  Recent research brought awareness of the issue of bots on social media and
the significant risks of mass manipulation of public opinion in the context of
political discussion. In this work, we leverage Twitter to study the discourse
during the 2018 US midterm elections and analyze social bot activity and
interactions with humans. We collected 2.6 million tweets for 42 days around
the election day from nearly 1 million users. We use the collected tweets to
answer three research questions: (i) Do social bots lean and behave according
to a political ideology? (ii) Can we observe different strategies among liberal
and conservative bots? (iii) How effective are bot strategies? We show that
social bots can be accurately classified according to their political leaning
and behave accordingly. Conservative bots share most of the topics of
discussion with their human counterparts, while liberal bots show less overlap
and a more inflammatory attitude. We studied bot interactions with humans and
observed different strategies. Finally, we measured bots embeddedness in the
social network and the effectiveness of their activities. Results show that
conservative bots are more deeply embedded in the social network and more
effective than liberal bots at exerting influence on humans.
