Social network analysis: methods and applications

Abstract

The paper describes the basic components of ISPRAS technology stack for social network data analysis. Particular attention is given to tasks, methods, and applications of network (social connections between users) and textual (user messages and profiles) data analysis: demographic attribute detection, event detection in messages corpora, user identity resolution, community detection, and influence measurement. Means for input data acquisition are also considered: collecting real data through web-interfaces of social services and generating random social graphs. For each of the developed tools we describe its functionality, use cases, basic steps of the underlying algorithms, and experimental results.

Keywords

• социальные сети
• социальные данные
• пользовательские данные
• социальный анализ
• анализ социальных сетей
• анализ содержимого
• веб-сервисы
• микроблоги
• компьютерная лингвистика
• теория графов
• машинное обучение
• распределённые алгоритмы и системы