mobile geo social

having a busy decade

… “Newspapers Have Never Made Much Money From News” http://tcrn.ch/9S7DoE /via @techcrunch

old media has written some good stuff on mobile & geo & social today, but the problem (for old media) is i didn’t pay them for any of it

Facebook Open Graph API allows any website to easily post content to your Facebook Stream http://bit.ly/9r8MCF /via @WSJ

MySpace new mantra: “Discover and be Discovered” http://bit.ly/c9RzkC /via @USAtoday

Facebook Will Soon Allow Users to Share Location http://nyti.ms/aZgsIn /via @NYtimes

All Time Box Office Adjusted for Ticket Price Inflation http://bit.ly/aA05Aq and Avatar is not Bigger Than Ben Hur #oscars

RT @twitterAPI A place is not just a latitude and a longitude – it has a name http://bit.ly/b8L1Cp and an ID, but not a WOEID

Twitter allows more access to its Firehose API http://bit.ly/ancwoq which is now pumping out 8 MB per second /via @dps

“If you had to choose between a car and a mobile phone, which would you choose?” http://youtu.be/dFxEjNEJsnU [video] from 2004!

Google Patents Location-Based Ads http://j.mp/9qLuFx /via @rww while Apple Plans To Control iPhone Geo Ads? http://j.mp/9IVYdX /via @GigaOM

Senator Conroy, Minister of Truth, is caught filtering his tag cloud http://j.mp/cyKlva /via @michaelayates <– wow this is ▓▓ ▓▓▓

there’s nothing like a Google App Engine bill and a glass of shiraz to motivate some code optimisation

Bush walking the Warrimoo Track to Bobbin Head

I’m at the edge adventure centre (10 hudson avenue, Salisbury road, Castle Hill). http://4sq.com/a3Nl8w

happy to come home and find the boys playing Star Wars video games. the training complete nearly is.

In other news, GeoMeme now measures real-time local trends based on both MySpace and Twitter content.

GeoMeme uses the new Real-Time Stream API from MySpace to tap into the flood of geo-located updates being posted by MySpace users all around the world.

MySpace content is mashed up with tweets from a number of mobile Twitter apps, and located onto a Google Map. Local trends are identified using semantic analysis services from Yahoo.

A couple of example GeoMemes generated by all this real-time geo-located content: Rihanna beats Lady Gaga in New York, and Avatar beats Hurt Locker in Los Angeles.

I remember in January 2000, old media mogul Rupert Murdoch said he was not going to waste his money buying any ‘dotcom’ upstarts. The very next day, AOL bought Time Warner. Not the other way around!

Murdoch had apparently failed to grasp the significance of the interwebs.

However, ten years later Time Warner has regained its mojo and is now trying to offload a spent and jaded AOL. Did Murdoch get it wrong ten years ago, or did it simply take a whole decade for him to be proven right?

In 2009, the mob is rushing once again to the conclusion that Murdoch is losing his marbles, planning to charge for his online content and blocking the Googlebot from stealing it.

Personally I believe that Murdoch should worry less about the Googlebot, and more about how social media is turning his industry on its head.

The problem is that all of those dotcom upstarts have brought us information overload. There has been an exponential increase in the amount of information and content available to us, way beyond the capacity of the human brain to process.

The solution is social media, which empowers us to easily share the content we care about with our friends and contacts, and adds valuable metadata to that shared content, such as Likes or Retweet counts. This metadata helps us filter the signal from the noise, so that we can focus on just the best quality content from our trusted circle of friends.

This works great for movie reviews. People have always listened to the advice of friends when it comes to choosing what movie to watch. Social media simply provides an efficient and scalable way to do this.

The best example of this social filter is currently FriendFeed, although we can expect to soon see something equally impressive on Facebook. Twitter Search could do this even better if only it were possible to search the entire tweet history of just your friends, or a chosen social distance into your social graph, rather then merely search 7 days of the public timeline. I am hoping that the Google Social Search Experiment will enable this sort of social filter when Google completes its Twitter integration.

Back to Mr. Murdoch… Social media also works for the filtering of news content, however it’s more tricky than movie reviews because there is a need for trustworthy fact rather than mere opinion. This is why Eric Schmidt believes that figuring out how to rank real-time social content, perhaps based on a reliable measure of reputation and authority, is “the great challenge of the age“. It also explains why Twitter’s Retweet feature does not allow the original tweet to be modified, because this makes the Retweet count a more reliable indicator of authority.

So my advice to Rupert Murdoch and other media companies struggling with this; worry less about the Googlebot and more about social media. Focus on improving the quality of your content, so that people share it with their friends.

And if your own social media strategy is not delivering any tangible benefits, try moving it from your Marketing department to your Customer Service department. Use social media to listen more carefully to the needs of your customers, so you can improve the quality of your content to the point where a paid online content model becomes viable.

If Marketing and Customer Service argue about who owns the customer relationship, remind them both that thanks to social media it’s actually the customer who owns and controls the relationship with your business. Not the other way around!

I am pleased to announce the launch of GeoMeme, the fun way to measure and share real-time local twitter trends.

I got thinking about this when a recent Los Angeles earthquake was being measured in tweets per second rather than using the Richter Scale.

Then came the Magnitwude Calculator as a standard way to measure the magnitude of Twitter trends.

[Then came twotspot.com but that domain name was just too damn rude, so it was quickly renamed to GeoMeme.]

What does GeoMeme do?

GeoMeme measures real-time local twitter trends.

Tweeps are located on the map using public data from a number of iPhone twitter apps. When twitter launches its geolocation API, that will be used to locate even more people on the map.

GeoMeme measures and compares how many people on the map are tweeting about each of your two search terms:

The ‘magnitude’ of each search term is equal to the number of unique people tweeting per hour per square kilometer, so it increases when more people are tweeting in a smaller area.

Example: if 100 different people in an area of 10km² have tweeted about ‘love’ in the last 2 hours, the magnitude is 5.0 (100 divided by 10 divided by 2).

So you can search for ‘love’ and ‘hate’ and GeoMeme works out which one “beats” the other with the higher magnitude.

The default search terms are and smiley faces which provides a good measure of local happiness, as an example.

Can I use my iPhone?

Sure, or your iPod Touch. Here’s the screenshot:

Give me an example!

Thanks to some early coverage on The Register, Mashable, and Google Maps Mania, and winning Mashup of the Day on ProgrammableWeb, we’re off to a flying start. I’m glad GeoMeme is hosted on Google App Engine for scalability.

Here’s a selection of the most popular GeoMemes so far:

• beats in New York City
• Mega Shark beats Giant Octopus in LA
• Snow Leopard beats Windows 7 in Cupertino
• bridge beats swimming in San Francisco Bay
• wtf beats ftw in Washington

How does it all work?

I will leave the details of how it all works to another post, stay tuned for that.

2009 has already seen some big Twitter moments, including Michael Jackson’s death and memorial service, #iranelection, Oprah’s mainstreaming, and the race between @aplusk and @cnn to reach 1 million followers.

But how can we objectively measure and compare the scale of such things?

A little while ago I got thinking about this when a Los Angeles earthquake was being measured in tweets per second rather than using the Richter Scale.

And now here is my solution, the Magnitwude Calculator, which measures the current magnitude of tweets on any topic within any location.

Please have a fiddle. Type in a search term or select from the autocomplete list of currently trending topics, move the map around, and tell me what you think:

You can link directly to the Magnitwude Calculator at http://hitching.net/magnitwude

Today I spent an enjoyable couple of hours at the Australian Film Television and Radio School (AFTRS), learning about Multi Platform Content, and talking about Mobile Social Technology & Alternate Reality Gaming (ARG).

We examined some emerging mobile social technologies, and how they can enable new forms of story-telling. And we shared my personal journey into a Star Trek Alternate Reality Game which has so far involved me sending pictures of sheep to strangers in Paris, and which explains my recent cryptic Twitter and Facebook status updates. Well some of them anyway.

The slide deck is embedded below, and contains all the links for those of you who asked.

[Update 3 June 2009] OMG! I was chosen as one of the five finalists in the game. Here’s a video of Leonard Nimoy putting my name into the hat to pick the winner.

(more…)

Cloud computing is being sold as a hosting architecture to provide instantly scalable on-demand computing power, storage and bandwidth.

“The cloud’s resources scale with user demands. Pay only for what you use” says RackSpace, the latest to join the cloud gang.

One problem for the cloud gang, however, is that hosting has always struggled as a low margin commodity business.

Rackspace has just hired Robert Scoble to help spread the message, so we should expect this space to soon get hotter than an Sun SPARC with a loose heatsink.

But where exactly can some value be added in cloud computing, to increase the margins and keep Scoble funded so he can continue to filter the signal from the noise on FriendFeed? Okay, that’s slightly selfish but it’s an interesting question.

The interesting answer IMHO is cloud datasets.

Having useful datasets available in the cloud will unlock value from the data by allowing a new generation of mashup. These aren’t mashups that simply use data from remote web services, like plotting Craigslist ads onto a Google Map. This involves the mashup (joining) of datasets in the cloud using the power and speed of a relational database.

This cloud database approach might also provide Twitter and other owners of valuable data with a revenue model that doesn’t depend on advertising.

Here’s 10 cloud datasets that I’d personally like to mashup, to help explain:

1. Wikipedia. Funnily enough Amazon Web Services has just announced that it now offers a 66Gb dataset of Wikipedia. “The wiki markup for each article is transformed into machine-readable XML, and common relational features such as templates, infoboxes, categories, article sections, and redirects are extracted in tabular form.” One example: imagine the opportunities for a start-up social travel site to mashup its content with the wealth of travel information now available on Wikipedia. Massive.

2. Geonames. It bugs me that everyone who wants to use the geonames database needs to duplicate 800Mb of data. Move it into the cloud! Example: the travel site can now analyse reams of user-generated content (or Wikipedia content) for up-to-date categorization and geo-coding onto a map. Another example: most websites need a simple (but updated-more-often-than-you-would-think) list of countries on the rego form. Wouldn’t it be good if everyone used the same (geonames) list?

3. MaxMind IP address lookup. Turn an IP address into an always accurate city location. Example: targeted ad serving and traffic analysis.

4. Google PageRank. For any URL, what’s the PageRank measure of quality? If this is relational data (rather than from a remote web service), it can be combined with other measures of quality at database speeds.

5. Real-time stock market data.

6. Real-time sports data.

7. Dodgy credit card numbers.

8. Dodgy email addresses.

9. Twitter. Some of the above might be considered proprietary rather than public data, which brings me to Twitter and a potential revenue model for them and the cloud gang. If you’ve got valuable proprietary data like Twitter has got (some would say that’s all they’ve got), then replicating it into a relational cloud database will unlock more value than could ever be extracted (or sold) via a remote web API.

Example: when visiting an e-commerce site, it would be nice to see only the product reviews submitted by people I am following on Twitter, sequenced by a measure of quality based on how often those people have been retweeted. Of course, the cloud gang already have the billing infrastructure and monitoring in place to work out exactly how much proprietary data you have used, and what to charge you for it. Did I mention yet that Jeff Bezos is an investor in Twitter?

The advertising pie is not big enough to fund the whole of the interweb, so perhaps paid data consumption is the revenue model for Twitter and others. Businesses are happy to pay hosting providers for commodity services like CPU cycles and disk space, so why not pay Twitter (via a hosting provider) for valuable information? Did I mention yet that Jeff Bezos is an investor in Twitter?

10. This one is further out there; private foreign keys. Imagine the Twitter dataset including the email address of users, joined using that email address to a Facebook or Digg dataset, but not revealing that email address in the result set. That’s number 10 on my list. It would need to work in a similar way to Facebook’s FQL or Yahoo’s YQL or Google’s GQL, to expose enough information to be useful but to not expose anything that would violate privacy concerns. I hope to write some more about this and the privacy implications in another post.

So, who’s in the cloud gang? Google is well placed with AppEngine and plenty of valuable datasets to get started with. Amazon has all the billing machinery in place to sell proprietary data from Twitter and others. Sun now has MySQL which already supports remote replication and column-level permissions to enforce private foreign keys. And now RackSpace has Robert Scoble. This will be an interesting one.

Your micro-blogging on Twitter or FriendFeed is topical.

Your blog is quality.

Both are valuable. How can you combine the two?

1. Display your FriendFeed content on your blog using an embeddable widget:

2. Display your latest Twitter updates on your blog with a customized widget:

3. Combine the display of RSS feeds from FriendFeed and Twitter and elsewhere using an RSS plugin on your WordPress, Blogger, Moveable Type or TypePad blog.

4. Install Fresh From FriendFeed and Twitter – a WordPress plugin that keeps your blog always fresh by regularly adding your best recent content from FriendFeed or Twitter. Unlike the above solutions that only display content, Fresh From allows your visitors to search your micro-blogging content, and allows you to easily edit, tag and turn it into regular blog posts. Disclosure: I wrote this plugin, it got me thinking about this post.

5. Going the other way, FriendFeed makes it easy to import your blog’s RSS feed into FriendFeed.

6. Make sure your blog’s feed is using Media RSS extensions if you can, so FriendFeed picks up any media attachments. There are a couple of Wordpress plugins available that achieve this.

7. You can import your blog’s RSS feed into Twitter using services such as twitterfeed and RSS To Twitter:

8. Alex King’s Twitter Tools is a WordPress plugin that creates a tweet on Twitter whenever you post in your blog, with a link to the blog post. It can also create a daily or weekly digest post of your tweets on your blog.

9. Glenn Slaven’s FriendFeed Comments WordPress plugin will take the comments & ‘likes’ on your posts from FriendFeed and place them on the post that they’re related to on your blog.

10. If you are using the Disqus comment system on your WordPress, Blogger, Moveable Type or TypePad blog, comments can now be synchronised between your blog and FriendFeed.

What have I missed out? Comments please!

In 2006, a certain old-media tycoon reportedly asked Mark Zuckerberg, the 20-something founder of Facebook, “how can I build a social network like Facebook?”

Zuckerberg replied “You can’t!”

What Zuckerberg meant was that Facebook hadn’t set out to ‘build’ a social network. His billion dollar insight was that Facebook would instead provide online social tools to help existing friends and existing social groups to communicate easily, share photos, stalk, and poke each other.

Then in 2007, Facebook opened its app platform for third party developers to add additional social stuff to keep users on the site. Soon we were all happily throwing sheep at each other and spamming our friends with app invites.

App fatigue arrived in 2008. A redesign of the Facebook site removed some of the weeds, but the metrics spoke loudly, or rather their unit of measurement did; popular apps began to be listed according to ‘monthly active users’ rather than ‘daily active users’.

Slide, RockYou and iLike had been quick enough to make some money, however there was a long tail of apps without enough active users to generate a decent return on investment. The app gold rush was over.

It become apparent that there was less value in creating new social activities inside of a social site such as Facebook, and more value in socializing, or adding social data and context to, the existing sites that people are already using out there in the big wide web.

In other words, social data portability has arrived, and extends Zuckerberg’s earlier “You can’t!” insight; you can’t ‘build’ the platform because the web is the platform.

We are told that data portability is for people who want more control over their data and do not want to be locked in to any particular social network. In 2008, Facebook Connect and Google Friend Connect and MySpaceID have emerged as the big solutions from those wanting to port your social data, and profitably.

Facebook makes money from people viewing and clicking on ads on their website. Facebook Connect therefore allows you to export your Facebook profile and friend list to external sites, but really is intended to increase activity back on the Facebook website, by importing social information from those connected external sites back into your Facebook Feed for your friends to see. MySpaceID ditto.

Google however makes money from people clicking on ads anywhere, so Google Friend Connect can afford to remain socially agnostic, allowing users to identify themselves and their friends according to any network they belong to, and feed their external site activity into the social sites of their choice.

Being socially agnostic is more useful to more users in theory, but not yet in practice for Google Friend Connect. Even though it would be technically simple for Google to access your profile and friend lists using the Facebook Platform, what happened when Google submitted its Friend Connect app to Facebook for approval earlier in 2008?

Zuckerberg replied “You can’t!”, then added some fud about privacy.

This week however Google was able to make some progress on the theory of Friend Connect by launching an integration with Twitter. It’s now possible for you to use your Twitter identity and friends list on external sites powered by Friend Connect, which significantly increases the chances of spotting someone you know on those sites.

What’s interesting about this recent development to me is the apparent haste, including Google asking for my Twitter username and password directly, rather than waiting for Twitter to complete its long-awaited OAuth implementation. I’ve also seen more than the usual number of server errors and teething problems in this latest build of Friend Connect.

Maybe this is an indication that OAuth will be coming soon from Twitter, which would be fantastic.

Or maybe this is an indication that Twitter will be coming soon from Google; some visibility into Twitter data would be useful for Google in working out an acquisition price.

Or maybe this haste reveals how social data is such a hugely valuable chunk of information for Google to organize, and monetize, if ways can be found to use external social data to improve ad targetting without abusing the privacy of users and the privacy policies of their social networks.

In any event, there are interesting times ahead for social data portability. Users stand to benefit from a richer, more social, internet experience, as long as their privacy is not abused. And stay tuned on the social data portability battle between Facebook and Google and MySpace: who will work out how to best monetize external social data in 2009?