Your title slide should focus on the title of the talk. It should also include your name and affiliation, your logo if you have a cute one, possibly your blog or e-mail address if you want people to get in touch, and your twitter handle.
Here’s one of mine:
I usually mention that the beginning of the talk that if people have questions they can tweet them at me. This isn’t just because Twitter is a great way to get questions from people too shy to speak up (or who don’t get an opportunity). Here’s the hack: letting people know that you’ll be reading everything they say about your talk on Twitter makes them more likely to say nice things.
Further, in a multi-track conference, people who weren’t actually in your talk (or were there but not paying a lot of attention) will judge your talk based on what people on Twitter say about it. Get a few good tweets, and you’ve created the wide perception that you’ve given a good talk.
Of course, it helps to actually give a good talk. More on that soon.
This article is part of my series of speaking hacks for introverts and nerds. Read about the motivation here.
How can twitter be so popular and successful if it’s down all the time?
We base statements like this on the assumption that quality of a web application maps linearly to the application’s stability. This is obviously true for most sites most of the time, but things get interesting at the edge where rare, unpredictable failure actually enables more complex human interactions around the service.
Unlike e-mail, twitter etiquette doesn’t demand that you read or reply to every message from every person you follow (or who follows you). Combine that lightweight social touch with occasional technical issues and human communication patterns, and we start to see some interesting behavior.
Twitter’s lack of reliability as a platform allows us to use the technical failings to mask our own social imperfections. How often have you heard or said something like “I was sure I was following you” or “I must not have gotten that DM” or even “I think I tweeted that…”? Even just a small percent of users behaving this way changes the social expectations.
I’d love to construct an experiment to figure out whether this idea has merit, and if so, what the optimal amount of unavailable operations for social deniability is. Should 1 in 100 actions fail? 1 in 10,000? 1 in 1,000,000? Does it matter if any fail, as long as we believe that every so often failure occurs? (How often do things really get lost in the mail, anyway?)
It’s amusing to conceive of a system that succeeds socially because it often fails technically.
bc is a command-line calculator that’s fast and has the capacity to do some fairly complex math.
Try it out on the command line:
echo '100 / 10' | bc -l
I released the code under GPL, and it’s available on github: http://github.com/hmason/tweetbc.
John Cook mentions the bot and makes some great observations in his post three surprises with bc.
I gave a talk at the NYC Python Meetup on July 29 on Practical Data Analysis in Python.
I tend to use my slides for visual representations of the concepts I’m discussing, so there’s a lot of content that was in the presentation that you unfortunately won’t see here.
The talk starts with the immense opportunities for knowledge derived from data. I spent some time showing data systems ‘in the wild’ along with the appropriate algorithmic vocabulary (for example, amazon.com‘s ‘books you might like’ feature is a recommender system).
Once we can describe the problems properly, we can look for tools, and Python has many! Finally, in the fun part of the presentation, I demoed working code that uses NLTK to build a Twitter spam filter with 90% accuracy*.
Please let me know if you have questions or comments.
* I’ll post the code and training data shortly