Exploring influence and interests among users within social networks

Jose Simoes, Julia Kiseleva, Elena Sivogolovko, Boris Novikov

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийглава/разделнаучнаярецензирование

1 Цитирования (Scopus)

Аннотация

The spread of influence among individuals in a social network is one of the fundamental questions in the social sciences. In this chapter we consider the main definitions of influence, which are based on a small set of snapshot observations of a social network. The former is particularly useful because large-scale social network data sets are often only available in snapshots or crawls. In our work, considering a rich dataset of user preferences and interactions, we use clustering techniques to study how user interests group together and identify the most popular users within these groups. For this purpose, we focus on multiple dimensions of users-related data, providing a more detailed process model of how influence spreads. In parallel, we study the measurement of influence within the network according to interest dependencies. We validate our analysis using the history of user social interactions on Facebook. Furthermore, this chapter shows how these ideas can be applied in real-world scenarios, namely for recommendation and advertising systems.

Язык оригиналаанглийский
Название основной публикацииComputational Social Networks
Подзаголовок основной публикацииSecurity and Privacy
ИздательSpringer Nature
Страницы177-206
Число страниц30
Том9781447140511
ISBN (электронное издание)9781447140481
ISBN (печатное издание)1447140508, 9781447140474
DOI
СостояниеОпубликовано - 1 авг 2012

Предметные области Scopus

  • Компьютерные науки (все)

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