| [38] |
L. Zhou, et al. |
An exploratory study into deception detection in text-based computer-mediated communication |
Logistic regression |
content |
2003 |
| [36] |
C. Castillo, et al. |
Information credibility on twitter |
Decision tree |
Content and context |
2011 |
| [27] |
H. Zhang, et al. |
An improving deception detection method in computer- mediated communication |
SVM |
Content-based features |
2012 |
| [28] |
S. Afroz, et al. |
Detecting hoaxes, frauds, and deception in writing style online |
SVM |
Content-based features |
2012 |
| [41] |
K. Cho, et al. |
Learning phrase representations using RNN encoder-decoder for statistical machine translation |
Deep learning |
Content and context |
2014 |
| [29] |
E.J. Briscoe, et al. |
Cues to deception in social media communications |
SVM |
Content- based features |
2014 |
| [35] |
J. Ito, et al. |
Assessment of tweet credibility with LDA features |
Random forest |
Content and context |
2015 |
| [30] |
V. Perez-Rosas, R. Mihalcea |
Experiments in open domain deception detection, |
SVM |
Content- based features |
2015 |
| [37] |
M. Hardalov, et al. |
In search of credible news |
Logistic regression |
content |
2016 |
| [31] |
V. Rubin, et al. |
Fake news or truth? Using satirical cues to detect potentially misleading news |
SVM |
Content- based features |
2016 |
| [32] |
B.D. Horne, S. Adali |
This just in: fake news packs a lot in the title, uses more straightforward, repetitive content in the text body, more similar to satire than real news |
SVM |
Content-based features |
2017 |
| [12] |
E. Tacchini, et al. |
Some like it hoax: automated fake news detection in social networks |
Logistic regression |
content |
2017 |
| [8] |
W.Y. Wang |
Liar, liar pants on fire: a new benchmark dataset for fake news detection |
ensemble |
Content and context |
2017 |
| [43] |
S. Volkova, et al. |
Separating facts from fiction: linguistic models to classify suspiciously and trusted news posts on twitter |
RNN and CNN |
Content and context |
2017 |
| [42] |
N. Ruchansky, et al. |
a hybrid deep model for fake news detection |
Modified LSTM |
Content and context |
2017 |
| [8] |
W.Y. Wang |
Liar, liar pants on fire: a new benchmark dataset for fake news detection |
Deep learning |
Content and context |
2017 |
| [44] |
O. Ajao, et al. |
Fake news identification on twitter with hybrid CNN and RNN models |
RNN and CNN |
Content and context |
2018 |
