  Designers of online deliberative platforms aim to counter the degrading
quality of online debates. Support technologies such as machine learning and
natural language processing open avenues for widening the circle of people
involved in deliberation, moving from small groups to "crowd" scale. Numerous
design features of large-scale online discussion systems allow larger numbers
of people to discuss shared problems, enhance critical thinking, and formulate
solutions. We review the transdisciplinary literature on the design of digital
mass deliberation platforms and examine the commonly featured design aspects
(e.g., argumentation support, automated facilitation, and gamification) that
attempt to facilitate scaling up. We find that the literature is largely
focused on developing technical fixes for scaling up deliberation, but may
neglect the more nuanced requirements of high quality deliberation. Current
design research is carried out with a small, atypical segment of the world's
population, and much research is still needed on how to facilitate and
accommodate different genders or cultures in deliberation, how to deal with the
implications of pre-existing social inequalities, how to build motivation and
self-efficacy in certain groups, and how to deal with differences in cognitive
abilities and cultural or linguistic differences. Few studies bridge
disciplines between deliberative theory, design and engineering. As a result,
scaling up deliberation will likely advance in separate systemic siloes. We
make design and process recommendations to correct this course and suggest
avenues for future research
