外语社区实体级事件扩散预测框架

Govind, M. Spaniol
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引用次数: 6

摘要

通过网络或其他“传统”媒体获取新闻,使得信息几乎可以迅速传播到世界的每一个角落。这些报告涵盖了各种各样的事件,从与当地有关的事件到引起全球关注的事件。一个事件的社会影响可以相对容易地通过它在新闻或社交媒体上吸引的注意力(例如,它收到和/或引发的回应数量)来“衡量”。然而,这并不一定反映其跨文化影响及其向其他社区的扩散。为了解决预测信息在外语社区传播的问题,我们引入了ELEVATE框架。ELEVATE利用Web内容中的实体信息,并利用与位置相关的数据进行与语言相关的事件扩散预测。我们在不同语言的维基百科社区中传播事件的实验证明了我们的方法的可行性,以及对最先进方法的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ELEVATE: A Framework for Entity-level Event Diffusion Prediction into Foreign Language Communities
The accessibility to news via the Web or other "traditional" media allows a rapid diffusion of information into almost every part of the world. These reports cover the full spectrum of events, ranging from locally relevant ones up to those that gain global attention. The societal impact of an event can be relatively easily "measured" by the attention it attracts (e.g. in the number of responses it receives and/or provokes) in the news or social media. However, this does not necessarily reflect its inter-cultural impact and its diffusion into other communities. In order to address the issue of predicting the spread of information into foreign language communities we introduce the ELEVATE framework. ELEVATE exploits entity information from Web contents and harnesses location related data for language-related event diffusion prediction. Our experiments on event spreading across Wikipedia communities of different language demonstrate the viability of our approach and improvement over state-of-the-art approaches.
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