baldassarri baronchelli barrat caglioti castellano cattuto complexity dattoli evolutionary_dynamics granular_media granular_media herrmann information_theory innovation_dynamics kreyon language_dynamics loreto mari mukherjee petri pietronero puglisi quantum_optics self_organization servedio statistical_physics techno_social_systems tria zapperi zippers
2013 |
Becker, Martin; Caminiti, Saverio; Fiorella, Donato; Francis, Louise; Gravino, Pietro; Haklay, Mordechai; Hotho, Andreas; Loreto, Vittorio; Mueller, Juergen; Ricchiuti, Ferdinando; Servedio, Vito D P; Sirbu, Alina; Tria, Francesca Awareness and learning in participatory noise sensing Journal Article PLoS ONE, 8 , pp. e81638-1–e81638-12, 2013. Abstract | Links | BibTeX | Tags: citizen_science, loreto, servedio, sirbu, tria @article{b, title = {Awareness and learning in participatory noise sensing}, author = {Martin Becker and Saverio Caminiti and Donato Fiorella and Louise Francis and Pietro Gravino and Mordechai Haklay and Andreas Hotho and Vittorio Loreto and Juergen Mueller and Ferdinando Ricchiuti and Vito D.P. Servedio and Alina Sirbu and Francesca Tria}, url = {http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0081638}, year = {2013}, date = {2013-01-01}, journal = {PLoS ONE}, volume = {8}, pages = {e81638-1--e81638-12}, abstract = {The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.}, keywords = {citizen_science, loreto, servedio, sirbu, tria}, pubstate = {published}, tppubtype = {article} } The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments. |
Sirbu, Alina; Loreto, Vittorio; Servedio, Vito Domenico Pietro; Tria, Francesca Cohesion, consensus and extreme information in opinion dynamics Journal Article ADVANCES IN COMPLEX SYSTEM, 16 , 2013. Abstract | Links | BibTeX | Tags: loreto, opinion_dynamics, servedio, sirbu, tria @article{b, title = {Cohesion, consensus and extreme information in opinion dynamics}, author = {Alina Sirbu and Vittorio Loreto and Vito Domenico Pietro Servedio and Francesca Tria}, url = {http://www.worldscientific.com/doi/abs/10.1142/S0219525913500355}, year = {2013}, date = {2013-01-01}, journal = {ADVANCES IN COMPLEX SYSTEM}, volume = {16}, publisher = {WORLD SCIENTIFIC PUBL CO PTE LTD}, abstract = {Opinion formation is an important element of social dynamics. It has been widely studied in the last years with tools from physics, mathematics and computer science. Here, a continuous model of opinion dynamics for multiple possible choices is analyzed. Its main features are the inclusion of disagreement and possibility of modulating external information/media effects, both from one and multiple sources. The interest is in identifying the effect of the initial cohesion of the population, the interplay between cohesion and media extremism, and the effect of using multiple external sources of information that can influence the system. Final consensus, especially with the external message, depends highly on these factors, as numerical simulations show. When no external input is present, consensus or segregation is determined by the initial cohesion of the population. Interestingly, when only one external source of information is present, consensus can be obtained, in general, only when this is extremely neutral, i.e., there is not a single opinion strongly promoted, or in the special case of a large initial cohesion and low exposure to the external message. On the contrary, when multiple external sources are allowed, consensus can emerge with one of them even when this is not extremely neutral, i.e., it carries a strong message, for a large range of initial conditions.}, keywords = {loreto, opinion_dynamics, servedio, sirbu, tria}, pubstate = {published}, tppubtype = {article} } Opinion formation is an important element of social dynamics. It has been widely studied in the last years with tools from physics, mathematics and computer science. Here, a continuous model of opinion dynamics for multiple possible choices is analyzed. Its main features are the inclusion of disagreement and possibility of modulating external information/media effects, both from one and multiple sources. The interest is in identifying the effect of the initial cohesion of the population, the interplay between cohesion and media extremism, and the effect of using multiple external sources of information that can influence the system. Final consensus, especially with the external message, depends highly on these factors, as numerical simulations show. When no external input is present, consensus or segregation is determined by the initial cohesion of the population. Interestingly, when only one external source of information is present, consensus can be obtained, in general, only when this is extremely neutral, i.e., there is not a single opinion strongly promoted, or in the special case of a large initial cohesion and low exposure to the external message. On the contrary, when multiple external sources are allowed, consensus can emerge with one of them even when this is not extremely neutral, i.e., it carries a strong message, for a large range of initial conditions. |
Sirbu, Alina; Loreto, Vittorio; Servedio, Vito Domenico Pietro; Tria, Francesca Opinion Dynamics with Disagreement and Modulated Information Journal Article JOURNAL OF STATISTICAL PHYSICS, 151 , pp. 218–237, 2013. Abstract | BibTeX | Tags: loreto, opinion_dynamics, servedio, sirbu, tria @article{b, title = {Opinion Dynamics with Disagreement and Modulated Information}, author = {Alina Sirbu and Vittorio Loreto and Vito Domenico Pietro Servedio and Francesca Tria}, year = {2013}, date = {2013-01-01}, journal = {JOURNAL OF STATISTICAL PHYSICS}, volume = {151}, pages = {218--237}, abstract = {Opinion dynamics concerns social processes through which populations or groups of individuals agree or disagree on specific issues. As such, modelling opinion dynamics represents an important research area that has been progressively acquiring relevance in many different domains. Existing approaches have mostly represented opinions through discrete binary or continuous variables by exploring a whole panoply of cases: e.g. independence, noise, external effects, multiple issues. In most of these cases the crucial ingredient is an attractive dynamics through which similar or similar enough agents get closer. Only rarely the possibility of explicit disagreement has been taken into account (i.e., the possibility for a repulsive interaction among individuals' opinions), and mostly for discrete or 1-dimensional opinions, through the introduction of additional model parameters. Here we introduce a new model of opinion formation, which focuses on the interplay between the possibility of explicit disagreement, modulated in a self-consistent way by the existing opinions' overlaps between the interacting individuals, and the effect of external information on the system. Opinions are modelled as a vector of continuous variables related to multiple possible choices for an issue. Information can be modulated to account for promoting multiple possible choices. Numerical results show that extreme information results in segregation and has a limited effect on the population, while milder messages have better success and a cohesion effect. Additionally, the initial condition plays an important role, with the population forming one or multiple clusters based on the initial average similarity between individuals, with a transition point depending on the number of opinion choices.}, keywords = {loreto, opinion_dynamics, servedio, sirbu, tria}, pubstate = {published}, tppubtype = {article} } Opinion dynamics concerns social processes through which populations or groups of individuals agree or disagree on specific issues. As such, modelling opinion dynamics represents an important research area that has been progressively acquiring relevance in many different domains. Existing approaches have mostly represented opinions through discrete binary or continuous variables by exploring a whole panoply of cases: e.g. independence, noise, external effects, multiple issues. In most of these cases the crucial ingredient is an attractive dynamics through which similar or similar enough agents get closer. Only rarely the possibility of explicit disagreement has been taken into account (i.e., the possibility for a repulsive interaction among individuals' opinions), and mostly for discrete or 1-dimensional opinions, through the introduction of additional model parameters. Here we introduce a new model of opinion formation, which focuses on the interplay between the possibility of explicit disagreement, modulated in a self-consistent way by the existing opinions' overlaps between the interacting individuals, and the effect of external information on the system. Opinions are modelled as a vector of continuous variables related to multiple possible choices for an issue. Information can be modulated to account for promoting multiple possible choices. Numerical results show that extreme information results in segregation and has a limited effect on the population, while milder messages have better success and a cohesion effect. Additionally, the initial condition plays an important role, with the population forming one or multiple clusters based on the initial average similarity between individuals, with a transition point depending on the number of opinion choices. |
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