Identifying Top- k Nodes in Social Networks
| Autor: | Anna Divoli, Ranran Bian, Yun Sing Koh, Gillian Dobbie |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
Social network Computer science business.industry 02 engineering and technology Data science Field (computer science) Theoretical Computer Science Identification (information) Viral marketing Ranking Work (electrical) 020204 information systems New product development 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing business |
| Zdroj: | ACM Computing Surveys. 52:1-33 |
| ISSN: | 1557-7341 0360-0300 |
| Popis: | Top- k nodes are the important actors for a subjectively determined topic in a social network. To some extent, a topic is taken as a ranking criteria for identifying top- k nodes. Within a viral marketing network, subjectively selected topics can include the following: Who can promote a new product to the largest number of people, and who are the highest spending customers? Based on these questions, there has been a growing interest in top- k nodes research to effectively identify key players. In this article, we review and classify existing literature on top- k nodes identification into two major categories: top- k influential nodes and top- k significant nodes. We survey both theoretical and applied work in the field and describe promising research directions based on our review. This research area has proven to be beneficial for data analysis on online social networks as well as practical applications on real-life networks. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|