Fake news detectionIn today's scenario, extracting information from websites is a challenging problem because of the increasing amount of information shared on the Internet. Recently, there has been an increase in the popularity of using social media platforms like Twitter, Facebook, Instagram, etc...
fake news detection using deep learning. Tech. rep., Technical Report, Stanford Univ Breiman L (2001) Random forests. Mach Learn 45(1):5–32 Article Google Scholar Cao J, Sheng Q, Qi P, Zhong L, Wang Y, Zhang X (2019) False news detection on social media. arXiv preprint arXiv:...
The dynamics and influence of fake news on Twitter during the 2016 US presidential election remains to be clarified. Here, we use a dataset of 171 million tweets in the five months preceding the election day to identify 30 million tweets, from 2.2 millio
Simultaneously, it is of high importance to analyze network activity patterns to understand and identify coordinated inauthentic behavior. This analysis will provide a foundation for targeted interventions and astroturfing detection mechanisms. Policy recommendations for social media platforms can be developed ...
Change-point detection To identify phases characterized by different combinations of the language categories, we identified change-points—periods in which the values of all categories varied considerably at once. To quantify such variations, for each language category c, we computed \(\nabla ({z}_...
Feature extraction and trend detection can be performed using machine learning algorithms. Big data tools and techniques are needed to extract relevant information from continuous steam of data originating from Twitter. The objectives of this research work are to analyze the relative popularity of ...
Detection of fake news text classification on COVID-19 using deep learning approaches Computational and Mathematical Methods in Medicine, 2021 (1) (2021), Article 5514220 View in ScopusGoogle Scholar Bedre, 2020 R. Bedre Mann-Whitney U test (Wilcoxon rank sum test) in Python [pandas and SciPy...
It comprises the detection of asset and numeric values, filtering, cleaning and removing unnecessary information; hashtag splitting; and text lemmatisation tasks. Table 1 illustrates the operation of the text processing stage. Table 1. Example of tweet after text processing. Empty CellTweet Before ...
Bow-tie detection In the following we briefly described the main steps of the detection of the bow-tie structure, following the procedure outlined in Ref.41. The first step is the identification of the greatest Strongly Connected Component (SCC) and then the identification of the nodes in the...
(machine learning) that allows a machine to be fed with raw data and automatically find the representations necessary for the detection or classification of a certain pattern [50]. ANNs are models that “teach” the machine certain patterns. The model is based on biological neural networks, and...