MIDS Capstone Project Fall 2016



We all love Slack. Slack creates a “virtual hallway” where ideas flow freely, questions are answered by the collective, and debate on topics of interest flourishes. This is wonderful. However, as working-students (or one might argue, members of the 21st century), we recognize that our limited time is no match for the deluge of information available on Slack. This leads to a serious case of slack anxiety. When there is all this useful and valuable information out there, finding the information you need becomes a case of finding a needle in a haystack.

Slack already provides a structure for organizing conversations: channels. Every team has a number of channels where conversation is housed. The channels are sorted by time of message. When a user opens a channel, the most recent messages appear first. The user can then scroll up to find older messages.


Because we were unsatisfied with Slack's default organizing structure, we created awaybot. A user simply invites awaybot to listen to one or more public channels. The bot listens in real time to the conversations as they unfold. It continuously uses natural language processing algorithms to divide the conversation into topics and summarize these topics. When users feel overwhelmed by the deluge of information on Slack, they simply query awaybot. The user provides a command, the name of the channel, and a time duration. The bot returns a high-level summary of the topics that transpired during that duration. It's never been easier to get summaries of the conversations you missed!


Data Science W210. Capstone - Lecture - 1 - 2016

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Last updated:

March 30, 2017