  The public interest in accurate scientific communication, underscored by
recent public health crises, highlights how content often loses critical pieces
of information as it spreads online. However, multi-platform analyses of this
phenomenon remain limited due to challenges in data collection. Collecting
mentions of research tracked by Altmetric LLC, we examine information retention
in the over 4 million online posts referencing 9,765 of the most-mentioned
scientific articles across blog sites, Facebook, news sites, Twitter, and
Wikipedia. To do so, we present a burst-based framework for examining online
discussions about science over time and across different platforms. To measure
information retention we develop a keyword-based computational measure
comparing an online post to the scientific article's abstract. We evaluate our
measure using ground truth data labeled by within field experts. We highlight
three main findings: first, we find a strong tendency towards low levels of
information retention, following a distinct trajectory of loss except when
bursts of attention begin in social media. Second, platforms show significant
differences in information retention. Third, sequences involving more platforms
tend to be associated with higher information retention. These findings
highlight a strong tendency towards information loss over time - posing a
critical concern for researchers, policymakers, and citizens alike - but
suggest that multi-platform discussions may improve information retention
overall.
