Applications are invited to fill one postdoctoral fellowship at the
Institute for Scientific Interchange Foundation (ISI) in Turin, Italy.
The candidate is expected to work in the stimulating area of
computational social science. We are particularly interested in
strengthening our emphasis on modeling and investigating language and
opinion dynamics in human and social systems.

A strong interest towards working in a highly interdisciplinary area
is an imperative requisite, the object of the postdoc involving issues
from different fields such as hard sciences (physics, mathematics and
computer science), linguistics, cognitive science and economics.  Good
modeling abilities and computer programming skills are appreciated,
but not mandatory.

The selected candidate will be able to design and perform research in
a range of directions going from data science and theoretical
modelling to construction of web-based experiments involving human
subjects. He/she will have the freedom and the charge to help shaping
the research lines of the group. Creative and motivated individuals
are therefore strongly encouraged to apply, regardless of their
specialties.

The ISI Foundation offers a stimulating environment with different
groups working in interdisciplinary research on complex systems. The
duration of the fellowship is one year, and it is renewable for a
second year. We are able to guarantee competitive salaries.

Applications including a CV, a list of publications, and a description
of past research and future research interests, should be sent to
Vittorio Loreto (vittorio.loreto@isi.it).  Applicants might be later
required to arrange for two letters of recommendation.

Applications will be considered upon their reception. Though we do not
fix a strict deadline we invite candidates to send their applications
by December the 15th, 2011.

Popularity: 4% [?]

“On the accuracy of language trees”

S. Pompei, V. Loreto and F. Tria

Abstract

Historical linguistics aims at inferring the most likely language phylogenetic tree starting from information concerning the evolutionary relatedness of languages. The available information are typically lists of homologous (lexical, phonological, syntactic) features or characters for many different languages: a set of parallel corpora whose compilation represents a paramount achievement in linguistics.
From this perspective the reconstruction of language trees is an example of inverse problems: starting from present, incomplete and often noisy, information, one aims at inferring the most likely past evo- lutionary history. A fundamental issue in inverse problems is the evaluation of the inference made. A standard way of dealing with this question is to generate data with artificial models in order to have full access to the evolutionary process one is going to infer. This procedure presents an intrinsic limitation: when dealing with real data sets, one typically does not know which model of evolution is the most suit- able for them. A possible way out is to compare algorithmic inference with expert classifications. This is the point of view we take here by conducting a thorough survey of the accuracy of reconstruction meth- ods as compared with the Ethnologue expert classifications. We focus in particular on state-of-the-art distance-based methods for phylogeny reconstruction using worldwide linguistic databases.
In order to assess the accuracy of the inferred trees we introduce and characterize two generalizations of standard definitions of distances between trees. Based on these scores we quantify the relative per- formances of the distance-based algorithms considered. Further we quantify how the completeness and the coverage of the available databases affect the accuracy of the reconstruction. Finally we draw some conclusions about where the accuracy of the reconstructions in historical linguistics stands and about the leading directions to improve it.

(see here for details)

Popularity: 3% [?]

The kick-off meeting of the new EveryAware project will take place in Torino on March 14-15th 2011 at the ISI Foundation

EveryAware

Enhance environmental awareness through social information technologies

There is now overwhelming evidence that the current organisation of our economies and societies is seriously damaging biological ecosystems and human living conditions in the very short term, with potentially catastrophic effects in the long term. The enforcement of novel policies may be triggered by a grassroot approach, with a key contribution from information and communication technologies (ICT). Nowadays low-cost sensing technologies allow the citizens to directly assess the state of the environment; social networking tools allow effective data and opinion collection and real-time information spreading processes. In addition, theoretical and modeling tools developed by physicists, computer scientists and sociologists have reached the maturity to analyse, interpret and visualize complex data sets. The proposed project intends to integrate all crucial phases (environmental monitoring, awareness enhancement, behavioural change) in the management of the environment in a unified framework, by creating a new technological platform combining sensing technologies, networking applications and data-processing tools; the Internet and the existing mobile communication networks will provide the infrastructure hosting such a platform, allowing its replication in different times and places. Case studies concerning different numbers of participants will test the scalability of the platform, aiming at involving as many citizens as possible leveraging on the low cost and high usability of the sensing devices. The integration of participatory sensing with the monitoring of subjective opinions is novel and crucial, as it exposes the mechanisms by which the local perception of an environmental issue, corroborated by quantitative data, evolves into socially-shared opinions, eventually driving behavioural changes. Enabling this level of transparency critically allows an effective communication of desirable environmental strategies to the general public and to institutional agencies.

Partners:

FONDAZIONE ISTITUTO PER L’INTERSCAMBIO SCIENTIFICO (ISI) Italy
GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER Germany
UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA Italy
VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK N.V. (VITO) Belgium
UNIVERSITY COLLEGE LONDON United Kingdom

Popularity: 3% [?]

Aging in language dynamics
A. Mukherjee, F. Tria, A. Baronchelli, A. Puglisi and V. Loreto,
PLoS ONE, Volume 6, Issue 2, e16677 (2011).
[PDF]

Abstract
Human languages evolve continuously, and a puzzling problem is how to reconcile the apparent robustness of most of the deep linguistic structures we use with the evidence that they undergo possibly slow, yet ceaseless, changes. Is the state in which we observe languages today closer to what would be a dynamical attractor with statistically stationary properties or rather closer to a non-steady state slowly evolving in time? Here we address this question in the framework of the emergence of shared linguistic categories in a population of individuals interacting through language games. The observed emerging asymptotic categorization, which has been previously tested – with success – against experimental data from human languages, corresponds to a metastable state where global shifts are always possible but progressively more unlikely and the response properties depend on the age of the system. This aging mechanism exhibits striking quantitative analogies to what is observed in the statistical mechanics of glassy systems. We argue that this can be a general scenario in language dynamics where shared linguistic conventions would not emerge as attractors, but rather as metastable states.

Popularity: 3% [?]

Our PNAS paper Modeling the emergence of universality in color naming patterns by A. Baronchelli, T. Gong, A. Puglisi and V. Loreto, has been featured in Physics Today.

Popularity: 3% [?]

Statistical physics of social dynamics
C. Castellano, S. Fortunato, V. Loreto
Rev. Mod. Phys. 81, 591-646 (2009)

Popularity: 2% [?]

Modeling the emergence of universality in color naming patterns
A. Baronchelli, T. Gong, A. Puglisi and V. Loreto
Published (just online, at the moment) in PNAS. *Featured in: spektrumdirect (in German)

Popularity: 3% [?]