Jarosław Koźlak

Models of social groups in blogosphere based on information about comment addressees and sentiments

This work concerns the analysis of number, sizes and other characteristics of groups identified in the blogosphere using a set of models identifying social relations. These models differ regarding identification of social relations, influenced by methods of classifying the addressee of the comments (they are either the post author or the author of a comment on which this comment is directly addressing) and by a sentiment calculated for comments considering the statistics of words present and connotation. The state of a selected blog portal was analyzed in sequential, partly overlapping time intervals. Groups in each interval were identified using a version of the CPM algorithm, on the basis of them, stable groups, existing for at least a minimal assumed duration of time, were identified.

Predicting Community Evolution in Social Networks

Nowadays, sustained development of different social media can be observed worldwide. One of the relevant research domains intensively explored recently is analysis of social communities existing in social media as well as prediction of their future evolution taking into account collected historical evolution chains. These evolution chains proposed in the paper contain group states in the previous time frames and its historical transitions that were identified using one out of two methods: Stable Group Changes Identification (SGCI) and Group Evolution Discovery (GED). Based on the observed evolution chains of various length, structural network features are extracted, validated and selected as well as used to learn classification models. The experimental studies were performed on three real datasets with different profile: DBLP, Facebook and Polish blogosphere. The process of group prediction was analysed with respect to different classifiers as well as various descriptive feature sets extracted from evolution chains of different length. The results revealed that, in general, the longer evolution chains the better predictive abilities of the classification models. However, chains of length 3 to 7 enabled the GED-based method to almost reach its maximum possible prediction quality. For SGCI, this value was at the level of 3–5 last periods.

Analysis of Roles and Groups in Blogosphere

In the paper different roles of users in social media, taking into consideration their strength of influence and different degrees of cooperativeness, are introduced. Such identified roles are used for the analysis of characteristics of groups of strongly connected entities. The different classes of groups, considering the distribution of roles of users belonging to them, are presented and discussed.

Discovery of crises via agent-based simulation of a transportation system

The contribution deals with a class of intelligent decentralized systems that are marked by the possibility of arising critical situations. The work starts from the elaboration of an overall methodology dedicated to the discovery of crises and support of anti-crisis activities. Then the case of transportation enterprise support system is discussed in detail. A simulation study of anti-crisis management in such a system concludes the work.

Multi-agent Crisis Management in Transport Domain

A multi-agent system that solves static and dynamic versions of transport problem (Pickup and Delivery Problem with Time Windows) in presence of crises is shown here. Scenarios to serve different kinds of crises (especially vehicle failures and traffic jams) by agents are described. The results summarising system functioning for solving classical PDPTW as well as influence of crises and applied algorithms of serving them upon quality of obtained solutions have been presented.

Agent-Based Modeling of Supply Chains in Critical Situations

Supply chains are discussed in this article. They are viewed as intelligent decentralized systems that meet the agent paradigm. Thus possibility of arising critical situations in the chains can be analyzed in the agent-based manner. The work is focused on applying an overall methodology dedicated to the discovery of crises and support of anti-crisis activities. The agent-based model is proposed that incorporates majority of features of supply chains so that the modeling of crises can be wide-ranging and easy. As an illustration some simulation results are presented.

Learning in a multi-agent approach to a fish bank game

In this paper application of symbolic, supervised learning in a multi-agent system is presented. As an environment Fish Bank game is used. Agents represent players that manage fishing companies. Rule induction algorithm is applied to generate ship allocation rules. In this article system architecture and learning process are described and preliminary experimental results are presented. Results show that learning agent performance increases significantly when new experience is taken into account.

A multi-agent system for dynamic network reconfiguration

This paper presents a system for dynamic network reconfiguration based on intelligent agents and market-oriented methods. Reconfiguration encompasses routing changes as well as building new and removing unused connections between network nodes. The paper presents a short review of research background in network management methodologies, a description of the systems model and an overview of experimental results.

Combining Agent-Based and Social Network Analysis Approaches to Recognition of Role Influence in Social Media

These days, different forms of social media play a significant role in the functioning of individuals and society, and social network analysis methodology ensures a better understanding of the structure and behaviour of societies forming in such environments. Including an agent–based approach to such analyses allows a more complete understanding of the specificity of given users as well as the local interactions between them. In this paper we introduce a multi–agent model of user organisations in social media, and analyse roles in social organisations based on distinguishing features of user behaviour such as activity, cooperativeness and group formation. We also analyse the range of influence of users playing given roles in the society, taking into consideration the consequences of removal of users with specific roles and carry out several experiments with data from the political blogosphere.

Application of Holonic Approach for Transportation Modelling and Optimising

The goal of this work is to design an environment which makes it possible to build systems allowing flexible composition. Such systems may be used for modelling an organisation with a high level of complexity, with functionalities on different levels, realising heterogeneous activities.We use concepts and assumptions offered by multi-agent and holonic approaches. Theoretic representation of the abstract holon structure is given and a model for building a realisation for a domain, focusing especially on building and reorganising holons. The domain is the management of the transportation company and a delivery strategy for it. Selected results provided by the developed system are presented.