Stack Speaks: Talking text mining and developer data on the Cause A Scene podcast

Stack Speaks is a chance for us to highlight interesting appearances, talks, and presentations from Stack Overflow employees. 

Recently, I sat down with Kim Crayton as a guest on her #causeascene podcast. Kim is a coach, speaker, and leader who helps tech organizations put their values into operation and learn how to identify organizational barriers to inclusion. Kim’s podcast covers a lot of important territory for those of us who work in tech, and I was so happy to speak with her. We spent most of our time talking about Stack Overflow, and specifically this year’s Developer Survey. We talked about how and why we have been working to shift our attitude and language around the survey results, to more accurately describe its scope while still affirming its impact and value. We also explored what it means to reevaluate functionality of our site, a decade into its existence. We chatted about the positive impact of Stack Overflow for people in technical spaces, the ways in which its impact has not been so positive and has caused harm, and the questions we’re asking ourselves today.

“What are we doing in our public community? Are we thinking about both learners and experienced developers from broad backgrounds? In what ways are we creating a welcoming space for both?”

At the end of the podcast, we spent some time on another interest of mine, text mining and natural language processing. I put text mining using tidy data principles to work often in my daily data science tasks at Stack Overflow, so I love getting to share more broadly about these techniques! Enjoy the episode, and if you want to learn more about the work of data scientists, check out Cross Validated, a home for questions on data science, machine learning, and statistics.

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