使用Doc2Vec识别印度尼西亚推文中的骗局

2021 9th International Conference on Information and Communication Technology (ICoICT) Pub Date : 2021-08-03 DOI:10.1109/ICoICT52021.2021.9527515

Titi Widaretna, Jimmy Tirtawangsa, A. Romadhony

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引用次数: 4

摘要

在本文中，我们介绍了我们在tweet集合上的恶作剧检测工作。我们采用Doc2Vec作为文本表示方法，SVM作为分类器，将骗局检测作为文本分类问题来解决。我们收集并注释了5000条推文，其中包括2500条恶作剧推文和2500条真实推文。实验结果表明，本文提出的推文骗局检测准确率为93.4%。

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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Hoax Identification on Tweets in Indonesia Using Doc2Vec

In this paper, we present our work on hoax detection on a collection of Tweets. We tackle the hoax detection as a text classification problem, with Doc2Vec as the text representation method and SVM as the classifier. We collected and annotated 5000 Tweets that consist of 2500 hoax Tweets and 2500 truth Tweets. The experimental results show that the accuracy of our proposed hoax detection on Tweets is 93.4%.

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2021 9th International Conference on Information and Communication Technology (ICoICT)

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