Discovery and Visualization of Common Social Context

• US 20090138806A1
• Filed: 11/28/2007
• Published: 05/28/2009
• Est. Priority Date: 11/28/2007
• Status: Active Grant

• Current Assignee: Beijing Zitiao Network Technology Company Limited (ByteDance Ltd.)
• Original Assignee: International Business Machines Corporation
• Inventors: Weber, Sara, Travis, Amy D., Galvin, James P.
• Granted Patent: US 8,073,793 B2
• Time in Patent Office: Days
• US Class Current: 715/753
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]
• CPC Class Codes: G06Q 50/188 Electronic negotiation

Abstract

A method of determining a common social context can include detecting a collaboration between a plurality of participants. The method can include identifying a plurality of common social contexts and determining a probability that the collaboration belongs to each of the plurality of common social contexts. At least one probability and corresponding common social context can be output.

Claims

1. A computer-implemented method of determining a common social context comprising:

detecting a collaboration between a plurality of participants;

identifying a plurality of common social contexts;

determining a probability that the collaboration belongs to each of the plurality of common social contexts; and

outputting at least one probability and corresponding common social context.

2. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying at least one participant in the collaboration;

determining whether the participant is associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the participant is associated with the particular common social context.

3. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying a point of initiation for the collaboration;

determining whether the point of initiation is associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the point of initiation is associated with the particular common social context.

4. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying a collaborative application used for the collaboration;

determining whether the collaborative application is associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the collaborative application is associated with the particular common social context.

5. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying an electronic document used in the collaboration;

determining whether the electronic document is associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the electronic document is associated with the particular common social context.

6. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying a project artifact of the participant in the collaboration;

determining whether the project artifact is associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the project artifact is associated with the particular common social context.

7. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying at least one participant of the collaboration;

determining whether the participant is organizationally associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the participant is organizationally associated with the particular common social context.

8. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying at least one participant of the collaboration;

determining whether the participant is geographically associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the participant is geographically associated with the particular common social context.

9. The computer-implemented method of claim 1, wherein determining a probability further comprises:

identifying content used in the collaboration;

determining whether the content is associated with a particular common social context; and

increasing the probability the collaboration belongs to the particular common social context when the content is associated with the particular common social context.

10. The computer-implemented method of claim 1, wherein determining a probability further comprises:

monitoring the probability the collaboration belongs to a particular common social context;

determining when the probability the collaboration belongs to the particular common social context exceeds a minimum threshold level; and

outputting an alert when the probability the collaboration belongs to the particular common social context exceeds the minimum threshold level.

11. The computer-implemented method of claim 1, wherein determining a probability further comprises receiving a user action explicitly confirming the collaboration belongs to a particular common social context.

12. A computer-implemented method of visualizing collaborations related to a common social context comprising:

responsive to a user input, selecting a common social context;

identifying at least one collaboration related to the common social context;

identifying a plurality of participants of the collaboration and at least one collaboration application used for the collaboration;

presenting a visual representation of the plurality of participants; and

dynamically updating the visual representation to indicate which participants are communicating and the collaboration application being used in real-time.

13. The computer-implemented method of claim 12, wherein dynamically updating the visual representation further comprises:

displaying each participant as an icon;

monitoring a contribution of the participant to the collaboration; and

dynamically sizing the icon of the participant according to the contribution of the participant to the collaboration.

14. The computer-implemented method of claim 12, wherein dynamically updating the visual representation further comprises:

displaying at least two participants as icons;

displaying an electronic document as an icon; and

presenting a visual representation of a sharing of the electronic document between the at least two participants.

15. A computer program product comprising:

a computer-usable medium comprising computer-usable program code that determines a common social context, the computer-usable medium comprising;

computer-usable program code that detects a collaboration between a plurality of participants;

computer-usable program code that identifies a plurality of common social contexts;

computer-usable program code that determines a probability that the collaboration belongs to each of the plurality of common social contexts; and

computer-usable program code that outputs at least one probability and corresponding common social context.

16. The computer program product of claim 15, wherein the computer-usable medium further comprises:

computer-usable program code that identifies at least one participant of the collaboration;

computer-usable program code that determines whether the participant is associated with a particular common social context; and

computer-usable program code that increases the probability the collaboration belongs to the particular common social context when the participant is associated with the particular common social context.

17. The computer program product of claim 15, wherein the computer-usable medium further comprises:

computer-usable program code that identifies a point of initiation for the collaboration;

computer-usable program code that determines whether the point of initiation is associated with a particular common social context; and

computer-usable program code that increases the probability the collaboration belongs to the particular common social context when the point of initiation is associated with the particular common social context.

18. The computer program product of claim 15, wherein the computer-usable medium further comprises:

computer-usable program code that identifies content used in the collaboration;

computer-usable program code that determines whether the content is associated with a particular common social context; and

computer-usable program code that increases the probability the collaboration belongs to the particular common social context when the content is associated with the particular common social context.

19. The computer program product of claim 15, wherein the computer-usable medium further comprises:

computer-usable program code that monitors the probability the collaboration belongs to the particular common social context;

computer-usable program code that determines when the probability the collaboration belongs to a particular common social context exceeds a minimum threshold level; and

computer-usable program code that outputs an alert when the probability the collaboration belongs to the particular common social context exceeds the minimum threshold level.

20. The computer program product of claim 15, wherein the computer-usable program code that determines a probability further comprises computer-usable program code that receives a user action explicitly confirming the collaboration belongs to a particular common social context.