19 Feb

Carlos Lemos – new PhD thesis On Agent-Based Modelling of Large Scale Conflict Against a Central Authority: from Mechanisms to Complex Behaviour


Carlos Lemos presented his PhD thesis on the 16th of December 2016, at ISCTE-IUL, entitled “On Agent-Based Modelling of Large Scale Conflict Against a Central Authority: from Mechanisms to Complex Behaviour”. The jury was composed by Ernesto Costa, Francisco Santos, Pedro Magalhães, Luis Antunes, Jorge Louçã, Rui Lopes (supervisor), and Helder Coelho (co-supervisor).

Abstract:
In this work, an Agent-Based model of large scale conflict against a central authority was developed. The model proposed herein is an extension of Epstein’s Agent-Based model of civil violence, in which new mechanisms such as deprivation-dependent hardship, generalised vanishing of the risk perception (`massive fear loss’) below a critical ratio between deterrence and `group support’, legitimacy feedback, network influences and `mass enthusiasm’ (contagion) were implemented. The model was explored a set of computer experiments and the results compared with statistical analyses of events in the “Arab Spring”.

The main contributions of the present work for understanding how mechanisms of large scale conflict lead to complex behaviour were (i ) a quantitative description of the impact of the “Arab Spring” in several countries focused on complexity issues such as peaceful vs violent, spontaneous vs organized, and patterns of size, duration and recurrence of conflict events; (ii ) the explanation of the relationship between the estimated arrest probability and the size of rebellion peaks in Epstein’s model; (iii ) a new form of the estimated arrest probability with a mechanism of `massive fear loss’; (iv ) the derivation of a relationship between the legitimacy and action threshold for complex solutions to occur with both low and high values of the legitimacy; (v) a simple representation of political vs economic deprivation with a parameter which controls the `sensitivity’ to value; (vi ) the effect of legitimacy feedback; and (vii ) the effect of network influences on the stability of the solutions.



08 Apr

António Fonseca: new PhD thesis explaining the mechanisms of popularity

António Fonseca presented his PhD thesis on the 6th of April 2015, at ISCTE-IUL, entitled “Mecanismos de Popularidade e Difusão de Informação em Redes Sociais” (in Portuguese). The jury was composed by Ricardo Fonseca, Helder Coelho, Ernesto Costa, António Firmino da Costa, Luis Antunes, Pedro Lind, and Jorge Louçã (supervisor).

Abstract:
This research investigates the mechanisms of formation of popularity in society, assuming that popularity is generated though processes of information diffusion.
A static model of the distribution of popularity by various entities is here proposed and validated. It is demonstrated that it ts a probabilistic distribution of exponential growth of popularity. Complementarily, two dynamic models are proposed, representing the evolution of popularity. The first model, named Rami cation Model, is an exogenous impact model tracing the pro le of the typical evolution of popularity triggered by a single external event. The second one, called Epidemic Model, represents the process of popularity formation when arising from internal dissemination of messages within a community. All models are validated with experimental data.
A case study, concerning communication data collected during the
2011 elections in Portugal, allowed measuring the influence of popularity, generated through Social Communication, on opinion dynamics. Two sociophysics opinion dynamics models, based on the Brownian Model of Influence, and on the Social Impact Theory, were used to represent theoretically and quantitatively the dynamics of public debate in this period.
One of the most relevant results of the research concerns the understanding that the long term increasing of some entity’s popularity, as a result of communication processes between individuals, is independent from the entity subjective qualities, and it depends mainly from the communication processes being used.

17 Mar

David Rodrigues: new PhD thesis concerning the structure of news

David Rodrigues presented his PhD thesis on March 17th 2014, at 14.00 p.m, at ISCTE-IUL, entitled “Reading the News Through its Structure: New Hybrid Connectivity Based Approaches”. The jury was composed by Tanya Araújo, José Feliz Costa, Jeffrey Johnson, Rui Lopes, Helder Coelho, and Jorge Louçã (supervisor).

Abstract:
In this thesis a solution for the problem of identifying the structure of news published by online newspapers is presented. This problem requires new approaches and algorithms that are capable of dealing with the massive number of online publications in existence (and that will grow in the future). The fact that news documents present a high degree of interconnection makes this an interesting and hard problem to solve. The identification of the structure of the news is accomplished both by descriptive methods that expose the dimensionality of the relations between different news, and by clustering the news into topic groups. To achieve this analysis this integrated whole was studied using different perspectives and approaches. In the identification of news clusters and structure, and after a preparatory data collection phase, where several online newspapers from different parts of the globe were collected, two newspapers were chosen in particular: the Portuguese daily newspaper Público and the British newspaper The Guardian.
In the first case, it was shown how information theory (namely variation of information) combined with adaptive networks was able to identify topic clusters in the news published by the Portuguese online newspaper Público.
In the second case, the structure of news published by the British newspaper The Guardian is revealed through the construction of time series of news clustered by a kmeans process. After this approach an unsupervised algorithm, that filters out irrelevant news published online by taking into consideration the connectivity of the news labels entered by the journalists, was developed. This novel hybrid technique is based on Q analysis for the construction of the filtered network followed by a clustering technique to identify the topical clusters. Presently this work uses a modularity optimisation clustering technique but this step is general enough that other hybrid approaches can be used without losing generality. A novel second order swarm intelligence algorithm based on Ant Colony Systems was developed for the travelling salesman problem that is consistently better than the traditional benchmarks. This algorithm is used to construct Hamiltonian paths over the news published using the eccentricity of the different documents as a measure of distance. This approach allows for an easy navigation between published stories that is dependent on the connectivity of the underlying structure.
The results presented in this work show the importance of taking topic detection in large corpora as a multitude of relations and connectivities that are not in a static state. They also influence the way of looking at multi-dimensional ensembles, by showing that the inclusion of the high dimension connectivities gives better results to solving a particular problem as was the case in the clustering problem of the news published online.

The complete document is available here.

Following his Master and PhD in Complexity Sciences in Lisbon, David Rodrigues is now research Fellow at The Open University, Milton Keynes, United Kingdom – website here.