175 research outputs found
Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population
Online genealogy datasets contain extensive information about millions of
people and their past and present family connections. This vast amount of data
can assist in identifying various patterns in human population. In this study,
we present methods and algorithms which can assist in identifying variations in
lifespan distributions of human population in the past centuries, in detecting
social and genetic features which correlate with human lifespan, and in
constructing predictive models of human lifespan based on various features
which can easily be extracted from genealogy datasets.
We have evaluated the presented methods and algorithms on a large online
genealogy dataset with over a million profiles and over 9 million connections,
all of which were collected from the WikiTree website. Our findings indicate
that significant but small positive correlations exist between the parents'
lifespan and their children's lifespan. Additionally, we found slightly higher
and significant correlations between the lifespans of spouses. We also
discovered a very small positive and significant correlation between longevity
and reproductive success in males, and a small and significant negative
correlation between longevity and reproductive success in females. Moreover,
our machine learning algorithms presented better than random classification
results in predicting which people who outlive the age of 50 will also outlive
the age of 80.
We believe that this study will be the first of many studies which utilize
the wealth of data on human populations, existing in online genealogy datasets,
to better understand factors which influence human lifespan. Understanding
these factors can assist scientists in providing solutions for successful
aging
Reaction to New Security Threat Class
Each new identified security threat class triggers new research and
development efforts by the scientific and professional communities. In this
study, we investigate the rate at which the scientific and professional
communities react to new identified threat classes as it is reflected in the
number of patents, scientific articles and professional publications over a
long period of time. The following threat classes were studied: Phishing; SQL
Injection; BotNet; Distributed Denial of Service; and Advanced Persistent
Threat. Our findings suggest that in most cases it takes a year for the
scientific community and more than two years for industry to react to a new
threat class with patents. Since new products follow patents, it is reasonable
to expect that there will be a window of approximately two to three years in
which no effective product is available to cope with the new threat class
Quantitative Analysis of Genealogy Using Digitised Family Trees
Driven by the popularity of television shows such as Who Do You Think You
Are? many millions of users have uploaded their family tree to web projects
such as WikiTree. Analysis of this corpus enables us to investigate genealogy
computationally. The study of heritage in the social sciences has led to an
increased understanding of ancestry and descent but such efforts are hampered
by difficult to access data. Genealogical research is typically a tedious
process involving trawling through sources such as birth and death
certificates, wills, letters and land deeds. Decades of research have developed
and examined hypotheses on population sex ratios, marriage trends, fertility,
lifespan, and the frequency of twins and triplets. These can now be tested on
vast datasets containing many billions of entries using machine learning tools.
Here we survey the use of genealogy data mining using family trees dating back
centuries and featuring profiles on nearly 7 million individuals based in over
160 countries. These data are not typically created by trained genealogists and
so we verify them with reference to third party censuses. We present results on
a range of aspects of population dynamics. Our approach extends the boundaries
of genealogy inquiry to precise measurement of underlying human phenomena
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