METHOD OF DETERMINING INFLUENCE OF A MEMBER WITHIN A DATASET

• US 20100205220A1
• Filed: 01/06/2010
• Published: 08/12/2010
• Est. Priority Date: 01/06/2009
• Status: Active Grant

• Current Assignee: Christopher Hart, Joseph Chandra Wilkerson
• Original Assignee: Christopher Hart, Joseph Chandra Wilkerson
• Inventors: Wilkerson, Joseph Chandra, Hart, Christopher
• Granted Patent: US 8,407,179 B2
• Time in Patent Office: Days
• US Class Current: 707/797
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence

Abstract

A method of determining influence of a member within an overall dataset may include functions which capture, aggregate, analyze and visually present the relationships and influence that members of a dataset or collection, such as individual persons, websites, applications and/or machines, exercise over one another based on interaction, behavioral and demographic factors, etc. The calculated results of influence may be employed for the tracking of content and/or marketing, for example.

Claims

1. A method of determining influence of a member within an overall dataset in which a plurality of nodes exist, the member represented by one of the nodes in the dataset, comprising:

providing a root originator node to a location directly or indirectly accessible to a central server, the root originator node embodied by an apparatus, the apparatus comprised of an original content holder holding content and one or more tracking tags and configured to invoke a movement action resulting in the publishing of a new successor node to a new location directly or indirectly accessible to the central server, the new node receiving a new instance of the apparatus inclusive of the original content holder, a tracking tag and an ability to invoke the movement action to generate additional successor nodes,

generating the additional successor nodes by invoking the movement action to pass on a new instance of the apparatus, each additional successor node configured to serve as a distinct originator node for subsequently generated nodes,

capturing raw data from one or more events invoked at each node after a node has been generated,

assembling nodes based on the originator of each node,

assembling the dataset based on an association among all the originator nodes,

aggregating the raw data captured from an event at each originator node and rollup event occurrences transpiring at linked nodes, and

calculating an influence factor from the aggregated data that reflects the member'"'"'s influence on the dataset.

2. The method of claim 1, wherein each node represents a member in the dataset the member being one of an individual person, a machine, a website and an application.

3. The method of claim 1, further comprising:

displaying a plurality of nodes in the data set on a display medium for review of the influence thereof by a viewer.

4. The method of claim 3, wherein the visual size of the node indicates a member'"'"'s influence on the dataset.

5. The method of claim 3, wherein the display medium includes boundaries between nodes to reflect a grouping or other common characteristic responsible for the influence.

6. The method of claim 3, wherein color of the node represents a demographic or other characteristic of the dataset.

7. The method of claim 1, wherein the movement action to generate a successor node includes one of a sharing, forwarding, posting, installing or passing along of a new instance of the apparatus in order to publish the successor node to the new location.

8. The method of claim 1, wherein the content holder is embodied as any of a web widget, electronic mail message, mobile application, rich internet application (“

RIA”

), SMS message, MMS message, web application, web page, block of web content, block of mobile content, web advertisement, mobile advertisement and desktop application.

9. The method of claim 1, wherein the tracking tags further include:

primary keys to identify the node, the primary keys including a content holder ID that is generated by a central server at the root originator node and passed on to linked successor nodes at node generation, and

alternate keys with additional data associated with the node including one of a person ID of the person who created the node and a machine ID of the originating machine identification.

10. The method of claim 9, wherein assembling nodes further includes assembling a hierarchical data tree structure based on a one or more common content holder IDs contained in the primary keys of linked nodes which form the tree.

11. The method of claim 10, wherein assembling the dataset further includes associating originator nodes of the hierarchical data tree structure based on at least one of a common person ID and machine ID of the alternate keys contained therein so as to transform the tree structure to a graph data structure.

12. The method of claim 1, wherein capturing raw data further includes storing raw data as a given event is invoked at a given node and reporting to the central server there from, the event representative of direct or indirect human or automated interaction with the node.

13. The method of claim 1, wherein an event includes a load/open action, an user or machine interaction, a post/send/publish/share of apparatus, a listen/stream, a view, a download, and advertisement impression, advertisement click, a poll question answered, and direct or indirect resulted e-commerce.

14. The method of claim 1, wherein calculating the influence factor comprises dividing the total occurrences of an event at a specific node by the total occurrences of the event in the complete dataset.

15. A method of determining influence of a member within an overall dataset in which a plurality of nodes exist, comprising:

publishing a root originator node to a location directly or indirectly accessible to a central server, the root node having an original content holder holding content and a plurality of tracking tags comprising primary and alternate keys,

creating one or more successor nodes at locations accessible to the central server by the root node performing one of a sharing, forwarding, posting, installing or passing along action of the original content holder and tracking tags in order to publish a successor node to a new location, each of the successor nodes configured to serve as a distinct originator node in generating additional successor nodes that are linked thereto,

capturing raw data from one or more events invoked at each node after a node has been created,

assembling the nodes into a tree data structure based on the primary keys and captured raw data of the originator nodes,

aggregating, for each node of a tree structure, the raw data captured from an event at each originator node and rollup event occurrences transpiring at linked nodes to form tree structures with aggregated data,

transforming the aggregated tree structures into a graph with aggregated data based on the alternate keys of the originator nodes to provide a dataset with established connections between the nodes, and

calculating an influence factor from the aggregated data reflecting the member'"'"'s influence on the dataset.

16. The method of claim 15, wherein each node represents a member in the dataset, the member being one of an individual person, a machine, a website and an application.

17. The method of claim 15, further comprising:

displaying a plurality of nodes in the dataset on a display medium for review of the influence thereof by a viewer.

18. A method of displaying an influence of a member within an overall dataset on a display medium, the dataset including a plurality of nodes, the member visually represented by one of the nodes on the webpage, comprising:

providing a root originator node to a location directly or indirectly accessible to a central server, the root originator node embodied by an apparatus, the apparatus comprised of an original content holder holding content and one or more tracking tags and configured to invoke a movement action resulting in the publishing of a new successor node to a new location directly or indirectly accessible to the central server, the new node receiving a new instance of the apparatus inclusive of the original content holder, a tracking tag and an ability to invoke the movement action to generate additional successor nodes,

generating the additional successor nodes by invoking the movement action to pass on a new instance of the apparatus, each additional successor node configured to serve as a distinct originator node for subsequently generated nodes linked thereto,

capturing raw data from one or more events invoked at each node after a node has been generated,

assembling the dataset from the captured raw data and based on an association among all the originator nodes,

aggregating the raw data captured from an event at each originator node and rollup event occurrences transpiring at linked nodes,

calculating an influence factor from the aggregated data which reflects the member'"'"'s influence on the dataset.

displaying a plurality of nodes in the data set on a webpage for review of the influence thereof, the visual size of the node on the webpage indicating the member'"'"'s influence on the dataset.

19. The method of claim 18, wherein each node represents a member in the dataset, the member being one of an individual person, a machine, a website and an application.

20. The method of claim 18, wherein

the display medium includes boundaries between nodes to reflect a grouping or other common characteristic responsible for the influence, and

color of the node represents a demographic or other characteristic of the dataset.