Life After @Horse: Cataloging Twitter Bots

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Slides for a lightning talk I gave at the SF Python Meetup in October: http://www.meetup.com/sfpython/events/140587192/. BotCache (www.botcache.com) is a data ethnography project about Twitter bots that bring us joy.

Technology Business

Life After @Horse:
Building a Catalog of Twitter Bots
An Xiao Mina / @thecivicbeat
Tech Ethnographer and Designer

‣ Flask

‣ NLTK

‣ Charts API

‣ MongoDB

‣ Some bots on Twitter are more popular than
most human beings. Why is that?

‣ Team: Alex Leavitt (USC Annenberg), Me,
Catherine Snow (Web Developer), Jared Adler
(Journalist), Chris Csikszentmihalyi (Advisor)

‣ Ethnographic research and storytelling project
that relies heavily on language analysis

‣ Keep our Python skills sharp

Talking About

Talking To

@stealthmountain

Talking About

Talking To

@horse_ebooks

@horse_ebooks

@capscop

Lexical Diversity and Sentiment Analysis

‣ Adapt for new Twitter API
‣ Develop better visualization tools
‣ Improve language analysis for social media
‣ Data + Ethnography: Use data to understand human
computer interactions that build communities and
make us smile

‣ ??

Recent advances in Deep Learning have opened new avenues for disrupting the traditional way we work, however many of these algorithms work well because they are designed to uncover subtle relationships in data. Even if data features such as ethnicity, gender or race are explicitly removed from training. AI models can still learn bias through over-fitting on highly correlated features and missing information. As AI becomes increasingly democratized the implications of Bias on production AI is more relevant than ever. This session will demonstrate some of the constraints of state of the art AI and provide an overview of how to incorporate the ML interpret-ability toolkit into your workflow to help ensure that your projects don't amplify existing societal biases with unintended consequences, such as ethnic, gender or racial discrimination.

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This does not cover the animations or videos, because the Youtube (included) video has bugs related to the builds/transitions, it might be a good idea to download the slides separately and follow along in that window. (When the official conference video is available, I'll upload that instead.) Abstract: http://www.northeastphp.org/talks/view/156/Keynote-Ten-Evil-Things-Features-Engineering-at-Wikipedia A framework for understanding what, how, and why Features engineering is done on Wikipedia. Wikipedia is the 5th largest website on the internet. The problem: the community that builds the "sum of all knowledge" is shrinking. The goal of Features Engineering is to reverse that editor trend. This talk covers 10 concepts in the modern web that Wikipedia is leveraging to reverse the decline.

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