The impacts of information on individuals within a social network are, mostly, statically modeled and the dynamic is not frequently tackled. In addition, the works about modeling and simulation of the populations reactions to the information do not use explicit specification languages to describe their models. These models are specified in the shape of graph or math formulas and then directly implemented and coded using classical programming languages. We propose to model, in the frame of SICOMORES project studying stabilization phase of a conflict, the actions of influence in a multidimensional social networks (MSN). Each graph dimension corresponds to a predetermined social network (Family, religion, neighborhood). The purpose of this work is to provide a simple but efficient and accurate framework to model the behavior of an individual, but also the simulation of the propagation of information among a group of individuals and its influence on their behavior. In more details, we define a set of models of individuals characterized by a set of state variables (e.g. Using Maslow to construct the behavior of an individual) and the mesh between the individuals within a social network. Then, we introduce the platform architecture, sharing resources, specifically designed to simulate MSN. In the end, a scenario is used to validate our models using the platform based on DEVS formalism.

The impact of information on individuals within a social network is, mostly, statically modeled and the dynamic is not frequently tackled. In addition, the work of modeling and simulation of the population's reactions to the information do not use explicit specification languages to describe their models. These models are specified in the shape of graph or math formulas and then directly implemented and coded using classical programming languages. We propose to model the actions of influence in a multidimensional social network (MSN). Each graph layer corresponds to a predetermined social network based on one relationship. In this work, the use of the DEVS formalism has permitted to explicit M&S of human behavior and the interaction between individuals as a network. In more detail, we define a set of models of individuals characterized by a set of state variables (e.g., using Maslow's theory [15] to construct the behavior of an individual) and the mesh between the individuals within a social network. Then, we introduce the platform architecture, sharing resources, specifically designed to simulate MSN. In the end, a scenario is used to validate our models using the platform based on DEVS Specification.

Social simulation implies two preconditions: determining a population and simulate the information diffusion within it. A population represents a group of interconnected individuals sharing information. In this paper, the population we generate is detailed by socio-cultural features, specifically the way that people tend to link together. To this end, the use of a social network is a little bit restrictive: people are linked by only one relationship. Multidimensional Social Networks (MSN) model 3D social networks where each dimension represent a kind of relationship [1]. The MSN architecture allows us to better represent the diversity of humans relations but also define distinctive rules for the simulation of the message diffusion. The inner idea is that information disseminates differently according to the links through which the information propagates. So, we present in this paper the modeling of our MSN based on social science and a simulation using propagation rules for each dimension.

Social networks are the most salient concepts in social sciences. In industrial engineering, the informal communication between people in a social network has an important part in the change management. The choice to adopt a new technology, in particular Information System, in an organization or ecosystem is not always rational. The opinion of individuals is influenced by information gathered about the attributes of the technology from other members of their social network. Research in the domain gives significant results but the influence of information on individuals within a social network is, mostly, statically modeled where the dynamic aspect is not frequently tackled. In addition, the works about modeling and simulation of the population reaction to the information do not use explicit formal languages to describe their models. These models are classically specified in the shape of graph or math Expressions and then directly coded using classical programming languages. The DEVS formalism (Discrete EVent system Specifications) is being general enough to represent such dynamical systems. It provides an operational semantics applicable to this domain. These models are independent from implementation and so, easily reusable. The purpose of this work is to provide a simple but efficient and accurate framework to model and simulate the propagation of information and its influence on individual behavior. We present in this paper the results of three cases of simulation showing that our architecture is efficient and the numerous perspectives to this work.

Choosing to Design a decision support system aimed at developing the user's intercultural communication skills by making him experiment with the planning, sending and spreading of messages and their effects is particularly challenging: if the propagation process is to be realistic and accurate, it is necessary to create a virtual population represented by a network encapsulating specific cultural features. The goal of this paper is to propose a way of capturing a socio-cultural context by the study of the specific forms of sociality of the chosen people and how these forms organize their society. It allows to determine the relevant network layers (dimensions) and ultimately to generate a multidimensional social network representing a realistic population. The chosen context here is sub-Saharan Africa, with the additional requirement of simulating societies of failed, failing and war torn States, the intended user being a member of a peacekeeping force.

Analyzing the social roles inside on-line communities became a big challenge nowadays. The on-line communities formed around exchange platforms (e.g., forums) create an increasing source of data for analyzing user’s behavior. This paper proposes an exploratory analysis of communities in news website based on its sub-communities. Actually, we assume that people who participate in forum debate in news websites focus their participation in one or a very few topics (also called context), i.e., they formed the sub-communities. These subcommunities, will help us to find the contextual celebrity: the pertinent users in the sub-communities. We based our analysis on a dataset composed by 11,143 users writing more than 35,000 posts on 57 different forums grouped in 3 topics, and on social networks enriched with relations extracted from the content of the users’ posts. Keywords-Social role; Social network; On-line community.

Online discussions became increasingly widespread with the Web 2.0: no matter the distance, whether you know the person or not, you can discuss and exchange ideas with people all over the world through forums, blogs, and newsgroups. The news websites have extensively used forums in order to encourage the reader being a real participant in the information media. This paper aims at automatically extracting the celebrities from such discussions. We propose certain meta-criteria and we provide an evaluation on a dataset of 35,175 posts written by 14,443 users. The results show that one of the proposed meta-criteria succeeds in extracting celebrities and allows for further improvements.

The expansion of web user roles is, nowadays, a fact due to the ability of users to interact, discuss, exchange ideas and opinions, and form social networks through the web. The interaction level among users leads to the appearance of several social roles which can be characterized as positions, behaviors, or virtual identities. These roles may be developed in social networks, and they keep changing and evolving over time. In this article, a survey of the state-of-the-art approaches is presented regarding the identification of roles within the context of a social network. It is shown that social roles exist as a function of each other; they appear and evolve through user interaction. Different approaches are analyzed and additional characteristics that should be taken into account during the role analysis are discussed.

Forums on the Internet are an overwhelming source of knowledge considering the number of topics treated and users who participate in these discussions. This volume of data is difficult to comprehend for a person with respect for the large number of posts. Our work proposes a new formal framework for synthesizing information contained in these forums. We extract a social network that reflects reality by extracting multiple relationships between individuals (structural relationship, name and text quotation relationships). These relationships are created from the structure and the content of the discussion. Results show that discovering quotation relationships from forums is not trivial.

Web forums are a huge data source. They allow people to interact with unknown individuals. Studying forums shows that the interaction is not obvious only through the structure but also through the content of the post. Taking into account this observation, we extract a social network with different kinds of relationships i.e. the structural relation, the name and the text quotations relation. We present here the promising results we obtain, and the difficulties we face while extracting the quotations in this kind of textual content. These results are obtained from real data (from two information websites) which make the validation difficult. So, we create a validation protocol composed of two steps and based on human raters. Finally, we will see the objective of this work which is understanding interactions in order to extract the social roles of individuals.