Analytic Catalog

Tweets are inherently short, making it difficult for current state-of-the-art pre-trained language model-based detectors to accurately detect at what point AI starts to generate tweets in a given Twitter timeline. In this paper, we present a novel algorithm using stylometric signals to aid detecting AI-generated tweets. We propose models corresponding to quantifying stylistic changes in human and AI tweets in two related tasks: Task 1 - discriminate between human and AI-generated tweets, and Task 2 - detect if and when an AI starts to generate tweets in a given Twitter timeline. Our extensive experiments demonstrate that the stylometric features are effective in augmenting the state-of-the-art AI-generated text detectors.

Supported media types: Text

Tharindu Kumarage (Arizona State University) kskumara@asu.edu

Arslan Basharat (Kitware) semafor-sid-software@kitware.com

Source code: https://github.com/TSKumarage/Stylo-Det-AI-Gen-Twitter-Timelines

License: MIT License