An Analysis of Slant in Tweets: Case Study
An Analysis of Slant in Tweets: Case Study
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DOI：
10.1145/3365109.3368770
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发表时间：
2019-12
期刊：
影响因子：
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通讯作者：
Nagaraju Vadranam;K. M. George;Starla Marier Demings
中科院分区：
文献类型：
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作者：
Nagaraju Vadranam;K. M. George;Starla Marier Demings
确定社交媒体中发现的信息的质量和可靠性一直是一些研究人员的研究课题。一套解决方案可能并不适用于所有情况。本文提出了一种方法来估计倾斜的推文相关的主题。遵循的一般方法是从推文中构建标记数据，并使用监督学习来构建预测模型。将从两个数据集获得的结果与OTC模型和基于CNN的模型进行比较。
Determination of quality and reliability of information found in social media have been subjects of study by sever researchers. One set of solution may not work in all cases. This paper presents a method to estimate the slant of tweets related to a topic. The general approach followed is to construct labeled data from tweets and use supervised learning to build predictive models. Results obtained from two datasets are compared against OTC model and a CNN based model.