A Fast Algorithm for Hunting State-Backed Twitter Trolls-Reference-Cited by-同舟云学术

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A Fast Algorithm for Hunting State-Backed Twitter Trolls

Published:2022-09-02 Issue: Volume: Page:643-657
ISSN:2367-3370
Container-title:Pervasive Computing and Social Networking
language:
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Author:

Sahmoud Shaaban^ORCID,Abdellatif Abdelrahman^ORCID,Ragheb Youssof

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2840-6_49

Reference30 articles.

1. Kwak H, Lee C, Park H, Moon S (2010) What is Twitter, a social network or a news media? In: Proceedings of the 19th international conference on world wide web, pp 591–600

2. Wolfsfeld G, Segev E, Sheafer T (2013) Social media and the Arab spring: politics comes first. Int J Press Politics 18(2):115–137

3. Im J, Chandrasekharan E, Sargent J, Lighthammer P, Denby T, Bhargava A, Gilbert E (2020) Still out there: modeling and identifying russian troll accounts on twitter. In: 12th ACM conference on web Science, pp. 1–10

4. Sahmoud S, Safi H (2020) Detecting suspicious activities of digital trolls during the political crisis. In: 2020 IEEE international conference on informatics, IoT, and enabling technologies (ICIoT). IEEE, pp 532–537

5. Atanasov A, Morales GDF, Nakov P (2019) Predicting the role of political trolls in social media. arXiv:1910.02001

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1. A Unified Framework for Multi-Language Sentiment Analysis;2023 3rd International Conference on Computing and Information Technology (ICCIT);2023-09-13

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