed in ventromedial prefrontal cortex (vmPFC). Yet it remains unknown how these value representations are computed from sensory and memory representations in more posterior brain regions. We used electroencephalography (EEG) while subjects evaluated appetitive and aversive food items to study how event-related responses modulated by stimulus value evolve over time. We found that value-related activity shifted from posterior to anterior, and from parietal to central to frontal sensors, across three major time windows after stimulus onset: 150–250 ms, 400–550 ms, and 700–800 ms. Exploratory localization of the EEG signal revealed a shifting network of activity moving from sensory and memory structures to areas associated with value coding, with stimulus value activity localized to vmPFC only from 400 ms onwards. Consistent with these results, functional connectivity analyses also showed a causal flow of information from temporal cortex to vmPFC. Thus, although value signals are present as early as 150 ms after stimulus onset, the value signals in vmPFC appear relatively late in the choice process, and seem to reflect the integration of incoming information from sensory and memory related regions

Preferences, Information, and Parental Choice Behavior in Public School Choice

The incentives and outcomes generated by public school choice depend to a large degree on parents' choice behavior. There is growing empirical evidence that low-income parents place lower weights on academics when choosing schools, but there is little evidence as to why. We use a field experiment in the Charlotte-Mecklenburg Public School district (CMS) to examine the degree to which information costs impact parental choices and their revealed preferences for academic achievement. We provided simplified information sheets on school average test scores or test scores coupled with estimated odds of admission to students in randomly selected schools along with their CMS school choice forms. We find that receiving simplified information leads to a significant increase in the average test score of the school chosen. This increase is equivalent to a doubling in the implicit preference for academic performance in a random utility model of school choice. Receiving information on odds of admission further increases the effect of simplified test score information on preferences for test scores among low-income families, but dampens the effect among higher-income families. Using within-family changes in choice behavior, we provide evidence that the estimated impact of simplified information is more consistent with lowered information costs than with suggestion or saliency.

Observational Learning: Evidence from a Randomized Natural Field Experiment

We present results about the effects of observing others' choices, called observational learning, on individuals' behavior and subjective well-being in the context of restaurant dining from a randomized natural field experiment. Our experimental design aims to distinguish observational learning effect from saliency effect (because observing others' choices also makes these choices more salient). We find that, depending on specifications, the demand for the top 5 dishes was increased by an average of about 13 to 18 percent when these popularity rankings were revealed to the customers; in contrast, being merely mentioned as some sample dishes did not significantly boost their demand. Moreover, we find that, consistent with theoretical predictions, some modest evidence that observational learning effect was stronger among infrequent customers. We also find that customers' subjective dining experiences were improved when presented with the information about the top choices by other consumers, but not when presented with the names of some sample dishes.