流行度演化分析与预测综述

胡颖; 胡长军; 傅树深; 黄建一

doi:10.11999/JEIT160743

流行度演化分析与预测综述

doi: 10.11999/JEIT160743

基金项目:

国家973规划项目(2013CB329601)

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- 被引次数: 0
出版历程
- 收稿日期: 2016-07-14
- 修回日期: 2016-12-30
- 刊出日期: 2017-04-19

Survey on Popularity Evolution Analysis and Prediction

Funds:

The National 973 Program of China (2013CB329601)

摘要

摘要: 社交网络每天以爆发式的增长速率产生着大量信息，但是人们对海量信息的关注程度有限。人们关注哪些信息、对信息的关注程度如何随时间变化，即为信息的流行度演化问题。流行度演化反映了人们的关注点和信息的流动与传播。建模与预测网络信息的流行度演化有助于信息传播和人类行为的研究、辅助舆情监控、并带来极大的应用和商业价值。近几年，研究人员在该方面取得了丰硕的研究成果，但尚缺乏对这些成果进行梳理、总结的综述。该文系统地回顾网络信息流行度演化的主要工作，对分析与预测方法、模型、发展脉络进行梳理。首先从定性和定量方面阐述了流行度演化的特点；介绍如何量化影响流行度演化的众多因素，并对它们进行分类、总结；然后将已有的建模和预测方法归纳为3类：基于早期流行度、基于影响因素、基于级联传播，从原理、典型成果、特点比较、适用范围等方面对这3类方法进行评述；最后根据目前模型和方法的特点以及现实需求，指出了未来流行度演化的研究方向。
- 社交网络 /
- 流行度演化 /
- 预测 /
- 信息传播 /
- 网络信息
Abstract: Online social network is generating information at an explosive rate. Information competes with each other for peoples limite attention. How peoples attention to information evolves over time is referred to as the problem of popularity evolution. Popularity evolution reflects what people focus on and how information flow and diffuse. Popularity evolution prediction of online information helps the studies of information diffusion and human behaviors, assists public opinion monitoring, and brings high application value and commercial value. In recent years, researchers have gained great research achievements. However, there is still a lack of survey which reviews and summarizes existing work. This paper systematically reviews main work of popularity evolution analysis and prediction, and gives summarization to the existing methods and models. First, insight into understanding popularity evolution patterns from qualitative and quantitative perspectives is provided. How to measure factors affecting popularity evolution and to classify them in taxonomy are introduced. Third, the methods of modeling and predicting popularity evolution are categorized into three classes: previous-popularity-based, factor-based, and diffusion-based. These three classes from the following aspects are elaborated: theory, representative work, characteristic comparison, and application scope. Finally, the paper is concluded and future research directions are given according to existing work and current demands.
- Social network /
- Popularity evolution /
- Prediction /
- Information diffusion /
- Online information

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