近期微博分类方法综述与分类

Veranika Mikhailava, Victor Khaustov, V. Klyuev
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引用次数: 0

摘要

微博的日益普及要求科学家们开发出对短文本进行有效和高效分析的方法,以便了解微博用户的意见及其信息的可信度。在这篇综述中,我们研究了微博中最常见的情感分析方法,并解释了它们的优点和缺点。我们还回顾了评估新闻标题和政治声明可信度的方法,并讨论了它们在微博中的适用性。微博帖子的鲜明特征,如俚语、表情符号、糟糕的语法和拼写是评估的重点。微博消息的这一特性降低了传统分类器的性能,限制了其在实际应用中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overview and Categorization of Recent Approaches to Microblog Classification
A growing popularity of microblogs requires scientists to develop methods for effective and efficient analysis of short texts in order to understand opinions of microblog users and the trustworthiness of their messages. In this review, we examine most common approaches to sentiment analysis in microblogs and explain their advantages and weaknesses. We also review approaches to assessing credibility in news headlines and political statements and discuss their applicability in microblogs. Distinct characteristics of microblog posts, such as slang, emoticons, poor grammar and spelling are in the focus of the evaluation. Such properties of microblog messages deteriorate the performance of conventional classifiers and limit their use in practical applications.
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