社交媒体中的信息演化建模与跟踪

E. Shabunina, G. Pasi
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引用次数: 0

摘要

如今,用户生成内容是实时新闻和对世界事件的看法的主要来源。因此,社交媒体作为创造和传播用户生成内容的环境,代表了我们的文化,构成了潜在的知识宝库。在本文中,我们提出了一种全自动建模和跟踪社交媒体信息演变的方法。特别是,我们建议将社交媒体流建模为文本图。利用图简并技术识别图表示的信息流核心单元的时间序列。此外,作为这项工作的主要新颖之处,我们提出了一套及时跟踪和评估信息演变的措施。对一个最流行的社交媒体平台抓取的数据集进行了实验评估,证明了所提出方法的有效性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information evolution modeling and tracking in social media
Nowadays, User Generated Content is the main source of real time news and opinions on the world happenings. Social Media, which serves as an environment for the creation and spreading of User Generated Content, is, therefore, representative of our culture and constitutes a potential treasury of knowledge. In this paper we propose a fully automatic approach for modeling and tracking the information evolution in Social Media. In particular, we propose to model a Social Media stream as a text graph. A graph degeneracy technique is used to identify the temporal sequence of the core units of information streams represented by graphs. Furthermore, as the major novelty of this work, we propose a set of measures to track and evaluate the evolution of information in time. An experimental evaluation on the crawled datasets from one of the most popular Social Media platforms proves the validity and applicability of the proposed approach.
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