Measuring Online Social Bubbles

Social media have quickly become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view, and even foster polarization and misinformation. Here we explore and validate this hypothesis quantitatively for the first time, at the collective and individual levels, by mining three massive datasets of web traffic, search logs, and Twitter posts. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to search. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at the collective and individual level. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside "social bubbles". Our results could lead to a deeper understanding of how technology biases our exposure to new information

Search for nucleon decay via modes favored by supersymmetric grand unification models in Super-Kamiokande-I

We report the results for nucleon decay searches via modes favored by supersymmetric grand unified models in Super-Kamiokande. Using 1489 days of full Super-Kamiokande-I data, we searched for $p \to \bar{\nu} K^+$, $n \to \bar{\nu} K^0$, $p \to \mu^+ K^0$ and $p \to e^+ K^0$ modes. We found no evidence for nucleon decay in any of these modes. We set lower limits of partial nucleon lifetime 2.3$\times10^{33}$, 1.3$\times10^{32}$, 1.3$\times10^{33}$ and 1.0$\times10^{33}$ years at 90% confidence level for $p \to \bar{\nu} K^+$, $n \to \bar{\nu} K^0$, $p \to \mu^+ K^0$ and $p \to e^+ K^0$ modes, respectively. These results give a strong constraint on supersymmetric grand unification models.Comment: 14 pages, 13 figure

The time course of visual foraging in the lifespan: Spatial scanning, organization search, and target processing

Visual foraging is a variant of visual search, consisting of searching for an undetermined number of targets among distractors (e.g., looking for various LEGO pieces in a box). Under non-exhaustive tasks, the observer scans the display, picking those targets needed, not necessarily all of them, before leaving the search. To understand how the organization of such natural foraging tasks works, several measures of spatial scanning and organization have been proposed in the exhaustive foraging literature: best-r, intertarget distances, PAO, and target intersections. In the present study, we apply these measures and new Bayesian indexes to determine how the time course of visual foraging is organized in a dynamic non-exhaustive paradigm. In a large sample of observers (279 participants, 4–25 years old), we compare feature and conjunction foraging and explore how factors like set size and time course, not previously tested in exhaustive foraging, might afect search organization in non-exhaustive dynamic tasks. The results replicate previous fndings showing younger observers’ searching being less organized, feature conditions being more organized than conjunction conditions, and organization leading to a more efective search. Interestingly, observers tend to be less organized as set size increases, and search is less organized within a patch as it advances in time: Search organization decreases when search termination is coming, suggesting organization measures as potential clues to understand quitting rules in search. Our results highlight the importance of studying search organization in foraging as a critical source of understanding complex cognitive processes in visual searchOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the Research Grant Project PSI2015-69358-R (MINECO/FEDER) “Ministerio de Economía y Competitividad” (MINECO), and “Fondo Europeo de Desarrollo Regional” (FEDER), given to Beatriz Gil-Gómez de Liaño as PI at Universidad Autónoma de Madrid. Also, part of the research of this study was done thanks to the Fulbright Commission, and the European Union’s Horizon 2020 research and innovation program, Marie Sklodowska-Curie Actions, under Grant FORAGEKID 793268, also granted to Beatriz Gil-Gómez de Liaño at the University of Cambridge, Universidad Complutense de Madrid, and BWH-Harvard Medical Schoo

Timing Attention: from Reaction Time to Models of Visual Attention

Models of visual attention have been widely proposed over the last two decades. Researchers in different disciplines, such as psychology and engineering, are interested in these models in order to understand human perceptual mechanisms and/or build algorithms which mimic the attentional processes for some applications (e.g. robotics). In this dissertation I modeled the effect of learning experiences on attentional guidance. The presented model is an algorithmic-level model which links display inputs to the participants' reaction times. This dissertation consists of three studies. In the first study the role of selection history -as the effect of learning from the practice phase of the experiment on the main phase- is investigated. I also tested dimension-level (e.g. color and shape) and feature-level (e.g. blue and red) selection histories. The results showed the version of the model which includes selection history (on feature-level), beside stimulus-driven (bottom-up) and goal-driven (top-down) control mechanisms, is best suited for a quantitative description of the participants' reaction times. In the second study, I investigated the importance of intertrial priming -the effect of a previous trial on the current one- as well as the importance of each feature map (color, shape or orientation) in the model predictions. It was shown that by including the effect of intertrial priming a better description of the behavioral database can be achieved. Additionally, excluding any of the feature maps deteriorates the model predictions. In the third study, I proposed a model to decompose reaction times -into decision and sensorimotor components- as a prerequisite of RT modeling. This study will help us introduce more accurate attention models. Furthermore, it can support cognitive studies to better investigate the effect of certain factors (e.g. age and mental disorders) on motor system vs. decision making. The proposed attention model (in the first and the second study) is one of the first models that includes the selection history effect on guiding attention. This model can capture the between-group differences where each group of participants had a different learning experience. The model considers total reaction times of each participant. But attention can influence reaction times by affecting different cognitive processes. The third study introduces a method which helps us look at each process (and its relevant reaction time component) independently

Investigating Distractor-induced Effects in Visual Search Utilizing Eye-Tracking

The present study provides an insightful look into the effects of distractors using behavioral and eye-tracking measures. In this study, two eye-tracking experiments utilizing a feature search task were conducted to investigate the distractor-induced early quitting effect with a target prevalence of 50% rather than the 100% target prevalence typical of attentional capture studies. In Experiment 1, two independent variables of target (present/absent) and distractor (target/present) were examined with behavioral measures (accuracy and response time) as well as eye-tracking methods (total fixations, total fixation durations, and total distractor saccade percentages). Distractors were categorized as salient due to their red color, larger size, and delayed onset of 100 milliseconds after the presentation of other stimuli. In Experiment 2, all methodology was replicated with the exception that the salient item was occasionally the target. Experiment 1 demonstrated a robust replication of the distractor-induced early quitting effect on measures of accuracy and response time. Participants also fixated on fewer objects in the visual search task on distractor-present when they were most susceptible to distractor-induced early quitting. Additionally, participants tended to avoid making a saccade to the distractor on distractor-present trials. Experiment 2 demonstrated replication of data on participants’ accuracy, response time on target-present trials, and total fixations on target-present trials. Additionally, participants reported the opposite effect on total distractor saccade percentage, as participants had higher percentages of saccades to the distractor on distractor-present trials. However, other measures were not replicated

Rethinking Attentional Habits

Attentional habits acquired by visual statistical learning cause enduring biases toward specific locations. These habits, driven by recent search history, are thought to be independent of both goal-directed and stimulus-driven attentional mechanisms. This theoretical claim is based on three characteristics that these habits apparently exhibit, that is, they are inflexible, implicit, and efficient. We review methodological limitations in previous studies and briefly describe recent results that challenge this new framework. We conclude that it might be premature to assume that attentional habits are based on a special search history process that differs from the two traditionally recognized attentional mechanisms

Scanpath Eye Movements during Visual Mental Imagery in a Simulated Hemianopia Paradigm

Several studies have shown that eye movements (EM) are functionally involved in visual imagery. In this study we investigate the impact of a simulated homonymous hemianopia paradigm (SH) with and without foveal masking on scanpath eye movements during visual mental imagery. EM of twenty subjects were recorded under SH condition during viewing and subsequent visual imagery of complex pictures. Using evaluated string editing methods viewing and imagery scanpaths were compared. Our results show that scanpath EM are involved in visual mental imagery and reflect the picture content even under SH. In contrast, additional foveal masking significantly reduces the similarity between viewing and imagery scanpath. This points toward a detrimental effect of foveal masking on subsequent visual imagery performance

Delayed onsets are not necessary for generating distractor quitting thresholds effects in visual search

Acknowledgments This research is supported by a National Sciences and Engineering Research Council of Canada grant awarded to J.P (2016-06359). Open Access funding enabled and organized by CAUL and its Member InstitutionsPeer reviewedPublisher PD

How Principal Investigators’ Commercial Experience Influences Technology Transfer and Market Impacts

Businesses can benefit from university–industry collaborations, yet they rarely take full advantage of them. Scientists who serve as principal investigators (PIs) act as the nucleus of university–industry collaborations and partner with industry to cocreate value. We conducted a case study of PIs at publicly funded research universities, institutes, and organizations in Ireland to explore how having commercial experience influences how PIs approach technology transfer and how they develop new business models, products, and services. We learned that PIs’ prior commercial experience influences how they approach their research, project work, and project selection and affects how they commercialize knowledge and outputs from their scientific research––that is, patents, licences, agreements, etc.––throughout the project’s life cycle. In university– industry collaborations, PIs’ commercial experience can impact industry partners’ attempts to realize technology transfer and market impacts