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Semi-automated Methods for the Annotation and Design of a Semantic Network Designed for Sentiment Analysis of Social Web Content

机译:用于向社交网络内容情感分析设计的语义网络的分组和设计的半自动方法

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We have designed a new semantic network for the English language annotated with two types of domain knowledge: 1) general domain knowledge, represented as a sentiment polarity attached to relationships between words and 2) contextual knowledge, such as domain-specific proper names. In the context of social networks, such as Twitter, the evolution and maintenance of the network are particularly critical tasks for analysts not to incur in a quick obsolescence. We show how a set of semi-automated methodologies applied to our new semantic network show promising results on preliminary tests run using Twitter data.
机译:我们为具有两种类型的域知识的英语语义设计了一种新的语义网络:1)概述,表示为与单词和2)之间的关系附加的情感极性,例如域特定的正确名称。在社交网络的背景下,如Twitter,网络的演变和维护是用于分析师不得在快速过时产生的分析师的尤占关键任务。我们展示应用于我们新的语义网络的一组半自动化方法,显示了使用推特数据运行初步测试的有希望的结果。

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