Is Google the only one who has possibly accumulated a lot of data on your online activities?
Think again.
Most of us use one of these -
There's a common aspect to all these networks/tools - all of them can potentially collect data about the online preferences of their users. So - do they? Some of them do.
Online preferences are links that you visit, which translates to things that you are interested in. This kind of data can be used to build up a profile of the user.
Think about it -
1. Facebook knows what you share on facebook.com, knows what you "Like" among others' shared links, and now with OpenGraph knows what you "Like" on sites that have the Facebook Like button.
2. Twitter knows what links you share, and now with t.co - its own shortening service - it will know what links shared by others you clicked on (read "interested in"). From a Twitter blog post -
3. ShareThis - if you're logged into ShareThis, it knows what you shared.
Links you share and visit provide a picture, albeit incomplete, of your online preferences.
The question is, how are these tools and services planning to use this data?
If you know what someone likes, you can recommend stuff to that person. A lot of sites do this already. These recommendations are based on multiple parameters. E.g. Amazon's recommendation system - which does a great job - uses collaborative filtering. Simply put, it uses data from your past purchases, ratings and I-Own-This history and from other users whose history is similar to yours. The more history you have on Amazon, the better your recommendations get.
Building a content recommendation system seems to be an obvious step once you have a data mountain of your users' likes. And this is what these sites seem to be doing but to achieve different ends.
E.g. Facebook - See slide #29 http://www.slideshare.net/CMSummit/ms-internet-trends060710final. This has not happened yet, but what's stopping it, considering what Mark Zuckerberg said earlier this year ?
Twitter has recommendation plans - http://groups.google.com/group/twitter-development-talk/browse_thread/thread/14d5474c13ed84aa?pli=1
ShareThis already has behavioural advertising in the works with its segmentation technology.
The bottom line is - some of these services are going to use it to improve the end user's experience - and will do so within the boundaries of their privacy policies. The rest - we don't know.
Think again.
Most of us use one of these -
- Facebook
- Twitter
- ShareThis
- Technorati/Digg/et al
There's a common aspect to all these networks/tools - all of them can potentially collect data about the online preferences of their users. So - do they? Some of them do.
Online preferences are links that you visit, which translates to things that you are interested in. This kind of data can be used to build up a profile of the user.
Think about it -
1. Facebook knows what you share on facebook.com, knows what you "Like" among others' shared links, and now with OpenGraph knows what you "Like" on sites that have the Facebook Like button.
2. Twitter knows what links you share, and now with t.co - its own shortening service - it will know what links shared by others you clicked on (read "interested in"). From a Twitter blog post -
routing links through this service will eventually contribute to the metrics behind our Promoted Tweets platform and provide an important quality signal for our Resonance algorithm—the way we determine if a Tweet is relevant and interesting to users
3. ShareThis - if you're logged into ShareThis, it knows what you shared.
Links you share and visit provide a picture, albeit incomplete, of your online preferences.
The question is, how are these tools and services planning to use this data?
If you know what someone likes, you can recommend stuff to that person. A lot of sites do this already. These recommendations are based on multiple parameters. E.g. Amazon's recommendation system - which does a great job - uses collaborative filtering. Simply put, it uses data from your past purchases, ratings and I-Own-This history and from other users whose history is similar to yours. The more history you have on Amazon, the better your recommendations get.
Building a content recommendation system seems to be an obvious step once you have a data mountain of your users' likes. And this is what these sites seem to be doing but to achieve different ends.
E.g. Facebook - See slide #29 http://www.slideshare.net/CMSummit/ms-internet-trends060710final. This has not happened yet, but what's stopping it, considering what Mark Zuckerberg said earlier this year ?
Twitter has recommendation plans - http://groups.google.com/group/twitter-development-talk/browse_thread/thread/14d5474c13ed84aa?pli=1
ShareThis already has behavioural advertising in the works with its segmentation technology.
The bottom line is - some of these services are going to use it to improve the end user's experience - and will do so within the boundaries of their privacy policies. The rest - we don't know.