Content not yet available

This lecture has no active video or poster.

technical paper

AAAI 2024

February 24, 2024

Vancouver , Canada

SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter


snlp: other foundations of speech & natural language processing

ml: unsupervised & self-supervised learning

dmkm: applications

social network analysis & community mining

dmkm: graph mining

In the dynamic and rapidly evolving world of social media, detecting anomalous users has become a crucial task to address malicious activities such as misinformation and cyberbullying. As the increasing number of anomalous users improves the ability to mimic normal users and evade detection, existing methods only focusing on bot detection are ineffective in terms of capturing subtle distinctions between users. To address these challenges, we proposed SeGA, preference-aware self-contrastive learning for anomalous user detection, which leverages heterogeneous entities and their relations in the Twittersphere to detect anomalous users with different malicious strategies. SeGA utilizes the knowledge of large language models to summarize user preferences via posts. In addition, integrating user preferences with prompts as pseudo-labels for preference-aware self-contrastive learning enables the model to learn multifaceted aspects for describing the behaviors of users. Extensive experiments on the proposed TwBNT benchmark demonstrate that SeGA significantly outperforms the state-of-the-art methods (+3.5% ∼ 27.6%) and empirically validate the effectiveness of the model design and pre-training strategies. Our code and data are publicly available at



Next from AAAI 2024

BLiRF: Bandlimited Radiance Fields for Dynamic Scene Modeling
technical paper

BLiRF: Bandlimited Radiance Fields for Dynamic Scene Modeling

AAAI 2024

Sameera Ramasinghe and 3 other authors

24 February 2024

Stay up to date with the latest Underline news!

Select topic of interest (you can select more than one)


  • All Lectures
  • For Librarians
  • Resource Center
  • Free Trial
Underline Science, Inc.
1216 Broadway, 2nd Floor, New York, NY 10001, USA

© 2023 Underline - All rights reserved