METHOD AND SYSTEM FOR SOCIAL NETWORK ANALYSIS

• US 20090070679A1
• Filed: 12/30/2007
• Published: 03/12/2009
• Est. Priority Date: 09/12/2007
• Status: Abandoned Application

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Sundaresan, Neelakantan, Shen, Zeqian
• Application Number:
  US11/967,221
• Publication Number:
  US 20090070679A1
• Time in Patent Office: Days
• US Class Current: 715/733
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Methods and system for social network analysis are described. In one embodiment, user interaction data of a time period for a plurality of users in a social network may be accessed. Network analysis may be performed on the user interaction data. A necktie-shaped graph may be generated from the user interaction data in accordance with the performing of the network analysis. The necktie-shaped graph may be utilized for analysis of the social network.

Claims

1. A method comprising:

accessing user interaction data of a time period for a plurality of users in a social network;

performing network analysis on the user interaction data;

generating a necktie-shaped graph from the user interaction data in accordance with the performing of the network analysis; and

utilizing the necktie-shaped graph for analysis of the social network.

2. The method of claim 1, further comprising:

accessing reputation information associated with the plurality of users; and

applying a texture to the necktie-shaped graph in accordance with the reputation information.

3. The method of claim 1, further comprising:

accessing interaction frequency data associated with the plurality of users; and

applying a texture to the necktie-shaped graph in accordance with the interaction frequency data.

4. The method of claim 1, further comprising:

accessing transactional financial data associated with the plurality of users; and

applying a texture to the necktie-shaped graph in accordance with the transactional financial data.

5. The method of claim 1, wherein the generating comprises:

generating a strongly connected component of the necktie-shaped graph in accordance with the performing of the network analysis;

generating an in-component of the necktie-shaped graph in accordance with the performing of the network analysis; and

generating an out-component of the necktie-shaped graph in accordance with the performing of the network analysis; and

using a tube to connect the in-component to the out-component,

wherein the in-component of the necktie-shaped graph is smaller than the out-component of the necktie-shaped graph.

6. The method of claim 5, further comprising:

generating one or more tendrils in accordance with the performing of the network analysis, a particular tendril of the one or more tendrils connected to the in-component or the out-component.

7. The method of claim 5, further comprising:

generating a disconnected part in accordance with the performing of the network analysis, the disconnected part being disconnected from the strongly connect component, the in-component, and the out-component in the necktie-shaped graph.

8. The method of claim 1, wherein the utilizing comprises:

analyzing the necktie-shaped graph;

making a decision regarding the social network in accordance with the analyzing of the necktie-shaped graph; and

altering an aspect of the social network in accordance with the making of the decision.

9. The method of claim 1, wherein the utilizing comprises:

providing the necktie-shaped graph for presentation.

10. The method of claim 1, wherein the utilizing comprises:

accessing additional user interaction data associated with the social network during a different time period;

performing the network analysis on the additional user interaction data;

generating an additional necktie-shaped graph from the additional user interaction data in accordance with the performing of the network analysis; and

using the necktie-shaped graph and the additional necktie-shaped graph for analysis of the social network.

11. The method of claim 10, wherein the using comprises:

providing a difference between the necktie-shaped graph and the additional necktie-shaped graph for presentation.

12. The method of claim 1, wherein the user interaction data is associated with a single transaction category.

13. A method comprising:

accessing user interaction data associated for a plurality of users for a time period in a social network;

performing network analysis on the user interaction data;

selecting a plurality of example users within the social network, each of the example users being associated with reputation information;

generating a motif for the plurality of example users for the time period in accordance with the performing of the network analysis, a node of the motif being associated with a particular example user of the example users, the motif defining an expected relationship between the plurality of example users in the social network;

distinguishing the node of the plurality of example users in accordance with the reputation information of a respective example user; and

utilizing the motif with a plurality of distinguished nodes for analysis of the social network.

14. The method of claim 13, wherein the utilizing comprises:

providing the motif with the plurality of distinguished nodes for presentation.

15. The method of claim 13, wherein the utilizing comprises:

analyzing a template including the motif and a plurality of additional motifs; and

making a decision regarding the social network in accordance with the analyzing of the template.

16. The method of claim 13, further comprising:

accessing interaction frequency data associated with the plurality of users; and

applying a texture to at least one connecting line of the motif in accordance with the interaction frequency data.

17. The method of claim 13, further comprising:

accessing transactional financial data associated with the plurality of users; and

applying a texture to at least one connecting line of the motif in accordance with the transactional financial data.

18. The method of claim 13, wherein the distinguishing comprises:

colorizing the node of the plurality of example users in accordance with the reputation information.

19. The method of claim 13, wherein the social network is a social commerce network.

20. A machine-readable medium comprising instructions, which when implemented by one or more processors perform the following operations:

access user interaction data of a time period for a plurality of users in a social network;

perform network analysis on the user interaction data;

generate a necktie-shaped graph from the user interaction data in accordance with the performing of the network analysis; and

utilize the necktie-shaped graph for analysis of the social network.

21. The machine-readable medium of claim 20, wherein the one or more operations to generate the necktie-shaped graph include:

generate a strongly connected component of the necktie-shaped graph in accordance with the performing of the network analysis;

generate an in-component of the necktie-shaped graph in accordance with the performing of the network analysis; and

generate an out-component of the necktie-shaped graph in accordance with the performing of the network analysis; and

use a tube to connect the in-component to the out-component;

wherein the in-component of the necktie-shaped graph is smaller than the out-component of the necktie-shaped graph.

22. A machine-readable medium comprising instructions, which when implemented by one or more processors perform the following operations:

access user interaction data associated for a plurality of users for a time period in a social network;

perform network analysis on the user interaction data;

select a plurality of example users within the social network, each of the example users being associated with reputation information;

generate a motif for the plurality of example users for the time period in accordance with the performing of the network analysis, a node of the motif being associated with a particular example user of the example users, the motif defining an expected relationship between the plurality of example users in the social network;

distinguish the node of the plurality of example users in accordance with the reputation information of a respective example user; and

utilize the motif with a plurality of distinguished nodes for analysis of the social network.

23. The machine-readable medium of claim 22 further comprising instructions, which when implemented by one or more processors perform the following operations:

access interaction frequency data associated with the plurality of users; and

apply a texture to at least one connecting line of the motif in accordance with the interaction frequency data.

24. A system comprising:

a transaction relationship data access module to access user interaction data of a time period for a plurality of users in a social network;

a network analysis performance module to perform network analysis on the user interaction data accessed by the transaction relationship data access module;

a graph generation module to generate a necktie-shaped graph from the user interaction data in accordance with the performing of the network analysis by the network analysis performance module; and

a graph provider module to provide the necktie-shaped graph generated by the graph generation module for presentation.

25. The system of claim 24, further comprising:

a reputation information access module to access reputation information associated with the plurality of users; and

a texture application module to apply a texture to the necktie-shaped graph generated by the graph generation module in accordance with the reputation information.