Abstract
Automatic fake news detection is an im-portant, yet very challenging topic. Tradi-tional methods using lexical features haveonly very limited success.This paperproposes a novel method to incorporatespeaker profiles into an attention basedLSTM model for fake news detection.Speaker profiles contribute to the model intwo ways. One is to include them in the at-tention model. The other includes them asadditional input data. By adding speakerprofiles such as party affiliation, speakertitle, location and credit history, our modeloutperforms the state-of-the-art method by14.5% in accuracy using a benchmark fakenews detection dataset. This proves thatspeaker profiles provide valuable informa-tion to validate the credibility of news articles.
| Original language | English |
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| Title of host publication | Proceedings of the The 8th International Joint Conference on Natural Language Processing |
| Place of Publication | Taipei, Taiwan |
| Publisher | Asian Federation of Natural Language Processing |
| Pages | 252-256 |
| Number of pages | 5 |
| Volume | 2 |
| ISBN (Print) | 978-1-948087-01-8 |
| Publication status | Published - 27 Nov 2017 |
| Event | The 8th International Joint Conference on Natural Language Processing - Taipei, Taiwan Duration: 27 Nov 2017 → 1 Dec 2017 |
Conference
| Conference | The 8th International Joint Conference on Natural Language Processing |
|---|---|
| Country/Territory | Taiwan |
| City | Taipei |
| Period | 27/11/17 → 1/12/17 |