  Most people participate in meetings almost every day, multiple times a day.
The study of meetings is important, but also challenging, as it requires an
understanding of social signals and complex interpersonal dynamics. Our aim
this work is to use a data-driven approach to the science of meetings. We
provide tentative evidence that: i) it is possible to automatically detect when
during the meeting a key decision is taking place, from analyzing only the
local dialogue acts, ii) there are common patterns in the way social dialogue
acts are interspersed throughout a meeting, iii) at the time key decisions are
made, the amount of time left in the meeting can be predicted from the amount
of time that has passed, iv) it is often possible to predict whether a proposal
during a meeting will be accepted or rejected based entirely on the language
(the set of persuasive words) used by the speaker.
