Detecting opinion spams and fake news using text classification

By Hadeer Ahmed, Issa Traoré, Sherif Saad. 2018

469 citations recorded by the source corpus.

Subfields: Information Systems, Sociology and Political Science, Natural Language Processing, Safety, Robustness & Interpretability, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Suhail Yousaf
2. Iftikhar Ahmad
3. Muhammad Ovais Ahmad
4. Muhammad Nadeem Yousaf
5. Alex Nichol
6. Prafulla Dhariwal

In Sociology and Political Science

1. Suhail Yousaf
2. Iftikhar Ahmad
3. Muhammad Ovais Ahmad
4. Muhammad Nadeem Yousaf

In Natural Language Processing

1. Suhail Yousaf
2. Iftikhar Ahmad
3. Muhammad Ovais Ahmad
4. Muhammad Nadeem Yousaf
5. Alex Nichol
6. Prafulla Dhariwal

In Safety, Robustness & Interpretability

1. Suhail Yousaf
2. Iftikhar Ahmad
3. Muhammad Ovais Ahmad
4. Muhammad Nadeem Yousaf
5. Alex Nichol

In Signal Processing

1. Alex Nichol
2. Prafulla Dhariwal
3. Jonathan Ho
4. Yilun Du
5. David J. Fleet
6. Mohammad Norouzi
7. Emiel Hoogeboom
8. Tim Salimans

Citations in the corpus

• Diffusion Models Beat GANs on Image Synthesis (2021, background): “images are a more direct concern, and detecting and mitigating propaganda and fake news based on generative models is an ongoing area of research [4, 3, 5].”
• Fake News Detection Using Machine Learning Ensemble Methods (2020, methodology): “The first dataset is ISOT Fake News Dataset [23]; the second and third datasets are publicly available at Kaggle [24, 25].”