SOTAVerified

Twitter Bot Detection

Academic studies estimate that up to 15% of Twitter users are automated bot accounts [1]. The prevalence of Twitter bots coupled with the ability of some bots to give seemingly human responses has enabled these non-human accounts to garner widespread influence. Hence, detecting non-human Twitter users or automated bot accounts using machine learning techniques has become an area of interest to researchers in the last few years.

[1] https://aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/15587

Papers

Showing 1116 of 16 papers

TitleStatusHype
Twitter Bot Detection using Diversity Measures0
BotArtist: Generic approach for bot detection in Twitter via semi-automatic machine learning pipeline0
BotUmc: An Uncertainty-Aware Twitter Bot Detection with Multi-view Causal Inference0
Iteration over event space in time-to-first-spike spiking neural networks for Twitter bot classification0
Language-Agnostic Twitter-Bot Detection0
Twitter Bot Detection Using Bidirectional Long Short-term Memory Neural Networks and Word Embeddings0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RGTAcc92.1Unverified
2BotRGCNAcc89.6Unverified
3GATAcc87Unverified
4GCNAcc85.8Unverified
#ModelMetricClaimedVerifiedStatus
1DNA String Compression - Compression RatioAccuracy0.98Unverified