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Multitask learning for blackmarket tweet detection

  • Published:2019-08-27 Issue: Volume: Page:
  • ISSN:
  • Container-title:Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
  • language:
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Author:

Arora Udit1,Paka William Scott1,Chakraborty Tanmoy1

Affiliation:

1. IIIT-Delhi, New Delhi, India

Funder

Infosys Centre of AI, IIIT-Delhi, India

DST

Ramanujan Fellowship

Publisher

ACM

Reference16 articles.

1. Retweet us, we will retweet you: Spotting collusive retweeters involved in blackmarket services;Dutta H. S.;ASONAM. IEEE,2018

2. CoReRank

3. BotOrNot

4. The many faces of link fraud;Shah N.;ICDM. IEEE,2017

5. Twitter spam detection based on deep learning;Wu T.;Proceedings of the Australasian Computer Science Week Multiconference,2017

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1. Improving Supervised Learning in Conversational Analysis through Reusing Preprocessing Data as Auxiliary Supervisors;INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION;2022-11-07

2. Misreporting and Fake News Detection Techniques on the Social Media Platform;Highlights in Science, Engineering and Technology;2022-08-26

3. C-ANN: a deep leaning model for detecting black-marketed colluders in Twitter social network;Neural Computing and Applications;2022-01-20

4. Machine Learning-Based Identification of Collusive Users in Twitter Stream;2021 International Conference on Computational Performance Evaluation (ComPE);2021-12-01

5. Blackmarket-Driven Collusion on Online Media: A Survey;ACM/IMS Transactions on Data Science;2021-11-30
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