A Review of Spam Detection in Social Media

With significant usage of social media to socialize in virtual environments, bad actors are now able to use these platforms to spread their malicious activities such as hate speech, spam, and even phishing to very large crowds. Especially, Twitter is suitable for these types of activities because it...

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Bibliographic Details
Published in2021 6th International Conference on Computer Science and Engineering (UBMK) pp. 383 - 388
Main Authors Yurtseven, Ilke, Bagriyanik, Selami, Ayvaz, Serkan
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.09.2021
Subjects
Artificial intelligence
Blogs
Computer science
COVID-19
deep learning
machine learning
NLP
Phishing
social media
Social networking (online)
spam
Virtual environments
Online AccessGet full text
ISSN2521-1641
DOI10.1109/UBMK52708.2021.9558993

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Summary:With significant usage of social media to socialize in virtual environments, bad actors are now able to use these platforms to spread their malicious activities such as hate speech, spam, and even phishing to very large crowds. Especially, Twitter is suitable for these types of activities because it is one of the most common social media platforms for microblogging with millions of active users. Moreover, since the end of 2019, Covid-19 has changed the lives of individuals in many ways. While it increased social media usage due to free time, the number of cyber-attacks soared too. To prevent these activities, detection is a very crucial phase. Thus, the main goal of this study is to review the state-of-art in the detection of malicious content and the contribution of AI algorithms for detecting spam and scams effectively in social media.
ISSN:2521-1641
DOI:10.1109/UBMK52708.2021.9558993