28,349 research outputs found
Towards a Model of Understanding Social Search
Search engine researchers typically depict search as the solitary activity of
an individual searcher. In contrast, results from our critical-incident survey
of 150 users on Amazon's Mechanical Turk service suggest that social
interactions play an important role throughout the search process. Our main
contribution is that we have integrated models from previous work in
sensemaking and information seeking behavior to present a canonical social
model of user activities before, during, and after search, suggesting where in
the search process even implicitly shared information may be valuable to
individual searchers.Comment: Presented at 1st Intl Workshop on Collaborative Information Seeking,
2008 (arXiv:0908.0583
Fast kinetic Monte Carlo simulation of strained heteroepitaxy in three dimensions
Accelerated algorithms for simulating the morphological evolution of strained
heteroeptiaxy based on a ball and spring lattice model in three dimensions are
explained. We derive exact Green's function formalisms for boundary values in
the associated lattice elasticity problems. The computational efficiency is
further enhanced by using a superparticle surface coarsening approximation.
Atomic hoppings simulating surface diffusion are sampled using a multi-step
acceptance-rejection algorithm. It utilizes quick estimates of the atomic
elastic energies from extensively tabulated values modulated by the local
strain. A parameter controls the compromise between accuracy and efficiency of
the acceptance-rejection algorithm.Comment: 10 pages, 4 figures, submitted to Proceedings of Barrett Lectures
2007, Journal of Scientific Computin
Financing Constraints and the Family Farm: How do Families React?
This paper explores the idea that off-farm income is used for investment in farm assets. Using Alabama farm data for the 1997-2004 period, we find that farm investment is more sensitive to off-farm than to on-farm income, and that this sensitivity is stronger for farms with sales less than $250,000.Farm Management, Q12, Q14, G11,
Defining and Estimating Intervention Effects for Groups that will Develop an Auxiliary Outcome
It has recently become popular to define treatment effects for subsets of the
target population characterized by variables not observable at the time a
treatment decision is made. Characterizing and estimating such treatment
effects is tricky; the most popular but naive approach inappropriately adjusts
for variables affected by treatment and so is biased. We consider several
appropriate ways to formalize the effects: principal stratification,
stratification on a single potential auxiliary variable, stratification on an
observed auxiliary variable and stratification on expected levels of auxiliary
variables. We then outline identifying assumptions for each type of estimand.
We evaluate the utility of these estimands and estimation procedures for
decision making and understanding causal processes, contrasting them with the
concepts of direct and indirect effects. We motivate our development with
examples from nephrology and cancer screening, and use simulated data and real
data on cancer screening to illustrate the estimation methods.Comment: Published at http://dx.doi.org/10.1214/088342306000000655 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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