2023
DOI: 10.1007/s00521-023-08352-z
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Social media bot detection with deep learning methods: a systematic review

Abstract: Social bots are automated social media accounts governed by software and controlled by humans at the backend. Some bots have good purposes, such as automatically posting information about news and even to provide help during emergencies. Nevertheless, bots have also been used for malicious purposes, such as for posting fake news or rumour spreading or manipulating political campaigns. There are existing mechanisms that allow for detection and removal of malicious bots automatically. However, the bot landscape … Show more

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Cited by 14 publications
(10 citation statements)
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“…Next, we attempted to remove spam or disingenuous users by considering their posting rate ( 46 ). As each tweet we gather contains information about the user at the time of the posting, we use this data to calculate their posting rate: number of tweets they have posted divided by the number of days the account has been active (using user “created at” and “user statuses count” fields).…”
Section: Methodsmentioning
confidence: 99%
“…Next, we attempted to remove spam or disingenuous users by considering their posting rate ( 46 ). As each tweet we gather contains information about the user at the time of the posting, we use this data to calculate their posting rate: number of tweets they have posted divided by the number of days the account has been active (using user “created at” and “user statuses count” fields).…”
Section: Methodsmentioning
confidence: 99%
“…Bot-detection is the process of identifying and distinguishing between automated bots and human users [125,126]. Bots can be detected using algorithms based on behavioural analysis, challenge-response authentication systems, and machine learning techniques [125].…”
Section: Integration With Bot-detection Systems and Decision-making S...mentioning
confidence: 99%
“…Bots can be detected using algorithms based on behavioural analysis, challenge-response authentication systems, and machine learning techniques [125]. Nevertheless, despite the constant progress in the domain of cybersecurity, bots remain a serious threat, since they can shape public opinion by spreading fake news and serving as an instrument for cyberbullying and harassment [125,126].…”
Section: Integration With Bot-detection Systems and Decision-making S...mentioning
confidence: 99%
See 1 more Smart Citation
“…In particular, as stated by Hayawi et al CNNs typically excel in classifying textual content and identifying abusive language, angry terms, and named entities. On the other hand, LSTMs and RNNs are particularly valuable for understanding the relationship between consecutive time point data [15]. Among these, it is worth mentioning the approach outlined in [16] involves the integration of three LSTM models and a fully connected layer.…”
Section: Related Workmentioning
confidence: 99%