Archive for the ‘geolocation’ Category
Gather more foursquare Likes
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Gather more foursquare Likesfoursquare added a feature to allow people to like checkins without a 4sq account. Seeing the potential for abuse I tried to see whether I could like my own checkin, so I fired up a clean browser so I could try and like a checkin and I was unable to as it asked me to login.
Does it work for you? Your best check-ins, now with more likes
Remember that time that barista made a foam art panda bear in your latte that looked exactly like a certain botched fresco and you took a picture with your check-in, and tweeted it, and blasted it out …
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FourSquare is trying to get me High
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FourSquare is trying to get me HighI live down the road from an Amsterdam Coffee Shop, one of those places were you can buy weed. foursquare points to it and asks me whether I would like to try a new spot?
Sorry foursquare, no I do not want to get high.  |
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FourSquare Tips containing Adverts #gps #geolocation #jobs
I recently started noticing that certain locations that I check into had tips which were usually for companies close to that location. An example it the ING Bank advertising their career site when you are in the discount electronics shop across the road or in the mall. Or Heineken informing you that you can link your FourSquare profile to your Heineken profile.
Image source: me
Playing with DataSift #curation
Some weeks ago I got my beta access to DataSift, I was happy to get access and didn’t see time to use it. Yesterday evening I played with it for the first time, it was quite interesting to discover something which I suspected which was that they had their own query/modeling language called FSDL. It contains the ability to do queries over the data, including data over a map geo coordinates, which means I can do some complex queries to get the needed data. Once I submitted the query I was given an option to buy access to a stream of the data.
I believe less is more, so I’m happy to see that they released their service with support for quite a number of services – Twitter, Tweetmeme, Buzz, Digg, RSS feeds – and makes it possible to do matches on different fields within the data set. And they have made the possibility to add your own datasources, which can be modeled in the same way as the existing datasources.
Above you can see an example FSDL that I wrote for the keyword Snypher.
A great tool, with many uses.
GeoLocation and Data Leakage Prevention #foursquare #gowalla #dlp #security
To make it clear I’m not speaking of the information being broadcast by employees to social media, I’ve been musing on the risks of Data Leakage Prevention (DLP) of third party employees such as consultants using geolocation services such as foursquare, brightkite or Gowalla. Many companies – very usual with consulting companies – have requirements that their employees do not release the names of customers or customer data to the media, this includes releasing data pertaining to services which are offered, these policies have yet to be fully enforced when it comes to geolocation services.
For a consulting company, such as mine, which has a reasonably diverse offering of security software to customers, yet for a company who is known as a RSA, Oracle or Novell integrator it can create risk vectors when it is known that their in house software leans towards a specific platform. In this way it could become public knowledge that a company uses a specific product, and based on the date of the visits information pertaining to versions can be inferred.
Naturally posting the geolocation to a service such as foursquare doesn’t necessarily open security holes, and it may not violate the standard of “Due Care” in that it is not necessarily negligent to release this information. Although it might not be in the best interest of the customer to make this public knowledge.
On the other had there is also an advantage to be had, in any cases of disputes a travel log like an entry log can be produced as corroborating evidence, although without direct evidence this merely proves where the physical access control device was and not the location of the disputed individual. And only circumstantially where the owner was located.
Your thoughts?
Image source: me
Google Follow Finder Algorithm Issues #google #twitter [UPDATE]
Google Labs’ Follow Finder, announced on the 14th says of itself:
Follow Finder analyzes public social graph information (following and follower lists) on Twitter to find people you might want to follow.
It actually does much more than it promises.
“Tweeps you might like” probably does some geographic profiling, as I probably have 67 Dutch people I follow[1] of 2000+ – with the exception of some political figures of the Dutch Green party – yet I have 8 Dutch people in my top 10. I get 3 prominent members in the top 10, 2 of whom are ministers of the Dutch parliament. It completely ignores the fact that I have some of them in one of my lists. 4 politicians of other parties and the others associated with politics, and a Dutch comedian who I don’t like.
In “Tweeps with similar followers” there are 2 Dutch super connectors in the top 10 I follow, @jankarel (#3) and @woepwoep (#4), as well as @thomaspower (#8) or @vincentwright (#6), also both networking super connectors. This doesn’t surprise me, what does surprise me is that the first 2 don’t follow @fritswester and still have him in their top 4 “Tweeps you might like”. In other words, it ignores the tweeps like me and reads my tweets.
“Tweeps with similar followers” also isn’t sorted. Using Twiangulate I discover that @jankarel is less like me than @woepwoep
9 followed by jankarel, webhat and woepwoep
19 followed by jankarel and webhat
27 followed by jankarel and woepwoep
237 followed by webhat and woepwoep
and other two are also more like me:
5 followed by thomaspower, VincentWright and webhat
20 followed by thomaspower and VincentWright
191 followed by VincentWright and webhat
20 followed by thomaspower and webhat
Still @jankarel is number 3 in the list. Add the comparison of the first two in the list:
31 followed by keltie63, topexecutives and webhat
It does no sorting at all!
Tweep like me doesn’t even try:
The tweep most like me is @booge3872!
Twiangulate says:
84 followed by booge3872 and webhat
(Although she seems to be unfollowing people, as my first search we had 102 common followers.)
At least GLFF tried, and it’s a Labs product, so I don’t expect it to get it right the first time.
Just in case you didn’t know, I’m @webhat and you can find my GLFF data here.
UPDATE: Twiangulate returns different results for @booge3872 on booge3872-webhat and booge3872-webhat-kevinrose and booge3872-woepwoep-webhat.
FindMe #geolocation #facebook #crackberry
I discovered findme (links to FaceBook) by way of FireEagle. A different application to update my location to FaceBook.
First you need to register it to FaceBook before you can use it. It registers the cell location, rather than the GPS location, and allows you to tag the Cell with a location tag. It runs in the background. According to FireEagle:
Automatic operation is currently available for BlackBerry …
Click here for FindMe OTA Download.
Technorati Tags: geolocation, facebook, fireeagle, crackberry, blackberry, yahoo!
Trends in Local News Searching #seo
I was reading an article in the International Herald Tribune which stated that the search in foreign countries, such as China or India, of foreign news sources, European or American, for news about the home country is high. Citizens of a country like to know what the foreign press is saying about their home country.
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Google Trends for New York Times for India and China
When looking at the statistics you can see that the search for India is obviously most performed in India, with second and third place locations being the United Arab Emirates and Singapore. For China the same can be seen, Hong Kong SAR is the number one searcher for China and the second and third place are taken by Singapore and Malaysia.
For me knowing how people search is as important as what they search for. Trends is a powerful tool to do this, and local knowledge is just as important. Whether you are targeting specific regions or want global reach. These search trends also show that some of the targeting also affects foreign nationals overseas.
So how can you use this information?
Technorati Tags: seo, china, india, new, york, times, newyorktimes, nyt, search, news
Friendfeed Fun
I love FriendFeed, and input data in many different ways, as you can see from my FF statistics below:
How do I post to FriendFeed?
How I do that is by using my Social Media Syndication network:
technorati tags: friendfeed, social, media, web2.0
Ping.fm Syndication Issue #twitter
As you might have noticed I’m slowly coming to appreciate Ping.fm as a tool to update my microblogs, or status. Some Twitter and Brightkite subscribers started complaining that they were getting two messages. The first was a update from Ping.FM directly to Twitter. The second went from Ping.fm to Brightkite – which adds the geolocation – and was then posted to Twitter.
It looked a little like this:
Sitting at home about 2 hours ago from Ping.fm
As Brightkite sends the message on to Twitter with my current geolocation added it wasn’t necessary for Ping.fm to directly update Twitter.
The only things I still have which updates Twitter directly are:
- me
- Brightkite
- TwitterFeed (for my blog)
technorati tags: twitter, brightkite, ping.fm, syndication, microblogging, geomicroblogging
General Musing 