LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection
Author:
Affiliation:
1. Xi'an Jiaotong University, Xi'an, China
2. University of Notre Dame, Notre Dame, IN, USA
3. University of Virginia, Charlottesville, VA, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3616855.3635843
Reference51 articles.
1. Twitter Bot Detection with Reduced Feature Set
2. Detect Me If You Can: Spam Bot Detection Using Inductive Representation Learning
3. David M Beskow and Kathleen M Carley. 2018. Bot-hunter: a tiered approach to detecting & characterizing automated activity on twitter. In Conference paper. SBP-BRiMS: International conference on social computing, behavioral-cultural modeling and prediction and behavior representation in modeling and simulation, Vol. 3.
4. Fame for sale: Efficient detection of fake Twitter followers
5. The Paradigm-Shift of Social Spambots
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