Our experiments show that it is diffi- cult to differentiate solidly fake news spreaders on Twitter from users who share credible information leaving room for
sible fake news spreaders on Twitter as a first step towards preventing fake news and checked all the tweets with the list of fake news identified in the ...
3 июл. 2017 г. Throughout the most recent US Presidential election in. 2016 Twitter was used prolifically by both the Hillary. Clinton and Donald Trump ...
25 сент. 2020 г. ULMFiT for Twitter Fake News Spreader. Profiling. Notebook for PAN at CLEF 2020. 1H. L. Shashirekha 2F. Balouchzahi. Department of Computer ...
Keywords: Author Profiling · Fake News · Twitter · Spanish · English. 1 Introduction. In the past few years social media has been changing how people
25 сент. 2020 г. In this notebook we summarize our work process of preparing a software for the PAN 2020 Profiling Fake News Spreaders on Twitter task. Our.
However spreading of news in so- cial media is a double-edged sword because it can be used either for beneficial purposes or for bad purposes (fake news).
3 сент. 2018 г. Fake News focuses on classifying the credibility of a tweet post. It makes and presents some scores and their interpretation. Online news have ...
26 окт. 2022 г. To understand why internet users spread fake news online many studies have focused on individual drivers
This paper develops a method for automating fake news detection on Twitter by learning to predict accuracy assessments in two credibility-focused Twitter.
Does fake news spread more quickly on Twitter than real news?
A new study by three MIT scholars has found that false news spreads more rapidly on the social network Twitter than real news does — and by a substantial margin.
Are false stories more likely to be retweeted than true stories?
The study provides a variety of ways of quantifying this phenomenon: For instance, false news stories are 70 percent more likely to be retweeted than true stories are. It also takes true stories about six times as long to reach 1,500 people as it does for false stories to reach the same number of people.
How to classify tweet text?
To classify the tweet text, this study uses various natural language processing techniques to pre-process the tweets and then apply a hybrid convolutional neural network–recurrent neural network (CNN-RNN) and state-of-the-art Bidirectional Encoder Representations from Transformers (BERT) transformer.
Fake News Spreader Detection on Twitter using Character N-Grams