Re-Identifying Banned Social Media Commenters With Machine Learning

Researchers from John Hopkins University have developed a Deep Metric approach to identifying online commenters who may have had previous accounts suspended, or may be using multiple accounts to astroturf or otherwise manipulate the good faith of online communities such as Reddit and Twitter.

The approach, presented in a new paper led by NLP Researcher Aleem Khan, doesn’t require that the input data be automatically or manually annotated, and improves on the results of previous attempts even where only small samples of text are available, and where the text was not present in the dataset at training time.

The system offers a simple data augmentation schema, with embeddings of different sizes trained on a high-volume dataset containing over 300 million comments covering a million different user accounts.

The model architecture of the John Hopkins re-identification system, where the essential components are 1) text content, 2) a sub-Reddit feature and 3) publication time/date. Source: https://arxiv.org/pdf/2105.07263.pdf

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