USE-Based Deep Learning Approach to Detect Spammers on Twitter
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0769-4_36
Reference30 articles.
1. Dhaka D, Mehrotra M (2016) Cross-domain spam detection in social media: a survey. In: International conference on emerging technologies in computer engineering. Springer, Singapore, pp 98–112
2. https://www.inputmag.com/culture/twitter-suspended-500k-accounts-for-childsexual-exploitation-last-year-transparency. Last accessed 01 June 2022
3. Bandhakavi A, Wiratunga N, Deepak P, Massie S (2014) Generating a word-emotion lexicon from emotional tweets. In: Proceedings of the third joint conference on lexical and computational semantics (*SEM 2014), pp 12–21
4. Kakar S, Dhaka D, Mehrotra M (2021) Value-based behavioral analysis of users using Twitter. In: Inventive communication and computational technologies, vol. 145. Springer, Singapore, pp 283–294
5. Kakar S, Dhaka D, Mehrotra M (2021) Value-based retweet prediction on Twitter. Informatica 45(2)
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