Enhanced Event Detection in Twitter Through Feature Analysis

Dharini Ramachandran, P. Ramasubramanian
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引用次数: 2

Abstract

The Digital era has the benefits in unearthing a large amount of imperative material. One such digital document is social media data, which when processed can give rise to information which can be helpful to our society. One of the many things that we can unearth from social media is events. Twitter is a very popular microblog that encompasses fruitful and rich information on real world events and popular topics. Event detection in view of situational awareness for crisis response is an important need of the current world. The identification of tweets comprising information that may assist in help and rescue operation is crucial. Most pertinent features for this process of identification are studied and the inferences are given in this article. The efficiency and practicality of the features are discussed here. This article also presents the results of experimentation carried out to assess the most relevant combination of features for improved performance in event detection from Twitter.
通过特征分析增强Twitter的事件检测
数字时代的好处是可以挖掘出大量必要的材料。其中一种数字文件是社交媒体数据,经过处理后可以产生对我们社会有益的信息。我们可以从社交媒体中发现的许多东西之一就是事件。Twitter是一个非常受欢迎的微博,它包含了关于现实世界事件和热门话题的丰富信息。基于态势感知的事件检测是当前世界的一项重要需求。识别包含可能有助于帮助和救援行动的信息的推文至关重要。本文研究了这一识别过程中最相关的特征,并给出了推论。讨论了该功能的有效性和实用性。本文还介绍了为评估最相关的功能组合以提高Twitter事件检测性能而进行的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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