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Hybrid Semantic Analysis of Tweets: A Case Study of Tweets on Girl-Child in India

机译:推文的混合语义分析:以印度女童推文为例

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Social networks have become one of the major and important parts of daily life. Besides sharing ones views the social networking sites can also be very efficiently used to judge the behavior and attitude of individuals towards the posts. Analysis of the mood of public on a particular social issue can be judged by several methods. Analysis of the society mood towards any particular news in form of tweets is investigated in this paper. The key objective behind this research is to increase the accuracy and effectiveness of the classification by the process of Natural Language Processing (NLP) Techniques while focusing on semantics and World Sense Disambiguation. The process of classification includes the combination of the effect of various independent classifiers on one particular classification problem. The data that is available in the form of tweets on twitter can easily frame the insight of the public attitude towards the particular tweet. The proposed work implements a hybrid method that includes Hybrid K, clustering and boosting. A comparison of this scheme versus a K-means/SVM approach is provided. Results are shown and discussed.
机译:社交网络已成为日常生活的重要组成部分之一。除了分享观点外,社交网站还可以非常有效地用于判断个人对帖子的行为和态度。可以通过多种方法来判断公众对特定社会问题的情绪。本文以推文的形式分析了社会对任何特定新闻的情绪。这项研究的主要目标是通过自然语言处理(NLP)技术的过程来提高分类的准确性和有效性,同时关注语义和世界意义上的歧义消除。分类过程包括各种独立分类器对一个特定分类问题的影响的组合。在Twitter上以推文形式提供的数据可以轻松构成公众对特定推文态度的见解。拟议的工作实现了一种包括混合K,聚类和增强的混合方法。提供了该方案与K-means / SVM方法的比较。显示结果并进行讨论。

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