000			01584nam a22001577a 4500
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100			_aBastos, M., Walker, S. and Simeone, M. _929351
245			_aThe IMPED model: Detecting low-quality information in social media
260			_aAmerican Behavioral Scientist
300			_a65(6), May, 2021: p.863-883
520			_aThis article introduces a model for detecting low-quality information we refer to as the Index of Measured-diversity, Partisan-certainty, Ephemerality, and Domain (IMPED). The model purports that low-quality information is characterized by ephemerality, as opposed to quality content that is designed for permanence. The IMPED model leverages linguistic and temporal patterns in the content of social media messages and linked webpages to estimate a parametric survival model and the likelihood the content will be removed from the internet. We review the limitations of current approaches for the detection of problematic content, including misinformation and false news, which are largely based on fact checking and machine learning, and detail the requirements for a successful implementation of the IMPED model. The article concludes with a review of examples taken from the 2018 election cycle and the performance of the model in identifying low-quality information as a proxy for problematic content. – Reproduced
650			_aContent moderation, Diversity index, Partisanship, Misinformation, Web archive _927431
773			_aAmerican Behavioral Scientist
906			_aSOCIAL MEDIA
942			_cAR