Social Intelligence

Ikanow’s platform gives organizations a powerful, easy to implement set of tools that can mine a wide variety of data sources (RSS feeds, web pages, databases, XML documents, etc.) and generate the metadata needed to analyze social networks (whether they consist of friends, family, co-works, or co-conspirators in a criminal enterprise).

The business challenge

• Identifying Social Connections: One of the first steps of performing analysis on a social network is determining how individuals are connected, information which is frequently contained within structured and unstructured data sources just waiting to be mined.

• Clarifying Distributions: Figuring out how to utilize the link data at hand to solve questions like node centrality (who in a network is most influential), bridging (a user that ties two or more clusters on graph together), or network holes (lack of connectivity) that can be filled by an entrepreneur to create new markets by merging disparate communities of people.

• Segmenting Communities: Breaking out networks of individuals into communities based on the manner in which individuals are connected (familial relationship, employer, organizational membership, etc.).

Industry scenarios

• Social media marketing: The advent of social media sources like Twitter and Facebook and gives organizations interested in targeted marketing a wealth of data to mine to try identify and serve ever more segmented target markets, respond more rapidly to developing social trends by monitoring networks, and identify influential customers who help form shape consumer trends and influence buying patterns.

• Detecting and monitoring social unrest: The intelligence and law enforcement communities frequently face the need to map the multi-layered links between individuals and organizations to exploit patterns in the data to do things like identify potential informants or central figures in an organization through which communications flow. The ability to fuse structured and unstructured data from open and proprietary data sources gives these organizations more data points from which to start their analysis and identify potentially significant patterns.

IKANOW can help

• Unified data format: Ikanow’s unified semi-structured data format storage allows organizations to harvest a wide variety of disparate data sources and merge those data sources into a homogenous format that allows connections to be made between entities regardless of where they were extracted from.

• Visualization: Ikanow uses an RESTful interface that enables organizations to easily connect their existing visualization tools to Ikanow’s data store or develop custom visualization interfaces. Out of the box Ikanow ships with a flexible Flash based GUI that includes a link analysis tool (Event Graph) that serves as a fully functional example of how the link data generated by Ikanow can be accessed traversed.

• Export link data to GraphML: Although Ikanow isn’t a comprehensive graph analysis tool its ability to harvest link data from such a diverse set of data sources is a value add for organizations looking to enhance their ability to exploit multi-layered graph data in their existing graph analysis tools (NEO4J, Cuttlefish, FNA, Gephi, etc.) via the GraphML export functionality.