Fake News Classification Web Service for Spanish News by using Artificial Neural Networks

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS International Journal of Advanced Computer Science and Applications Pub Date : 2023-01-01 DOI:10.14569/ijacsa.2023.0140334
P. Moreno-Vallejo, G. Bastidas-Guacho, Patricio Rene Moreno-Costales, Jefferson Jose Chariguaman-Cuji
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引用次数: 1

Abstract

—The use of digital media, such as social networks, has promoted the spreading of fake news on a large scale. Therefore, several Machine Learning techniques, such as artificial neural networks, have been used for fake news detection and classification. These techniques are widely used due to their learning capabilities. Besides, models based on artificial neural networks can be easily integrated into social media and websites to spot fake news early and avoid their propagation. Nevertheless, most fake news classification models are available only for English news, limiting the possibility of detecting fake news in other languages, such as Spanish. For this reason, this study proposes implementing a web service that integrates a deep learning model for the classification of fake news in Spanish. To determine the best model, the performance of several neural network architectures, including MLP, CNN, and LSTM, was evaluated using the F1 score., and LSTM using the F1 score. The LSTM architecture was the best, with an F1 score of 0.746. Finally, the efficiency of web service was evaluated, applying temporal behavior as a metric, resulting in an average response time of 1.08 seconds.
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基于人工神经网络的西班牙新闻假新闻分类Web服务
-社交网络等数字媒体的使用促进了假新闻的大规模传播。因此,一些机器学习技术,如人工神经网络,已经被用于假新闻的检测和分类。这些技术由于其学习能力而被广泛使用。此外,基于人工神经网络的模型可以很容易地融入社交媒体和网站,及早发现假新闻,避免其传播。然而,大多数假新闻分类模型仅适用于英语新闻,限制了检测其他语言(如西班牙语)假新闻的可能性。出于这个原因,本研究提出实现一个web服务,该服务集成了一个深度学习模型,用于西班牙语的假新闻分类。为了确定最佳模型,使用F1分数评估了几种神经网络架构(包括MLP、CNN和LSTM)的性能。, LSTM使用F1分数。LSTM架构表现最好,F1得分为0.746。最后,对web服务的效率进行了评估,将时间行为作为度量标准,得到的平均响应时间为1.08秒。
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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