Speaking: 15 Minutes Or Less Per Idea

Let’s just admit it: very few people can pay attention to anything for more than fifteen minutes straight. Take advantage of this by never spending more than fifteen minutes on one idea during a talk.

That means that if your talk is 45 minutes long, you should break it down into at least three, perhaps four different ideas that you want to explore. I find it helpful to outline my talks this way on paper before I start putting slides together.

The ideas that you choose to explore within a talk should flow naturally together; there shouldn’t be a jarring transition. And if you find yourself belaboring the same point for more than fifteen minutes, try to break it down further.

This article is part of my series of speaking hacks for introverts and nerds. Read about the motivation here.


Speaking: Entertain, Don’t Teach

It’s tempting to think of a talk as the opportunity to take a body of knowledge and to educate your audience about that body of knowledge. You have something in your head and you want to get it into theirs.

Making education your top priority leads to terrible talks, with an unhappy audience that won’t retain any of the information you wanted them to remember, anyway. Instead, think about how you can create a compelling narrative through your material, layering in the deep technical content so that the most attentive listeners will take away a deep understanding while the people who are only half paying attention will, at the very least, enjoy the experience.

I can’t think of any talk that demonstrates this better than Gary Bernhardt’s WAT:

Remember: you’re entertaining, not educating.

This article is part of my series of speaking hacks for introverts and nerds. Read about the motivation here.


Speaking: Title Slides + Twitter = You Win

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:

talk_title_slide

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.


Speaking: Pick a Vague and Specific Title for Your Talk

Your title should be both vague and specific.

First, vague. You generally have to commit to give a talk months in advance of the actual event. You do not, however, generally have a talk written several months ahead of the actual event. You may also have a particular talk accepted, and then arrive at the conference and realize that what you had planned isn’t ideal for that audience. A vague title offers you a lot of flexibility in altering the content of your talk as conditions change without betraying the expectations of the audience based on the materials published earlier.

And then, specific. If your title is too vague (“Stuff and Junk”) people won’t be excited for your talk, and you’ll lack an audience entirely or won’t make it through the CFP process at all. Be specific about the frame of the talk, but leave the details vague.

For example, I recently gave a talk called “Human Behavior and the Social Web”. The title gives you a good idea what the talk will be about, but doesn’t commit me to sticking to any particular set of stories or material.

A particularly excellent example of this is Paul Graham’s PyCon 2012 keynote titled “Frighteningly Ambitious Startup Ideas” (which was also a really fun talk). That title gives you a specific frame to get very excited about, while leaving him with complete flexibility to alter the content up until the moment he got on stage.

This article is part of my series of speaking hacks for introverts and nerds. Read about the motivation here.


A (short) List of Data Science Blogs

I’m gathering a bundle of data science blogs to share. I’m looking to include blogs that update regularly and aren’t either personal opinion and project blogs (like this one) or primarily about marketing any particular company. Let me know if you have a favorite that I’ve forgotten.

If you’re just looking for one place to start, hop on over to Simply Statistics.


Why YOU (an introverted nerd) Should Try Public Speaking

You should be speaking at conferences.

Not an extrovert? Great. Speaking is for introverts!

We go to conferences to meet people (and learn things from people and find opportunities… from people). Meeting people at events takes a lot of energy, especially if you don’t look like the average dude at a conference. You have to explain your story to every single person you talk to, listen to theirs, and try to see if you have overlapping interests. It’s inefficient and takes a lot of time.

By being a speaker, you can tell your story just once, to everyone, and the people who are excited about what you have to say will come find you. You will actually save energy if you get up on stage.

It’s a great hack.

Before you say, “fine, but I’m not good at speaking”, please take a look at this:

People who are way less intelligent than you give excellent talks every day (you might not agree with what they say, but do try to appreciate the skilled delivery). If they can learn to do it, you can learn to do it.

A few years ago, I decided to learn how to speak. I started by studying people whose techniques I admired, and distilling their techniques down into algorithms that I can understand and try to apply to my own presentations. I’m very much a student but have really enjoyed talking to people about giving talks, so I’m going to do an experiment and post one speaking hack per week here on my blog on Fridays. Let me know what you think.


One Random Tweet, please.

One random tweet.

One random tweet.

It’s easy to believe that other people use social networks in the same way that you do. Your friends largely do use them the same way, which gives us an even more biased perspective.

Unfortunately, most networks don’t provide a way to explore representative communications that you’re not connected to.

Well, now you can! One random tweet, please.

Update: There were some slight technical difficulties due to hitting Twitter’s oembed rate limit. They should be repaired now.

(Note: between this and bookbookgoose.com I’m on a bit of a random kick lately. There’s a method to this madness!)


Experimenting With Physical Graphs

I ended up at NYC Resistor on Sunday, and decided to experiment with physical visualization of some data. I grabbed the clicks per second on keyphrases including my name (“hilary mason”) over the last six months, aggregated them by day, and made this graph:

attention on hilary mason

This is easy enough to construct for any phrase using the clickrate data that we’re calculating at bitly. I exported it from matplotlib in svg, added a label, and used the laser-cutter to create this out of plywood:

laser-cut time series

laser-cut time series

…which will shortly be adorning my desk at work. This is very simple, but there’s a lot of fun to be had with the physical manifestation of patterns we see in large amount of ephemeral data.


I’m a Dead Celebrity!

Hilary Mason, Bing Celebrity

Hilary Mason, Bing Celebrity

I have a Google alert set up for my name, and over the weekend it sent me here.

Update: Bing has removed the page and now redirects to a regular search.

It’s a page on Bing Celebrities, merging my information with information about Hilary Mason, the (now deceased) British actress. According to this page, I have starred in movies before I was born and made videos after I died. It’s my photo and her filmography.

It’s creepy, but it’s also intriguing. How does this happen?

The data is credited to AMG and inbaseline, whose domain, though linked directly from Bing, does not resolve. Entity disambiguation is certainly a challenge, but I expect more from Microsoft, with so much data and so many brains.

This kind of error makes it extremely clear that identity is not a solved problem. I’ve written a bit about identity slippage before. And that people are especially sensitive to errors about themselves. :)

This isn’t the first time a search engine has confused me with the other Hilary Mason, except the first time was cuil (remember that?) and it was her photo as Ugly Hag and my bio. I’ll take it Bing’s way, thank you!


Startups: Why to Share Data with Academics

Last week I wrote a bit about how to share data with academics. This is the complimentary piece, on why you should invest the time and energy in sharing your data with the academic community.

As I was talking to people about this topic it became clear that there are really two different questions people ask. First, why do this at all? And second, what do I tell my boss?

Let’s start with the second one. This is what you should tell your boss:

  • Academic research based on our work is a great press opportunity and demonstrates that credible people outside of our company find our work interesting.
  • Having researchers work on our data is an easy way to access highly educated brainpower, for free, that in no way competes with us. Who knows what interesting stuff they’ll come up with?
  • Personal relationships with university faculty are the absolute best way to recruit talent. If we invest a little bit of time in building a strong relationship with this professor, she’ll know the kind of people we’re looking for and send us her best students.

All of these points are valid, but they aren’t complete. As a startup, you’re mostly likely building a product at the intersection of a just-now-possible technology and a mostly-likely-ready market. The further the research in your field moves, the greater the number of possible futures for your company. Further, the greater the awareness of your type of technology in the community, the larger the market is likely to actually be.

Your company is one piece of a complex system, and the more robust that system becomes, the more possibilities there are for you. Share data, and you make the world a more interesting place in a direction that you’re interested in.