So far most social networks are user generated. A semi-synthetic social network is one where computer generated content is just as valuable as user generated.
Think about what makes social network's so efficient for intelligence and communication. Entities in the network are represented with profiles. The profiles have background information and a stream of new or changing intelligence information. The profiles also act as an intuitive node to connect related information.
Users sign up and create a feed by defining some filters that determine what intelligence information will be streamed to them.
The entities all have relationships which enrich the ability to filter/discover content and manage communication permissions efficiently.
Typically users register and create their own profile with their background information. They then continually populate the system with intelligence such as pictures, videos, status updates and so on.
They can interact with intelligence documents in the network by posting comments and due tot he relationships the new intelligence elements can be streamed thus create contextual conversations.
So far this concept has mostly been limited to intelligence about people. Facebook for example supports intelligence and communication about people's personal lives.
However some people have figured out how to apply the higher level concept of data organization to support other kinds of intelligence. Quora is a good example. Instead of just focusing on people as primary level entities you also have questions and topics. By creating relationships between these entities you can vastly improve the filtering/discovery of intelligence while also creating contextual conversation (aka answers).
I think there are many other cases and one of them requires semi-synthetic networks. To give an example we are in the oil and gas space. Entities people want intelligence about in our industry range from wells to facilities to pipelines to commodities to geographic areas to companies and of course people. Most of these entities have daily intelligence information that range from status updates to licenses to ownership changes and so on.
Since they can't update themselves we monitor the static data sets and programmatically use the event data to create/update profiles and generate and post stories on their behalf. The result is a rich network of thousands of entities with complex relationships the are generating endless valuable content...and all before the first user joins. When a suer joins they create their own profile and design feeds that enable them to easily monitor activity in the network.
Users can then post comments on activity posts, like a well license for example, and chose who that is shared with. Even though the well license story was posted as if the company did it they can still contextually connect with the people they work with. And, of course, the story/post was actually system generated without that company even knowing we posted it.
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The point of sharing this is not to explain my business but to expand people's paradigm of what a social network is and how the concepts can be expanded beyond just being about supporting intelligence about people.
It's time to rethink what a social network is. It's time to start thinking of them as networked intelligence and communication systems. What kind of intelligence are your customers looking for and what can you learn from the way social networks structure data and connect people around it?
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My name is Ashley Dunfield and I'm working to collect, organize and open access to the world's natural resource data/markets.
http://ca.linkedin.com/in/ashleydunfield
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Side note. If you do a great job organizing the intelligence people are looking for and connect them to each other around it you end up controlling access to the people in that market.
A shameless plug for myself is that Oil and Gas alone is expected to have a CAPEX of $26 Trillion over the next 20 years. Our goal is to capture this market first but hopefully extend the technology to all other natural resource markets that operate in a very similar way.
Think about what makes social network's so efficient for intelligence and communication. Entities in the network are represented with profiles. The profiles have background information and a stream of new or changing intelligence information. The profiles also act as an intuitive node to connect related information.
Users sign up and create a feed by defining some filters that determine what intelligence information will be streamed to them.
The entities all have relationships which enrich the ability to filter/discover content and manage communication permissions efficiently.
Typically users register and create their own profile with their background information. They then continually populate the system with intelligence such as pictures, videos, status updates and so on.
They can interact with intelligence documents in the network by posting comments and due tot he relationships the new intelligence elements can be streamed thus create contextual conversations.
So far this concept has mostly been limited to intelligence about people. Facebook for example supports intelligence and communication about people's personal lives.
However some people have figured out how to apply the higher level concept of data organization to support other kinds of intelligence. Quora is a good example. Instead of just focusing on people as primary level entities you also have questions and topics. By creating relationships between these entities you can vastly improve the filtering/discovery of intelligence while also creating contextual conversation (aka answers).
I think there are many other cases and one of them requires semi-synthetic networks. To give an example we are in the oil and gas space. Entities people want intelligence about in our industry range from wells to facilities to pipelines to commodities to geographic areas to companies and of course people. Most of these entities have daily intelligence information that range from status updates to licenses to ownership changes and so on.
Since they can't update themselves we monitor the static data sets and programmatically use the event data to create/update profiles and generate and post stories on their behalf. The result is a rich network of thousands of entities with complex relationships the are generating endless valuable content...and all before the first user joins. When a suer joins they create their own profile and design feeds that enable them to easily monitor activity in the network.
Users can then post comments on activity posts, like a well license for example, and chose who that is shared with. Even though the well license story was posted as if the company did it they can still contextually connect with the people they work with. And, of course, the story/post was actually system generated without that company even knowing we posted it. ---
The point of sharing this is not to explain my business but to expand people's paradigm of what a social network is and how the concepts can be expanded beyond just being about supporting intelligence about people.
It's time to rethink what a social network is. It's time to start thinking of them as networked intelligence and communication systems. What kind of intelligence are your customers looking for and what can you learn from the way social networks structure data and connect people around it? ---
My name is Ashley Dunfield and I'm working to collect, organize and open access to the world's natural resource data/markets.
http://ca.linkedin.com/in/ashleydunfield ---
Side note. If you do a great job organizing the intelligence people are looking for and connect them to each other around it you end up controlling access to the people in that market.
A shameless plug for myself is that Oil and Gas alone is expected to have a CAPEX of $26 Trillion over the next 20 years. Our goal is to capture this market first but hopefully extend the technology to all other natural resource markets that operate in a very similar way.