Abstract
Online Social Media (OSM) have been substantially transforming the process of spreading news, improving its speed, and reducing barriers toward reaching out to a broad audience. However, OSM are very limited in providing mechanisms to check the credibility of news propagated through their structure. The majority of studies on automatic fake news detection are restricted to English documents, with few works evaluating other languages, and none comparing language-independent characteristics. Moreover, the spreading of deceptive news tends to be a worldwide problem; therefore, this work evaluates textual features that are not tied to a specific language when describing textual data for detecting news. Corpora of news written in American English, Brazilian Portuguese, and Spanish were explored to study complexity, stylometric, and psychological text features. The extracted features support the detection of fake, legitimate, and satirical news. We compared four machine learning algorithms (k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGB)) to induce the detection model. Results show our proposed language-independent features are successful in describing fake, satirical, and legitimate news across three different languages, with an average detection accuracy of 85.3% with RF.
Highlights
The way to deliver and consume information has changed significantly today
We created a dataset composed by news documents written in American English, Brazilian Portuguese, and Spanish to evaluate the problem of fake news detection grounded on language-independent features
We proposed the usage of an Out-Of-Vocabulary (OOV) feature, which uses a dictionary of words for a given language and counts the total words that are not found in this set and their frequencies on the text
Summary
Internet access has become more democratic and fast, paving the way to spreading the news around the world in seconds. In 2017, the Brazilian Institute of Geography and Statistics (IBGE) published a survey (https://biblioteca.ibge.gov.br/visualizacao/livros/liv101631_informativo.pdf) regarding the use of the Internet by Brazilians, of which 95.5% access the global network to send and receive messages through Online Social Media (OSM). OSM grew into one of the most popular communication technologies for various types of personal relationships [1,2]. Most people expose their opinions, talk to loved ones, and share professional information and news about the world [1,3]. It is common to quickly find accurate opinions on the same subject, which enables an increase of critical and abstract thinking on current issues
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