376 research outputs found
Controlling Fairness and Bias in Dynamic Learning-to-Rank
Rankings are the primary interface through which many online platforms match
users to items (e.g. news, products, music, video). In these two-sided markets,
not only the users draw utility from the rankings, but the rankings also
determine the utility (e.g. exposure, revenue) for the item providers (e.g.
publishers, sellers, artists, studios). It has already been noted that
myopically optimizing utility to the users, as done by virtually all
learning-to-rank algorithms, can be unfair to the item providers. We,
therefore, present a learning-to-rank approach for explicitly enforcing
merit-based fairness guarantees to groups of items (e.g. articles by the same
publisher, tracks by the same artist). In particular, we propose a learning
algorithm that ensures notions of amortized group fairness, while
simultaneously learning the ranking function from implicit feedback data. The
algorithm takes the form of a controller that integrates unbiased estimators
for both fairness and utility, dynamically adapting both as more data becomes
available. In addition to its rigorous theoretical foundation and convergence
guarantees, we find empirically that the algorithm is highly practical and
robust.Comment: First two authors contributed equally. In Proceedings of the 43rd
International ACM SIGIR Conference on Research and Development in Information
Retrieval 202
How simple rules determine pedestrian behavior and crowd disasters
With the increasing size and frequency of mass events, the study of crowd
disasters and the simulation of pedestrian flows have become important research
areas. Yet, even successful modeling approaches such as those inspired by
Newtonian force models are still not fully consistent with empirical
observations and are sometimes hard to calibrate. Here, a novel cognitive
science approach is proposed, which is based on behavioral heuristics. We
suggest that, guided by visual information, namely the distance of obstructions
in candidate lines of sight, pedestrians apply two simple cognitive procedures
to adapt their walking speeds and directions. While simpler than previous
approaches, this model predicts individual trajectories and collective patterns
of motion in good quantitative agreement with a large variety of empirical and
experimental data. This includes the emergence of self-organization phenomena,
such as the spontaneous formation of unidirectional lanes or stop-and-go waves.
Moreover, the combination of pedestrian heuristics with body collisions
generates crowd turbulence at extreme densities-a phenomenon that has been
observed during recent crowd disasters. By proposing an integrated treatment of
simultaneous interactions between multiple individuals, our approach overcomes
limitations of current physics-inspired pair interaction models. Understanding
crowd dynamics through cognitive heuristics is therefore not only crucial for a
better preparation of safe mass events. It also clears the way for a more
realistic modeling of collective social behaviors, in particular of human
crowds and biological swarms. Furthermore, our behavioral heuristics may serve
to improve the navigation of autonomous robots.Comment: Article accepted for publication in PNA
Quantifying Social Influence in an Online Cultural Market
We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process–the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role
Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions
In online communities, antisocial behavior such as trolling disrupts
constructive discussion. While prior work suggests that trolling behavior is
confined to a vocal and antisocial minority, we demonstrate that ordinary
people can engage in such behavior as well. We propose two primary trigger
mechanisms: the individual's mood, and the surrounding context of a discussion
(e.g., exposure to prior trolling behavior). Through an experiment simulating
an online discussion, we find that both negative mood and seeing troll posts by
others significantly increases the probability of a user trolling, and together
double this probability. To support and extend these results, we study how
these same mechanisms play out in the wild via a data-driven, longitudinal
analysis of a large online news discussion community. This analysis reveals
temporal mood effects, and explores long range patterns of repeated exposure to
trolling. A predictive model of trolling behavior shows that mood and
discussion context together can explain trolling behavior better than an
individual's history of trolling. These results combine to suggest that
ordinary people can, under the right circumstances, behave like trolls.Comment: Best Paper Award at CSCW 201
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Effect of Succimer on Growth of Preschool Children with Moderate Blood Lead Levels.
Growth deficits associated with lead exposure might be ameliorated by chelation. We examined the effect of succimer on growth in 780 children 12-33 months old who had blood lead levels of 20-44 microg/dL and were randomized to receive up to three 26-day courses of succimer or placebo in a multicenter, double-blind trial. The difference in changes in weight and height between succimer and placebo groups at 1-34 months was calculated by fitting cubic splines. The difference in height change in children on succimer compared with placebo was -0.27 cm [95% confidence interval (95% CI), -0.42 to -0.11] from baseline to 9 months, when 99% of children had completed treatment, and -0.43 cm (95% CI, -0.77 to -0.09) during 34 months of follow-up. Similar differences in weight gain were not statistically significant. Although succimer lowers blood lead in moderately lead-poisoned children, it does not have a beneficial effect on growth and may have an adverse effect.Other Research Uni
Quantum Breaking of Elastic String
Breaking of an atomic chain under stress is a collective many-particle
tunneling phenomenon. We study classical dynamics in imaginary time by using
conformal mapping technique, and derive an analytic formula for the probability
of breaking. The result covers a broad temperature interval and interpolates
between two regimes: tunneling and thermal activation. Also, we consider the
breaking induced by an ultrasonic wave propagating in the chain, and propose to
observe it in an STM experiment.Comment: 8 pages, RevTeX 3.0, Landau Institute preprint 261/643
Bias reduction in traceroute sampling: towards a more accurate map of the Internet
Traceroute sampling is an important technique in exploring the internet
router graph and the autonomous system graph. Although it is one of the primary
techniques used in calculating statistics about the internet, it can introduce
bias that corrupts these estimates. This paper reports on a theoretical and
experimental investigation of a new technique to reduce the bias of traceroute
sampling when estimating the degree distribution. We develop a new estimator
for the degree of a node in a traceroute-sampled graph; validate the estimator
theoretically in Erdos-Renyi graphs and, through computer experiments, for a
wider range of graphs; and apply it to produce a new picture of the degree
distribution of the autonomous system graph.Comment: 12 pages, 3 figure
Implementation of Web-Based Respondent-Driven Sampling among Men who Have Sex with Men in Vietnam
Objective: Lack of representative data about hidden groups, like men who have
sex with men (MSM), hinders an evidence-based response to the HIV epidemics.
Respondent-driven sampling (RDS) was developed to overcome sampling challenges
in studies of populations like MSM for which sampling frames are absent.
Internet-based RDS (webRDS) can potentially circumvent limitations of the
original RDS method. We aimed to implement and evaluate webRDS among a hidden
population.
Methods and Design: This cross-sectional study took place 18 February to 12
April, 2011 among MSM in Vietnam. Inclusion criteria were men, aged 18 and
above, who had ever had sex with another man and were living in Vietnam.
Participants were invited by an MSM friend, logged in, and answered a survey.
Participants could recruit up to four MSM friends. We evaluated the system by
its success in generating sustained recruitment and the degree to which the
sample compositions stabilized with increasing sample size.
Results: Twenty starting participants generated 676 participants over 24
recruitment waves. Analyses did not show evidence of bias due to ineligible
participation. Estimated mean age was 22 year and 82% came from the two large
metropolitan areas. 32 out of 63 provinces were represented. The median number
of sexual partners during the last six months was two. The sample composition
stabilized well for 16 out of 17 variables.
Conclusion: Results indicate that webRDS could be implemented at a low cost
among Internet-using MSM in Vietnam. WebRDS may be a promising method for
sampling of Internet-using MSM and other hidden groups.
Key words: Respondent-driven sampling, Online sampling, Men who have sex with
men, Vietnam, Sexual risk behavio
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