The conceptual model of information confrontation of virtual communities in social networking services

Social networking services are one of the most popular mass media and are used as an effective tool for information confrontation due to their functional characteristics. Existing models of information confrontation take into account the redistribution between conflict parties of only one kind of resource, although in the social networking services there is a need to consider additional factors that determine the effectiveness of virtual communities’ opposition. A conceptual model of information confrontation of virtual communities in social networking services has been developed, and it includes three-layer dynamics of the number of actors, growth of information resources of virtual communities and dynamics of spending resources for the confrontation conduct. The model also takes into account the peculiarities of the antagonistic conflict of virtual communities’ actors through the choice of a differential equation that corresponds to the type of its dynamics. The offered conceptual model formalizes the behavior of virtual communities’ actors in the conditions of antagonistic conflict. At the same time, it allows to investigate the peculiarities of using different strategies to carry out the information fight of virtual communities in social networking services, to choose optimal strategies, to predict the development of conflicts in the information space and to develop effective measures to counter threats to the state’s information security

A competitive search game with a moving target

We introduce a discrete-time search game, in which two players compete to find an invisible object first. The object moves according to a time-varying Markov chain on finitely many states. The players are active in turns. At each period, the active player chooses a state. If the object is there then he finds the object and wins. Otherwise the object moves and the game enters the next period. We show that this game admits a value, and for any error-term epsilon > 0 , each player has a pure (subgame-perfect) epsilon-optimal strategy. Interestingly, a 0-optimal strategy does not always exist. We derive results on the analytic and structural properties of the value and the epsilon-optimal strategies. We devote special attention to the important timehomogeneous case, where we show that (subgame-perfect) optimal strategies exist if the Markov chain is irreducible and aperiodic

OR for entrepreneurial ecosystems : a problem-oriented review and agenda

Innovation-driven entrepreneurship has become a focus for economic development and received increasing attention from policy makers and academics over the last decades. While consensus has been reached that context matters for innovation and entrepreneurship, little evidence and decision support exists for policy makers to effectively shape the environment for growth-oriented companies. We present the entrepreneurial ecosystem concept as a complex systems-based approach to the study of innovation-driven entrepreneurial economies. The concept, in combination with novel data sources, offers new opportunities for research and policy, but also comes with new challenges. The aim of this paper is to take stock of the literature and build bridges for more transdisciplinary research. First, we review emergent trends in ecosystem research and provide a typology of four overarching problems based on current limitations. These problems connect operational research scholars to the context and represent focal points for their contributions. Second, we review the operational research literature and provide an overview of how these problems have been addressed and outline opportunities for future research, both for the specific problems as well as cross-cutting themes. Operational research has been invaluable in supporting decision-makers facing complex problems in several fields. This paper provides a conceptual and methodological agenda to increase its contribution to the study and governance of entrepreneurial ecosystems

Dynamic competition over social networks Dynamic competition over social networks

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/cesdp2017.htmlDocuments de travail du Centre d'Economie de la Sorbonne 2017.21 - ISSN : 1955-611XWe provide an analytical approach to the problem of influence maximization in a social network when two players compete by means of dynamic targeting strategies. We formulate the problem as a two-player zero-sum stochastic game. We prove the existence of the uniform value: if the players are sufficiently patient, both players can guarantee the same mean-average opinion without knowing the exact discount factor. Further, we put forward some elements for the characterization of equilibrium strategies. In general, players must implement a trade-off between a forward-looking perspective, according to which they shall aim at maximizing the future spread of their opinion in the network, and a backward-looking perspective, according to which they shall aim at counteracting their opponent's previous actions. When the influence potential of players is small, an equilibrium strategy is to systematically target the agent with the largest eigenvector centrality.Nous proposons une approche analytique au problème de maximisation de l'influence dans un réseau social entre deux joueurs utilisant des stratégies dynamiques. Le problème est formulé comme un jeu stochastique à somme nulle. Nous prouvons l'existence de la valeur uniforme et donnons une caractérisation partielle des stratégies d'équilibre. Nous montrons notamment que lorsque l'influence exercée par les agents est faible, ces derniers doivent systématiquement cibler l'agent avec la centralité "vecteur propre" la plus élevée

Dynamic competition over social networks

International audienceWe propose an analytical approach to the problem of influence maximization in a social network where two players compete by means of dynamic targeting strategies. We formulate the problem as a two-player zero-sum stochastic game. We prove the existence of the uniform value: if the players are sufficiently patient, both can guarantee the same mean-average opinion without knowing the exact length of the game. Furthermore, we put forward some elements for the characterization of equilibrium strategies. In general, players must implement a trade-off between a forward-looking perspective, according to which they aim to maximize the future spread of their opinion in the network, and a backward-looking perspective, according to which they aim to counteract their opponent’s previous actions. When the influence potential of players is small, we describe an equilibrium through a one-shot game based on eigenvector centrality