100 research outputs found
Modeling self-sustained activity cascades in socio-technical networks
The ability to understand and eventually predict the emergence of information
and activation cascades in social networks is core to complex socio-technical
systems research. However, the complexity of social interactions makes this a
challenging enterprise. Previous works on cascade models assume that the
emergence of this collective phenomenon is related to the activity observed in
the local neighborhood of individuals, but do not consider what determines the
willingness to spread information in a time-varying process. Here we present a
mechanistic model that accounts for the temporal evolution of the individual
state in a simplified setup. We model the activity of the individuals as a
complex network of interacting integrate-and-fire oscillators. The model
reproduces the statistical characteristics of the cascades in real systems, and
provides a framework to study time-evolution of cascades in a state-dependent
activity scenario.Comment: 5 pages, 3 figure
The Contagion Effects of Repeated Activation in Social Networks
Demonstrations, protests, riots, and shifts in public opinion respond to the
coordinating potential of communication networks. Digital technologies have
turned interpersonal networks into massive, pervasive structures that
constantly pulsate with information. Here, we propose a model that aims to
analyze the contagion dynamics that emerge in networks when repeated activation
is allowed, that is, when actors can engage recurrently in a collective effort.
We analyze how the structure of communication networks impacts on the ability
to coordinate actors, and we identify the conditions under which large-scale
coordination is more likely to emerge.Comment: Submitted for publicatio
Using Twitter to Understand Public Interest in Climate Change: The case of Qatar
Climate change has received an extensive attention from public opinion in the
last couple of years, after being considered for decades as an exclusive
scientific debate. Governments and world-wide organizations such as the United
Nations are working more than ever on raising and maintaining public awareness
toward this global issue. In the present study, we examine and analyze Climate
Change conversations in Qatar's Twittersphere, and sense public awareness
towards this global and shared problem in general, and its various related
topics in particular. Such topics include but are not limited to politics,
economy, disasters, energy and sandstorms. To address this concern, we collect
and analyze a large dataset of 109 million tweets posted by 98K distinct users
living in Qatar -- one of the largest emitters of CO2 worldwide. We use a
taxonomy of climate change topics created as part of the United Nations Pulse
project to capture the climate change discourse in more than 36K tweets. We
also examine which topics people refer to when they discuss climate change, and
perform different analysis to understand the temporal dynamics of public
interest toward these topics.Comment: Will appear in the proceedings of the International Workshop on
Social Media for Environment and Ecological Monitoring (SWEEM'16
The joint influence of competition and mutualism on the biodiversity of mutualistic ecosystems
Relations among species in ecosystems can be represented by complex networks
where both negative (competition) and positive (mutualism) interactions are
concurrently present. Recently, it has been shown that many ecosystems can be
cast into mutualistic networks, and that nestedness reduces effective
inter-species competition, thus facilitating mutually beneficial interactions
and increasing the number of coexisting species or the biodiversity. However,
current approaches neglect the structure of inter-species competition by
adopting a mean-field perspective that does not deal with competitive
interactions properly. Here, we introduce a framework based on the concept of
multilayer networks, which naturally accounts for both mutualism and
competition. Hence, we abandon the mean field hypothesis and show, through a
dynamical population model and numerical simulations, that there is an
intricate relation between competition and mutualism. Specifically, we show
that when all interactions are taken into account, mutualism does not have the
same consequences on the evolution of specialist and generalist species. This
leads to a non-trivial profile of biodiversity in the parameter space of
competition and mutualism. Our findings emphasize how the simultaneous
consideration of positive and negative interactions can contribute to our
understanding of the delicate trade-offs between topology and biodiversity in
ecosystems and call for a reconsideration of previous findings in theoretical
ecology, as they may affect the structural and dynamical stability of
mutualistic systems.Comment: 11 pages. Submitted for publicatio
Antagonistic Structural Patterns in Complex Networks
Identifying and explaining the structure of complex networks at different
scales has become an important problem across disciplines. At the mesoscale,
modular architecture has attracted most of the attention. At the macroscale,
other arrangements --e.g. nestedness or core-periphery-- have been studied in
parallel, but to a much lesser extent. However, empirical evidence increasingly
suggests that characterizing a network with a unique pattern typology may be
too simplistic, since a system can integrate properties from distinct
organizations at different scales. Here, we explore the relationship between
some of those organizational patterns: two at the mesoscale (modularity and
in-block nestedness); and one at the macroscale (nestedness). We analytically
show that nestedness can be used to provide approximate bounds for modularity,
with exact results in an idealized scenario. Specifically, we show that
nestedness and modularity are antagonistic. Furthermore, we evince that
in-block nestedness provides a parsimonious transition between nested and
modular networks, taking properties of both. Far from a mere theoretical
exercise, understanding the boundaries that discriminate each architecture is
fundamental, to the extent modularity and nestedness are known to place heavy
constraints on the stability of several dynamical processes, specially in
ecology.Comment: 7 pages, 4 figures and 1 supplemental information fil
Measuring and mitigating behavioural segregation using Call Detail Records
The overwhelming amounts of data we generate in our daily routine and in social networks has been crucial for the understanding of various social and economic factors. The use of this data represents a low-cost alternative source of information in parallel to census data and surveys. Here, we advocate for such an approach to assess and alleviate the segregation of Syrian refugees in Turkey. Using a large dataset of mobile phone records provided by Turkey's largest mobile phone service operator, TĂĽrk Telekom, in the frame of the Data 4 Refugees project, we define, analyse and optimise inter-group integration as it relates to the communication patterns of two segregated populations: refugees living in Turkey and the local Turkish population. Our main hypothesis is that making these two communities more similar (in our case, in terms of behaviour) may increase the level of positive exposure between them, due to the well-known sociological principle of homophily. To achieve this, working from the records of call and SMS origins and destinations between and among both populations, we develop an extensible, statistically-solid, and reliable framework to measure the differences between the communication patterns of two groups. In order to show the applicability of our framework, we assess how house mixing strategies, in combination with public and private investment, may help to overcome segregation. We first identify the districts of the Istanbul province where refugees and local population communication patterns differ in order to then utilise our framework to improve the situation. Our results show potential in this regard, as we observe a significant reduction of segregation while limiting, in turn, the consequences in terms of rent increase
The Emergence of Roles in Large-Scale Networks of Communication
Communication through social media mediates coordination and information diffusion across a range of social settings. However, online networks are large and complex, and their analysis requires new methods to summarize their structure and identify nodes holding relevant positions. We propose a method that generalizes the sociological theory of brokerage, originally devised on the basis of local transitivity and paths of length two, to make it applicable to larger, more complex structures. Our method makes use of the modular structure of networks to define brokerage at the local and global levels. We test the method with two different data sets. The findings show that our approach is better at capturing role differences than alternative approaches that only consider local or global network features
- …