  In the digital era, information consumption is predominantly channeled
through online news media disseminated on social media platforms. Understanding
the complex dynamics of the news media environment and users habits within the
digital ecosystem is a challenging task that requires at the same time large
bases of data and accurate methodological approaches. This study contributes to
this expanding research landscape by employing network science methodologies
and entropic measures to analyze the behavioural patterns of social media users
sharing news pieces and dig into the diverse news consumption habits within
different online social media user groups. Our analyses reveal that users are
more inclined to share news classified as fake when they have previously posted
conspiracy or junk science content, and vice versa, creating a series of
misinformation hot streaks. To better understand these dynamics, we used three
different measures of entropy to gain insights into the news media habits of
each user, finding that the patterns of news consumption significantly differ
among users when focusing on disinformation spreaders, as opposed to accounts
sharing reliable or low-risk content. Thanks to these entropic measures, we
quantify the variety and the regularity of the news media diet, finding that
those disseminating unreliable content exhibit a more varied and at the same
time a more regular choice of web domains. This quantitative insight into the
nuances of news consumption behaviours exhibited by disinformation spreaders
holds the potential to significantly inform the strategic formulation of more
robust and adaptive social media moderation policies.
