Leveraging the Flow of Collective Attention for Computational Communication Research

Abstract

Human attention becomes an increasingly scarce resource in the age of information explosion. To better understand the flow of collective attention, we construct the attention flow network using anonymous smartphone data of 100,000 users in a major city of China. In the constructed network, nodes are websites visited by users, and links denote the switch of users between two websites. We find a strong concentration of collective attention allocated to popular websites for smartphone users, and strong scaling relationships for the flow of collection attention in the flow networks. Especially, there is a centralized flow structure, the website of large traffic can control the circulated collective attention. Finally, we discussed the benefits and limitations of using the flow network analysis for computational communication research.

Publication
Work in progress
Date
Links
  • The Panel of Social Networks and Computational Communication, The XXXVII Sunbelt Social Networks Conference of the International Network for Social Network Analysis(INSNA), May 30th – June 4th, 2017 Beijing, China.
  • 网络与数据科学前沿论坛,2017年11月11-12日,西北工业大学,国际会议中心第二会议室,西安,中国

In preparing.