Joint link-attribute user identity resolution in online social networks
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.
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.
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.
We present a new click model for processing click logs and predicting relevance and appeal for query–document pairs in search results. Our model is a simplified version of the task-centric click model but outperforms it in an experimental comparison.
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.
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.
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.