共享任务:使用语义相似度进行阿拉伯语宣传检测

Salar Mohtaj, Sebastian Möller
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引用次数: 3

摘要

近年来,通过社交媒体宣传和传播假新闻已经成为一个严重的问题。在本文中,我们提出了我们在阿拉伯语宣传检测的共同任务的方法,其目标是识别阿拉伯语社交媒体文本中的宣传技术。我们提出了一个语义相似度检测模型,将测试集中的文本与训练集中的句子进行比较,以找到最相似的实例。目标文本的标签是从训练集中最相似的文本中获得的。该模型在文本数据集上的微F1得分为0.494。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TUB at WANLP22 Shared Task: Using Semantic Similarity for Propaganda Detection in Arabic
Propaganda and the spreading of fake news through social media have become a serious problem in recent years. In this paper we present our approach for the shared task on propaganda detection in Arabic in which the goal is to identify propaganda techniques in the Arabic social media text. We propose a semantic similarity detection model to compare text in the test set with the sentences in the train set to find the most similar instances. The label of the target text is obtained from the most similar texts in the train set. The proposed model obtained the micro F1 score of 0.494 on the text data set.
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