You should also pitch it to John Keefe, who heads up WNYC's excellent Data News Team.

On Wed, Feb 11, 2015 at 12:02 PM, Samantha Sunne <[address removed]> wrote:

Murray, have you pitched this to the Post or Daily News or Gothamist? They publish people's data and visualization work outright sometimes. It might catch the attention of local government, too.

On Wed, Feb 11, 2015 at 11:57 AM, Marc Shifflett <[address removed]> wrote:

<emoji_u1f44d.png> You forced me to get my glasses

I notice Airbnb sends cancellations through their reviews system. Would this skew activity a bit? 

I was just in New Orleans. Local property owners would love to see this. 

Marc

On Feb 11, 2015, at 9:19 AM, Chris Henrick <[address removed]> wrote:

Seriously awesome work! 

To add to John's suggestions on how to improve the data rendering across browsers I think CartoDB would be a great use case. This is because it serves the geo-data as a Tile Layer rather than SVGs which prevents the browser from possibly bogging down with 30K points (a friend of mine stated this was happening when viewing on FireFox). CartoDB also allows for anyone to dl the data, not to mention any changes or updates you make to the data will be reflected in your visualization in real time.

just my two cents, but very nice work! 

-Chris L Henrick

-------------------------

MFA Candidate, Design & Technology

Parsons, The New School For Design

Cartographic Design Portfolio - Thesis Blog - MFA DT Blog

Github: @clhenrick Twitter: @chrislhenrick

“Whenever I see an adult on a bicycle, I no longer despair for the future of the human race.”

— H.G. Wells

On Wed, Feb 11, 2015 at 9:03 AM, Murray <[address removed]> wrote:

The main goal of my project was to release the data and to provide an easy to use tool to see the major issues with Airbnb in NYC. 

I'm interested in some of the other things that you mentioned (correlation with rent increases, property prices) but I think it would take time to prove anything and would just be a correlation amongst many other factors as opposed to a  significant reduction in housing supply which was a lot easier to build the initial story around. I was going to add a layer to the map with  metrics like price/sq ft; rent increases; property prices increased: which would allow the user to see correlations, but decided the initial release of the tool didn't need this. 

I would encourage you to use the data yourself if you wanted to pursue some additional analysis/valuations. 

No, can't tell whether listings are owned or rented - would need the exact address and a real name for that...

On Feb 11, 2015, at 4:06 AM, James Beveridge <[address removed]> wrote:

This is incredibly well done. +1 for tutorials! Producing work like could be an entire online course.

Murray, are you aware of any analysis correlating airbnb availability per neighborhood over time to either available rental property or average new rental rates? It would be powerful to be able to show that each new airbnb rental entering the market contributes to XX fewer available rentals or $YY increase in average rent. From the boom in airbnb activity starting in 2014 this has to be a nontrivial factor in increasing rents.

Also, do you have any way of determining whether airbnb properties are owned or rented by their hosts? It would be interesting to know what % of hosts are solely using airbnb as an arbitraged revenue source vs renting property they own themselves, though the impact on housing prices might be much the same.

Thanks,

James

Sent from my iPhone

On Tue, Feb 10, 2015 at 10:55 AM, Murray <[address removed]> wrote:

No technical tutorials (yet), but I relied heavily on D3, crossfilter, leaflet and python documentation, tutorials and posts. Will try and post the ones that I benefited from most. This is my first project with any and all of these technologies, so it's definitely something "anyone" can do.

 

On Tuesday, February 10,[masked]:48 AM, Alex P <[address removed]> wrote:

This is great, thanks Murray! I don't suppose you have a tutorial of how you managed it?

On Tue, Feb 10, 2015 at 9:11 AM, Murray <[address removed]> wrote:

Hi All,

I'm proud to announce a "civic hacking" project I've been working on for the last couple of months. 

Although it doesn't use "Open Data", it uses data I "compiled" from the Airbnb site about a month ago of ALL NYC listings (including availability calendars and reviews).

I've built a site (http://insideairbnb.com) that allows you to easily visualize how Airbnb is being used in NYC, with particular reference to the dimensions that impact housing (the type of property, availability, activity, as well as hosts with multiple listings).

Feel free to give feedback, share it around, and of particular interest to this group, DOWNLOAD the data (http://insideairbnb.com/get-the-data.html)...

Special thanks to Noel Hidalgo and Chris Whong for help and assistance, and a few others for your feedback at a couple of civic hacking nights I attended in December.

Enjoy!

http://insideairbnb.com

  

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Murray Cox

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