Posts Tagged ‘’

Has today been a good day?

Monday, April 16th, 2012

Last week, I came up with a quick hack, explained quite neatly by @crouchingbadger:

It was a bit of fun, even if it did seem to convince a group of commenters on engadget that I was a rage-fuelled XBox gamer. 🙂

There’s one big limitation with the hack, though: I don’t spend that much of my day in front of the TV.

It’s interesting to use it to measure my reactions to specific TV programmes or games. But thinking bigger, it’d be cool to try a hack that monitors me throughout the day to measure what kind of day I’m having.

I don’t spend much time in front of the TV, but I do spend a *lot* of time in front of my Macbook. And it has a camera, too!

What if my MacBook could look out for my face, and whenever it can see it, monitor what facial expression I have and whether I’m smiling? And while I’m at it, as I’ve been playing with sentiment analysis recently, add in whether the tweets I post sound positive or neutral.

Add that together, and could I make a reasonable automated estimate as to whether I’m having a good day?

(more…) for television

Wednesday, January 6th, 2010

One of the social network sites I’ve been using the longest is

(If you know what is, bear with me teaching you to suck eggs for a few paragraphs… it gets more interesting – honest!)

The idea of is that a background service captures (or “scrobbles“) the music that I listen to on my computer at home, on the mp3 player that I use in the car, and on my laptop in the office.

This means that I now have a large record detailing the music I’ve listened to over the last three years.

I do this for a few reasons, including:

  • The data is made available to me through a rich API, which means I’m free to play with it, as well as take advantage of the creations of others, such as the wonderful visualisations generated by lastgraph
  • I can see what my friends listen to, which is interesting, as well as being a good way to come across new music
  • use this detailed history of my music-listening tastes to make automated recommendations of other music that I might like

This is all a long-winded way of saying that I like I find it useful and interesting, and want the same for all the media that I consume – not just music.

I went looking for an equivalent for the books that I read in August 2008, and started using goodreads.

But what about the television that I watch? Could I create a scrobbler to capture what I watch on television? And then try and come up with a few examples of how I could share and visualise the data?

This question is where I started at Christmas… and after a few evenings of hacking some Python together, I’ve come up with: for television

Please go take a look. (needs Flash – sorry)

(more…) for books?

Friday, August 1st, 2008

my 'goodreads' bookshelf

I’m rubbish at choosing books to read, so recommendations from friends who are better read than I am are very useful. I enjoy using as a way to discover new music that I might like, so thought I’d look to see if you could get the same for books.

I’ve found two sites that I quite like:

This is a lovely site. Track the different books you have read, and are reading. Sort them into different “bookshelves” if you want to group them.

It’s got a ton of RSS feeds, and it’s focus absolutely seems to be to make it easier to track what your friends have read and are reading, what they like and don’t like.