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Detecting and tracking political abuse in social media (2011)
| Venue: | In Proceedings of ICWSM |
| Citations: | 33 - 4 self |
BibTeX
@INPROCEEDINGS{Ratkiewicz11detectingand,
author = {J. Ratkiewicz and M. D. Conover and M. Meiss and A. Flammini and F. Menczer},
title = {Detecting and tracking political abuse in social media},
booktitle = {In Proceedings of ICWSM},
year = {2011}
}
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Abstract
We study astroturf political campaigns on microblogging platforms: politically-motivated individuals and organiza-tions that use multiple centrally-controlled accounts to create the appearance of widespread support for a candidate or opin-ion. We describe a machine learning framework that com-bines topological, content-based and crowdsourced features of information diffusion networks on Twitter to detect the early stages of viral spreading of political misinformation. We present promising preliminary results with better than 96% accuracy in the detection of astroturf content in the run-up to the 2010 U.S. midterm elections. 1
Keyphrases
social medium political abuse information diffusion network astroturf content multiple centrally-controlled account viral spreading astroturf political campaign political misinformation early stage u.s. midterm election crowdsourced feature widespread support politically-motivated individual preliminary result
