only when the effectiveness of early
detection will sufficiently increase
the cost of deception.
The future of social media ecosystems might already point in the
direction of environments where
machine-machine interaction is the
norm, and humans navigate a world
populated mostly by bots. We believe
there is a need for bots and humans
to be able to recognize each other, to
avoid bizarre, or even dangerous, situations based on false assumptions
of human interlocutors.j
The authors are grateful to Qiaozhu
Mei, Zhe Zhao, Mohsen JafariAsbagh,
Prashant Shiralkar, and Aram Galstyan
for helpful discussions.
This work is supported in part by the
Office of Naval Research (grant N15A-
020-0053), National Science Foundation (grant CCF-1101743), DARPA
(grant W911NF-12-1-0037), and the
James McDonnell Foundation (grant
220020274). The funders had no role
in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
j That Time 2 Bots Were Talking, and Bank
of America Butted In; www.theatlantic.com/
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Emilio Ferrara ( firstname.lastname@example.org) is a research assistant
professor at the University of Southern California, Los
Angeles, and a computer scientist at the USC Information
Sciences Institute. He was a postdoctoral fellow at
Indiana University when this work was carried out.
Onur Varol ( email@example.com) is a Ph.D. candidate at
Indiana University, Bloomington, IN.
Clayton Davis ( firstname.lastname@example.org) is a Ph.D. candidate
at Indiana University, Bloomington, IN.
Filippo Menczer ( email@example.com) is a professor of
computer science and informatics at Indiana University,
Alessandro Flammini ( firstname.lastname@example.org) is an
associate professor of informatics at Indiana University,
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