Innovation 3.0 = Leveraging social media. The potential exists to get the best of both the 1.0 and 2.0 worlds. The 1.0 internal R&D labs did not suffer integration issues but usually missed the big innovation opportunities that were achieved by acquiring start-ups (2.0). Social media offers the alluring possibility of harnessing outside innovation without the integration issues.
Social Resource and Metadata Hub
Upload and share your files and bookmarks, join groups and communicate with others! ALOE features
* feed support for all open groups
* the ALOE bookmarklet
* full UTF-8 support
* an improved web interface
The tools used to search and find Learning Objects in different systems do not provide a meaningful and scalable way to rank or recommend learning material. This work propose and detail the use of Contextual Attention Metadata, gathered from the different tools used in the lifecycle of the Learning Object, to create ranking and recommending metrics to improve the user experience. Four types of metrics are detailed: Link Analysis Ranking, Similarity Recommendation, Personalized Ranking and Contextual Recommendation. While designed for Learning Objects, it is shown that these metrics could also be applied to rank and recommend other types of reusable components like software libraries.
abstract of the international conference april 27-29, 2007 @ mit about
"Collaboration and Collective Intelligence". some interesting resources and issues.
In conclusion, even when using a very weak definition of "friend" (i.e., anyone who a user has directed a post to at least twice) we find that Twitter users have a very small number of friends compared to the number of followers and followees they declare. This implies the existence of two different networks: a very dense one made up of followers and followees, and a sparser and simpler network of actual friends. The latter proves to be a more influential network in driving Twitter usage since users with many actual friends tend to post more updates than users with few actual friends. On the other hand, users with many followers or followees post updates more infrequently than those with few followers or followees.