Papers by Süleyman Gökhan TAŞKIN
Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Jan 29, 2021
In recent years, news and their sources have transformed with the increasing use of the internet.... more In recent years, news and their sources have transformed with the increasing use of the internet. Instead of traditional media platforms such as radio, television, newspaper and magazine, the use of social media platforms is also growing. While certain sources share the news in traditional media, every user can be a news source in social media. Fake news is news produced by fake or provocative users for the purpose of propaganda, provocation or misleading users. Since an ordinary social media user may share any news without any filter and they are usually interesting, a fake news can spread rapidly. For this reason, it is very important to detect fake news as soon as possible. Sometimes, fake news is detected by expert systems. It is not possible to detect fake news in a short time with such expert systems on social media platforms with very dense sharing traffic. This causes fake news to be shared by many people in a short time. Therefore, semiautomatic and automatic fake news detection systems can provide fake news detection in a shorter time than non-autonomous expert systems. Automatic detection systems are needed to be developed in order to overcome this shortcoming. In this study, we collect data from Twitter, annotate them whether they are fake or real news. Then, we use supervised (K-Nearest Neighbor-KNN, Support Vector Machines-SVM, and Random Forest) and unsupervised (K-means, Non-Negative Matrix Factorization-NMF, and Linear Discriminant Analysis-LDA) machine learning algorithms to detect fake news automatically. We run each algorithm 100 times and the average F1-score values were examined. The best results were obtained with 0.86 F1-score value in supervised learning algorithms. The F1-score value of unsupervised learning algorithms remained at 0.72.
Arabian Journal for Science and Engineering, 2021
Social media has affected people's information sources. Since most of the news on social media is... more Social media has affected people's information sources. Since most of the news on social media is not verified by a central authority, it may contain fake news for various reasons such as advertising and propaganda. Considering an average of 500 million tweets were posted daily on Twitter alone in the year of 2020, it is possible to control each share only with smart systems. In this study, we use Natural Language Processing methods to detect fake news for Turkish-language posts on certain topics on Twitter. Furthermore, we examine the follow/follower relations of the users who shared fake-real news on the same subjects through social network analysis methods and visualization tools. Various supervised and unsupervised learning algorithms have been tested with different parameters. The most successful F1 score of fake news detection was obtained with the support vector machines algorithm with 0.9. People who share fake/true news can help in the separation of subgroups in the social network created by people and their followers. The results show that fake news propagation networks may show different characteristics in their own subject based on the follow/follower network.
Academic Perspective Procedia, 2018
Data storage devices use a specific structure when storing or accessing the stored data. This is ... more Data storage devices use a specific structure when storing or accessing the stored data. This is called file system. Before beginning to store data in the data storage device, it must be formatted absolutely. While this data storage device is being formatted, the file system should be selected.NTFS, the most commonly used file system, keeps the files in the disk as a list in the MFT (Master File Table) file. Even if the file is deleted, the file record in this table will not be deleted. The physical location of the file can be found by looking at these MFT records.In this study, computer software was created on the basis of restoring the disk using a MFT file of the NTFS file system, and the result was examined.When national studies are examined, data recovery programs on the market are compared with each other. When international studies are examined, it is seen that NTFS and MFT concepts are explained but data recovery method using MFT records is not examined in detail.
Twitter üzerinde Türkçe sahte haber tespiti
Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi
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Papers by Süleyman Gökhan TAŞKIN