CrowdTarget: Target-based Detection of Crowdturfing in Online Social Networks

By Jonghyuk Song, Sangho Lee, Jong Kim. 2015

81 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, 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 Artificial Intelligence

1. Daphne Ippolito
2. Daniel Duckworth
3. Chris Callison-Burch
4. Douglas Eck
5. Philipp Koehn
6. Luke S. Zettlemoyer
7. John Wieting
8. Kevin Gimpel

In Information Systems

1. Chris Callison-Burch
2. Daphne Ippolito

In Natural Language Processing

1. Daphne Ippolito
2. Daniel Duckworth
3. Chris Callison-Burch
4. Douglas Eck
5. Kevin Gimpel
6. Philipp Koehn
7. John Wieting
8. Benjamin Van Durme

In Safety, Robustness & Interpretability

1. Chris Callison-Burch
2. Douglas Eck
3. Daniel Duckworth
4. Daphne Ippolito

In Signal Processing

1. Chris Callison-Burch
2. Douglas Eck
3. Jesse Engel
4. Yi-Hsuan Yang
5. Curtis Hawthorne
6. Yu-Siang Huang
7. Ian Simon
8. Olof Mogren

Citations in the corpus

• Automatic Detection of Generated Text is Easiest when Humans are Fooled (2019, background): “, 2018), influences elections (Allcott and Gentzkow, 2017), and undermines user trust (Wang et al., 2012; Song et al., 2015).”
• Human and Automatic Detection of Generated Text (2019, background): “Aside from news, crowdturfing of fake reviews on websites such as Amazon and Yelp significantly undermines user trust (Wang et al., 2012; Song et al., 2015).”