Proceedings of the 6th International Conference on Knowledge Discovery and Data Mining, Workshop on Social Network Mining and Analysis
The sixth SNA-KDD workshop (www.snakdd.com) is proposed as the sixth in a successful series of workshops on social network mining and analysis co-held with KDD, soliciting experimental and theoretical work on social network mining and analysis in both online and offline social network systems.
In the modern Web, it is common for an active person to have several profiles in different online social networks. As new general-purpose and niche social network services arise every year, the problem of social data integration will likely remain actual in the nearest future. Discovering multiple profiles of a single person across different social networks allows to merge all user's contacts from different social services or compose more complete social graph that is helpful in many social-powered applications. In this paper we propose a new approach for user profile matching based on Conditional Random Fields that extensively combines usage of profile attributes and social linkage. It is extremely suitable for cases when profile data is poor, incomplete or hidden due to privacy settings. Evaluation on Twitter and Facebook sample datasets showed that our solution significatnly outperforms common attribute-based approach and is able to find matches that are not discoverable by using only profile information. We also demonstrate the importance of social links for identity resolution task and show that certain profiles can be matched based only on social relationships between OSN users.
Purpose – The current paper aims to investigate whether the structure of international migration system and its country-to-country distribution have remained stable through the recent turbulent changes in the World System, or experienced any visible alteration. We also seek to outline some of the main factors which likely exerted the most influence upon any recent changes in the structure of international migration network.
Design/methodology/approach – The methodology we use largely belongs to the social network analysis framework – but with some noteworthy limitations stipulated by the specifics of our data.
Findings – Centrality analysis sheds light on some key features of the international migration network. First, the list of the most central nodes demonstrates remarkable stability over time, with the United States consistently occupying the first place, and Russia and Germany stably entering the top-5 (or even top-3 ever since 1990). A number of EU countries and Australia are also set in their positions of highly central nodes. Centrality analysis also clearly demonstrates the emergence (in the 1970s) and development of the Gulf countries (particularly Saudi Arabia and UAE) as major migration destinations.
Research limitations/implications – The results of our analysis present a mixture of evidence to support both the principles of neoclassical migration theory developed in two seminal papers by Todaro (1969) and Harris and Todaro (1970), and some of its critiques, as the migration patterns are strongly influenced by historical links (such as colonial ties), geographical distance, cultural distance, etc. Defining the scope of influence of each of these factors lies far beyond the scale of this paper. However, further application of social network analysis to studying the global migration network, in our opinion, has quite remarkable potential for contributing to this line of research.
Originality/value – This paper’s originality/value lies in drawing attention to the specific features in the structure of the global migration network and their implications for the World-System studies.
The goal of the expert search task is finding knowledgeable persons within the enterprise. In this paper we focus on its distinctions from the other information retrieval tasks. We review the existing ap- proaches and propose a new term weighting scheme which is based on analysis of communication patterns between people. The effectiveness of the proposed approach is evaluated on a collection of e-mails from an organization of approximately 1500 people. Results show that it is possible to take into account communication structure in the process of term weighting, effectively combining communication-based and document-based approaches to expert finding.
This book constitutes the refereed proceedings of the 10th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2014, held in St. Petersburg, Russia in July 2014. The 40 full papers presented were carefully reviewed and selected from 128 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
This article is an expanded version of the report submitted by the author on V scientific and practical conference dedicated to the memory of the first Dean of the Faculty of Sociology HSE Alexander O. Kryshtanovskiy "Sociological research methods in modern practice". The article is based on a study of the quantative data obtained in the course of one of the stages of the study "New social movements of youth" by Center of Youth Studies HSE - SaintPetersburg. At this stage, youth community mapping was conducted and analysis of the data using SNA tools was organised. The issue of this work is related to the specific application of network theory and network analysis methods in the process of discovering relations between various informal organisations on the example of youth communities.
In online social networks, high level features of user behavior such as character traits can be predicted with data from user profiles and their connections. Recent publications use data from online social networks to detect people with depression propensity and diagnosis. In this study, we investigate the capabilities of previously published methods and metrics applied to the Russian online social network VKontakte. We gathered user profile data from most popular communities about suicide and depression on VK.com and performed comparative analysis between them and randomly sampled users. We have used not only standard user attributes like age, gender, or number of friends but also structural properties of their egocentric networks, with results similar to the study of suicide propensity in the Japanese social network Mixi.com. Our goal is to test the approach and models in this new setting and propose enhancements to the research design and analysis. We investigate the resulting classifiers to identify profile features that can indicate depression propensity of the users in order to provide tools for early depression detection. Finally, we discuss further work that might improve our analysis and transfer the results to practical applications.
The core problem considered in the article is dedicated to the revealing of project system elements, where the network modeling can be adopted to management. Using of Web of Science and ProQuest databases provided with the opportunity of publication activity statistics research and with the definite articles and other types of publications’ analysis for the search of basic directions of network theory adoption for project management. The identification of the most demanded and actual directions of network approach and social network analysis application to management of project system elements was fulfilled.
The CCIS series is devoted to the publication of proceedings of computer science conferences. Its aim is to efficiently disseminate original research results in informatics in printed and electronic form. While the focus is on publication of peer-reviewed full papers presenting mature work, inclusion of reviewed short papers reporting on work in progress is welcome, too. Besides globally relevant meetings with internationally representative program committees guaranteeing a strict peer-reviewing and paper selection process, conferences run by societies or of high regional or national relevance are also considered for publication.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.