About: Hong Kong Protests: Using Natural Language Processing for Fake News Detection on Twitter

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Hong Kong Protests: Using Natural Language Processing for Fake News Detection on Twitter
Creator	Alvanou, Aikaterini Bezas, Konstantinos Kermanidis, Katia Maragoudakis, Manolis Papamichail, Asterios Zervopoulos, Alexandros
topic	covid:b4ca5ba1b22837424c5560c8052682f38cadbdf3#this
source	PMC
abstract	The automation of fake news detection is the focus of a great deal of scientific research. With the rise of social media over the years, there has been a strong preference for users to be informed using their social media account, leading to a proliferation of fake news through them. This paper evaluates the veracity of politically-oriented news and in particular the tweets about the recent event of Hong Kong protests, with the aid of a dataset recently published by Twitter. From this dataset, Chinese tweets are translated into English, which are kept along with originally English tweets. By utilizing a language-independent filtering process, relevant tweets are identified. To complete the dataset, tweets originating from valid sources are used as the real portion, with journalists rather than news agencies being considered, which constitutes a novel aspect of the methodology. Well-known Machine Learning algorithms are used to classify tweets, which are represented by a feature value vector that is extracted, selected and preprocessed from the datasets and mainly revolves around language use, with word entropy being a novel feature. The results derived from these algorithms highlight morphological, lexical and vocabulary differences between tweets spreading fake and real news, which are for the most part in accordance with past related work.
has issue date	2020-05-06(xsd:dateTime)
bibo:doi	10.1007/978-3-030-49186-4_34
has license	no-cc
sha1sum (hex)	b4ca5ba1b22837424c5560c8052682f38cadbdf3
schema:url	https://doi.org/10.1007/978-3-030-49186-4_34
resource representing a document's title	Hong Kong Protests: Using Natural Language Processing for Fake News Detection on Twitter
has PubMed Central identifier	PMC7256559
schema:publication	Artificial Intelligence Applications and Innovations
resource representing a document's body	covid:b4ca5ba1b22837424c5560c8052682f38cadbdf3#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/b4ca5ba1b22837424c5560c8052682f38cadbdf3
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