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Simplifying Complexity
ecology and complexity science
Curated by Eric L Berlow
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Future impact: Predicting scientific success

To construct a formula to predict future h-index, we assembled a large data set and analysed it using machine-learning techniques. Our initial sample from academictree.org — a crowd-sourced website listing scientists' mentors, trainees and collaborators — contains the names and institutions of about 34,800 neuroscientists, 2,000 scientists studying the fruitfly Drosophila and 1,300 evolutionary researchers. We matched these authors to records in Scopus, an online database of academic papers and citation data. We restricted our analysis to authors who had accrued an h-index greater than 4 (to exclude inactive scientists); to publications after 1995 (because electronic records are sparse before then); to authors who had published their first manuscript in the past 5–12 years; and to authors who were identifiable in Scopus.

 

Future impact: Predicting scientific success

Daniel E. Acuna, Stefano Allesina & Konrad P. Kording

Nature 489, 201–202 (13 September 2012) http://dx.doi.org/10.1038/489201a


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Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread

The dynamics of infectious diseases caused by pathogens transmissible from human to human strongly depends on contact patterns between individuals. High quality observational data on contact patterns, usually presented in the form of age-specific contact matrices, are difficult to gather and are currently available only for few countries worldwide. Here we propose a computational approach, based on the simulation of a virtual society of agents, allowing the estimation of contact patterns by age for 26 European countries.

 

Fumanelli L, Ajelli M, Manfredi P, Vespignani A, Merler S (2012) Inferring the Structure of Social Contacts from Demographic Data in the Analysis of Infectious Diseases Spread. PLoS Comput Biol 8(9): e1002673. http://dx.doi.org/10.1371/journal.pcbi.1002673


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Earth's Last Unexplored Wilderness: Your Very Own Home

Earth's Last Unexplored Wilderness: Your Very Own Home | Simplifying Complexity | Scoop.it

Biologists are starting to explore the woolly ecosystems in our homes and hospitals, and figuring out how they can make us sick or keep us healthy.


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Ten Simple Rules for Online Learning

The success of online courseware such as that offered by the Massachusetts Institute of Technology (MIT) (http://ocw.mit.edu) and now by many other institutions, together with a plethora of recent announcements of major new initiatives in this arena such as Coursera (https://www.coursera.org), Udacity (http://www.udacity.com), and the Harvard-MIT partnership edX (http://www.edxonline.org), have made it clear that online learning has reached a tipping point. Many signs point to the possibility in the near future of getting a quality, university-level education at a distance, and for free. As exciting as this prospect may be, it behooves online students to follow a few simple rules for getting the most out of the experience, while being realistic in their expectations, as outlined below.

 

Searls DB (2012) Ten Simple Rules for Online Learning. PLoS Comput Biol 8(9): e1002631. http://dx.doi.org/10.1371/journal.pcbi.1002631


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A 61-million-person experiment in social influence and political mobilization - strong social ties matter

A 61-million-person experiment in social influence and political mobilization - strong social ties matter | Simplifying Complexity | Scoop.it

Human behaviour is thought to spread through face-to-face social networks, but it is difficult to identify social influence effects in observational studies, and it is unknown whether online social networks operate in the same way. Here we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 US congressional elections. The results show that the messages directly influenced political self-expression, information seeking and real-world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them but also the users’ friends, and friends of friends. The effect of social transmission on real-world voting was greater than the direct effect of the messages themselves, and nearly all the transmission occurred between ‘close friends’ who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real-world behaviour in human social networks.

 

A 61-million-person experiment in social influence and political mobilization

Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer, Cameron Marlow, Jaime E. Settle & James H. Fowler

Nature 489, 295–298 (13 September 2012) http://dx.doi.org/10.1038/nature11421


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BBC Documentary Climate Wars Episode 2

A great homework video for the IB Biology Ecology Topic (links to ToK).
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