It detects different cultures and writing styles, not actual content. They train it with rightthink and wrongthink.
The system uses statistical methods to analyze writing characteristics, such as words used or more frequently used grammatical classes. These are then fed into a machine learning-based classifier, which is able to distinguish patterns of language, vocabulary and semantics of fake and real news, and automatically infer whether the content submitted to the platform is false. The models were trained with a massive database of real and false news and were exposed to the vocabulary used in over 100,000 articles published over the last five years. The researchers will aim to use the false news related to the upcoming presidential elections, as well as content related to the Covid-19 pandemic to further calibrate the models.
Prairie 1 points 3.2 years ago
It detects different cultures and writing styles, not actual content. They train it with rightthink and wrongthink.
The models were trained with a massive database of real and false news and were exposed to the vocabulary used in over 100,000 articles published over the last five years. The researchers will aim to use the false news related to the upcoming presidential elections, as well as content related to the Covid-19 pandemic to further calibrate the models.