1. Social Media and Semantic Technology Web 3.0 Conference, Jan/10 Peter Sweeney, Founder & Co-President @petersweeney

3. http://www.flickr.com/photos/senor_codo/1512636345/ Social media creates a massive amount of content. Real-time Web imposes deep challenges for search/retrieval. Semantic technology can provide benefits of aggregation, summarization, filtering, and mining. For many, the consumer experience of social media embraces the content glut: “living in the flow”. Consumers may not perceive glut as a problem. There is a faith that the information will propagate across social networks; social enables information to find them. For consumer-facing ventures, care must be taken to ensure solutions are aligned with problems that are perceived as real and immediate.

4. Anti-social networks as a backlash against social media. “ I’m not really your friend”; fatigue in adding persistent social connections for temporary or loose social relationships. Sociologists: conflict of weak (co-workers, acquaintances, etc.) vs. strong ties (friends, loved ones); social networking infrastructure is premised on strong ties, but the task-oriented purpose of social networks is heavily biased to weak ties. Semantic technology can provide solutions, providing structural support for social networking (ontology, taxonomy, etc.) The dynamic and fluid environment of weakly tied relationships and tasks complicates the problem and represents an area for innovation in semantic technology.

5. http://www.flickr.com/photos/microagua/3598123093/ Invariably, social networks fragment into smaller cells/cliques as they grow. It doesn’t matter how you define the social network initially (e.g. subject interest), fragmentation is a consequence of the size of the network. There are many factors that may contribute: weak vs. strong ties, shifting content/interests/personal relationships, etc. Again, semantic technology offers ways of providing more structural support to the network to facilitate connections and mediate relationships. However, if the network itself is prone to fragmentation, it heightens the need for more dynamic, ad hoc, and fluid solutions.

6. Function Follows Form In network-based business models, function often follows form. Networks that were architected to a particular function are re-purposed over time to new applications. Examples: Facebook began as a social network based on a demographic-based community (Harvard students); today it is a virtual nation of over 200-million users, attempting to contain every conceivable social application. Large social networks are being taxed with applications that are not well suited to social networks, making them ripe for disruption. This problem area represents an opportunity beyond social networking, not within it, and semantic technologists are well positioned to capitalize on this gap.

7. Just as networks emerged around other organizing bases (such as documents, search, multimedia, etc.), there will emerge new mass market networks that are not premised on “social”, but rather formed to more effectively address the knowledge-based functions of social media. For the problems addressed here, we don’t need semantically enhanced social networks as much as we need semantic networks, where the organizing basis is around the units of thoughts, concepts, and ideas. Primal Fusion builds a special class of consumer-directed semantic networks, called “thought networking” to address this opportunity. Thought networking is designed to provide for fluid, consumer-driven, task-oriented applications. We are leveraging these networks through consumer-facing applications such as research assistants, news tracking, and blogging tools, as well as producer-facing applications for content manufacturing and automation. We are also exposing our infrastructure as a technology platform for others to add these capabilities to their solutions.