  Most of the information operations involve users who may foster polarization
and distrust toward science and mainstream journalism, without these users
being conscious of their role. Gab is well known to be an extremist-friendly
platform that performs little control on the posted content. Thus it represents
an ideal benchmark for studying phenomena potentially related to polarization
such as misinformation spreading. The combination of these factors may lead to
hate as well as to episodes of harm in the real world. In this work we provide
a characterization of the interaction patterns within Gab around the COVID-19
topic. To assess the spreading of different content type, we analyze
consumption patterns based on both interaction type and source reliability.
Overall we find that there are no strong statistical differences in the social
response to questionable and reliable content, both following a power law
distribution. However, questionable and reliable sources display structural and
topical differences in the use of hashtags. The commenting behaviour of users
in terms of both lifetime and sentiment reveals that questionable and reliable
posts are perceived in the same manner. We can conclude that despite evident
differences between questionable and reliable posts Gab users do not perform
such a differentiation thus treating them as a whole. Our results provide
insights toward the understanding of coordinated inauthentic behavior and on
the early-warning of information operation.
