Category: Uncategorized

Posted: February 4, 2013 | Author: Hilary Mason | Filed under: blog | 4 Comments »

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:

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

…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.

Posted: January 29, 2013 | Author: Hilary Mason | Filed under: blog | 3 Comments »

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!

Posted: January 28, 2013 | Author: Hilary Mason | Filed under: blog | 3 Comments »

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.

Posted: January 19, 2013 | Author: Hilary Mason | Filed under: blog | Tags: academics, data, research | 5 Comments »

This post assumes that you want to share data. If you’re not convinced, don’t worry — that’s next on my list.

You and your academic colleagues will benefit from having at least a quick chat about the research questions they want to address. I’ve read every paper I’ve been able to find that uses bitly data and all of the ones that acquired the data without our assistance had serious flaws, generally based on incorrect assumptions about the data they had acquired (this, unfortunately, makes me question the validity of most research done on commercial social data without cooperation from the subject company).

The easiest way to share data is through your own API. Set generous rate limits where possible. Most projects are not realtime and they can gather the data (or, more likely, have a grad student gather the data) over the course of weeks. Using the API also has the side-effect of having the researchers bound only by your ToS.

When it’s not practical to use your API, create a data dump. At bitly, we have one open dataset, the 1.usa.gov data (clicks on 1.usa.gov links, stripped of all personally identifiable data). If I’m approached by students who are looking for a dataset for a homework project or someone who just wants to play, I point them there.

Often, though, researchers are investigating specific questions that require a specific sample of the data. We’ve worked with people investigating the spread of malware, studying the use of social networks during the Arab Spring, looking at how effective the media was during the Fukushima crisis in Japan, just for a few examples.

(Academics: every so often someone asks for “a copy of your database”. That’s not feasible for technical or business reasons. It’s more productive to describe your work and how you think the data would help. We’ll figure out what’s possible.)

When we do create and share a dataset, the data we share is always stripped of any potentially identifying information. Still, we require researchers to sign an NDA. The NDA basically states:

1. You will not share this data with anyone.

   This is not ideal for the research community, but necessary, according to our lawyers. We simply ask anyone who wants a copy of the same dataset for academic pursuits to sign the same NDA.

2. You may publish whatever you like.

   Academic freedom FTW.

3. We reserve the right to use anything that you invent while using our data.

   This is actually not because we expect people to come up with anything commercially useful to us that we haven’t already thought of, but to protect us should someone assert later that we used one of their ideas in a product.

And that’s it! To summarize, how to share data, in order of preference:

1. Your API
2. A public dataset
3. A not-public custom-built and legally protected dataset

Now, go out, share, and research.

Posted: January 8, 2013 | Author: Hilary Mason | Filed under: blog | Leave a comment »

We just released a bunch of social data analysis APIs over at bitly. I’m really excited about this, as it’s offering developers the power to use social data in a way that hasn’t been available before. There are three types of endpoints and each one is awesome for a different reason.

First, we share the analysis that we do at the link level. Every developer using data from the web has the same set of problems — what are the topics of those URLs? What are their keywords? Why should you rebuild this infrastructure when we’ve done it already? We’ve also added in a few bits of bitly magic — for example, you can use the /v3/link/location endpoint to see where in the world people are consuming that information from.

Second, we’ve opened up access to a realtime search engine. That’s an actual search engine that returns results ranked by current attention and popularity. Links are only retained for 24 hours, so you know that anything you see is actively receiving attention. If you think of bitly as a stream of stories that people are paying attention to, this search API offers you the ability to filter the stream by criteria like domain, topic, or location (“food” links from Brooklyn is one of my favorites) and pull out the content, in realtime, that meets your criteria. You can test it out with a human-friendly interface at rt.ly.

Finally, we asked the question — what is the world paying attention to right now? We have a system that tracks the rate of clicks – a proxy for attention – on phrases contained within the URLs being clicked through bitly. Then we can look and see which phrases are currently receiving a disproportionate amount of attention. We call these “bursting phrases”, and you can access them with the /v3/realtime/bursting_phrases endpoint. It’s analogous to Twitter’s trending topics, but based on attention (what people do), not shares (what they say), and across the entire social web.

I’m extremely excited to see what people build with these tools.