  We present three models used to describe the recruitment of the undecided
population by pro-vax and no-vax factions. Starting from real-world data of
Facebook pages, we compare three opinion dynamics models that catch different
behaviours of the undecided population.
  The first one is a variation of the SIS model, where undecided position is
considered indifferent. Neutrals can be "infected" by one of the two extreme
factions, joining their side, and they "recover" when they lose interest in the
debate and go back to neutrality.
  The second model is a three parties Voters model: neutral pages represent a
centrist position. They lean their original ideas, that are different from both
the other parties.
  The last is the Bilingual model adapted to the vaccination debate: neutral
individuals are in agreement with both pro-, ad anti-vax factions, with a
position of compromise between the extremes ("bilingualism''). If they have a
one-sided neighbourhood, the convenience to agree with both parties comes out,
and bi-linguists can become mono-linguists.
  Our results depicts an agreement between the three models: anti-vax opinion
propagates more than pro-vax, thanks to an initial strategic position in the
online social network (even if they start with a smaller population). While
most of the pro-vaccines nodes are segregated in their own communities,
no-vaccines ones are entangled at the core of the network, where the majority
of undecided population is located.
  In the last section, we propose and compare some policies that could be
applied on the network to prevent anti-vax overcome: they lead us to conclude
that censoring strategies are not effective, as well as segregating scenarios
based on unfollowing decisions, while the addition of links in the network
favours the containment of the pro-vax domain, reducing the distance between
pro-vaxxers and undecided population.

Physics and Society;Computers and Society;Social and Information Networks