Methods and apparatus for analyzing a social network
View Patent ↗Techniques are disclosed for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network. Exemplary techniques include monitoring activity performed by members on the social network, the monitored activity including actions other than the declaring and undeclaring of connections between members. A graphical representation of at least a portion of the social network may be computed to include at least one indication of the monitored activity.
1. A method for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network, the method comprising:
monitoring activity performed by members on the social network, the activity comprising actions other than declaring and undeclaring of connections between members; and
computing, using at least one processor, a graphical representation of at least a portion of the social network, the graphical representation comprising at least one indication of the monitored activity;
wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network; and
visually distinguishing nodes representing members who joined the social network within a specified period of time from nodes representing other members of the at least a portion of the social network.
2. The method of claim 1 , wherein the monitored activity comprises actions performed for purposes other than analyzing the social network.
3. The method of claim 1 , wherein the monitoring comprises determining a measure of a first member's influence on a second member in the social network.
4. The method of claim 3 , wherein the measure of the first member's influence on the second member is determined based at least in part on at least one monitored action selected from the group consisting of:
the second member declaring a connection with the first member;
the first member viewing and/or performing an action on an object contributed by the second member;
the second member viewing and/or performing an action on an object contributed by the first member;
the first member sharing an object with the second member;
the second member sharing an object with the first member;
the first member providing an impression on the second member; and
the second member providing an impression on the first member.
5. The method of claim 3 , wherein computing the graphical representation comprises including in the graphical representation a node representing the first member, the node having at least one visual characteristic determined based at least in part on the measure of the first member's influence on the second member.
6. The method of claim 5 , wherein computing the graphical representation comprises determining a size of the node based at least in part on the first member's influence on other members of the social network.
7. The method of claim 3 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing the first member and a second node representing the second member; and
determining a proximity between the first node and the second node in the graphical representation based at least in part on the measure of the first member's influence on the second member.
8. The method of claim 3 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing the first member and a second node representing the second member; and
including in the graphical representation a connector between the first node and the second node, the connector having at least one visual characteristic determined based at least in part on the measure of the first member's influence on the second member.
9. The method of claim 8 , wherein computing the graphical representation comprises determining a thickness of the connector and/or a proximity between the first node and the second node based at least in part on the measure of the first member's influence on the second member and/or on a measure of the second member's influence on the first member.
10. The method of claim 1 , further comprising applying to the graphical representation at least one filter selected from the group consisting of a location filter, an organization filter, a job type filter, a job level filter, and a group filter.
11. The method of claim 1 , wherein computing the graphical representation comprises:
determining a measure of influence for each of at least some of the plurality of members in the social network;
including in the graphical representation a node representing each of the at least some of the plurality of members; and
visually distinguishing nodes representing members whose measure of influence is above a threshold from nodes representing members whose measure of influence is below the threshold.
12. A method for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network, the method comprising:
monitoring activity performed by members on the social network, the activity comprising actions other than declaring and undeclaring of connections between members; and
computing, using at least one processor, a graphical representation of at least a portion of the social network, the graphical representation comprising at least one indication of the monitored activity;
wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network; and
including in the graphical representation connectors between nodes representing members who influence each other in the social network;
wherein a connector between a node representing a first member and a node representing a second member is not included in the graphical representation if the first member has declared a connection with the second member, and/or if the second member has declared a connection with the first member.
13. The method of claim 1 , wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network;
determining proximities between nodes in the graphical representation based at least in part on measures of influence between the members represented by the nodes; and
in response to a request from a user to reduce visual complexity of the graphical representation, altering the graphical representation to decrease the proximities between nodes.
14. The method of claim 13 , wherein altering the graphical representation comprises changing an angular position of a first node relative to a second node in the graphical representation.
15. The method of claim 1 , further comprising:
in response to a user selection of a first member of the social network, recomputing the graphical representation as if the first member were not a member of the social network.
16. The method of claim 1 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing a first member and a plurality of other nodes representing other members having influence on the first member in the social network; and
for each of the plurality of other nodes, determining a proximity between the other node and the first node in the graphical representation based at least in part on a measure of influence on the first member of the other member represented by the other node.
17. The method of claim 1 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing a first member and a plurality of other nodes representing other members that the first member influences in the social network; and
for each of the plurality of other nodes, determining a proximity between the other node and the first node in the graphical representation based at least in part on a measure of influence of the first member on the other member represented by the other node.
18. The method of claim 1 , wherein computing the graphical representation comprises:
including in the graphical representation a plurality of nodes, each of the plurality of nodes representing a group of members of the social network; and
positioning the plurality of nodes in the graphical representation to indicate comparative levels of activity of the groups represented by the nodes.
19. Apparatus comprising:
at least one processor; and
at least one non-transitory storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network, the method comprising:
monitoring activity performed by members on the social network, the activity comprising actions other than declaring and undeclaring of connections between members; and
computing a graphical representation of at least a portion of the social network, the graphical representation comprising at least one indication of the monitored activity;
wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network; and
visually distinguishing nodes representing members who joined the social network within a specified period of time from nodes representing other members of the at least a portion of the social network.
20. The apparatus of claim 19 , wherein the monitored activity comprises actions performed for purposes other than analyzing the social network.
21. The apparatus of claim 19 , wherein the monitoring comprises determining a measure of a first member's influence on a second member in the social network.
22. The apparatus of claim 21 , wherein the measure of the first member's influence on the second member is determined based at least in part on at least one monitored action selected from the group consisting of:
the second member declaring a connection with the first member;
the first member viewing and/or performing an action on an object contributed by the second member;
the second member viewing and/or performing an action on an object contributed by the first member;
the first member sharing an object with the second member;
the second member sharing an object with the first member;
the first member providing an impression on the second member; and
the second member providing an impression on the first member.
23. The apparatus of claim 21 , wherein computing the graphical representation comprises including in the graphical representation a node representing the first member, the node having at least one visual characteristic determined based at least in part on the measure of the first member's influence on the second member.
24. The apparatus of claim 23 , wherein computing the graphical representation comprises determining a size of the node based at least in part on the first member's influence on other members of the social network.
25. The apparatus of claim 21 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing the first member and a second node representing the second member; and
determining a proximity between the first node and the second node in the graphical representation based at least in part on the measure of the first member's influence on the second member.
26. The apparatus of claim 21 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing the first member and a second node representing the second member; and
including in the graphical representation a connector between the first node and the second node, the connector having at least one visual characteristic determined based at least in part on the measure of the first member's influence on the second member.
27. The apparatus of claim 26 , wherein computing the graphical representation comprises determining a thickness of the connector and/or a proximity between the first node and the second node based at least in part on the measure of the first member's influence on the second member and/or on a measure of the second member's influence on the first member.
28. The apparatus of claim 19 , wherein the method further comprises applying to the graphical representation at least one filter selected from the group consisting of a location filter, an organization filter, a job type filter, a job level filter, and a group filter.
29. The apparatus of claim 19 , wherein computing the graphical representation comprises:
determining a measure of influence for each of at least some of the plurality of members in the social network;
including in the graphical representation a node representing each of the at least some of the plurality of members; and
visually distinguishing nodes representing members whose measure of influence is above a threshold from nodes representing members whose measure of influence is below the threshold.
30. Apparatus comprising:
at least one processor; and
at least one non-transitory storage medium storing processor-executable instructions that, when executed by the at least one processor, perform a method for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network, the method comprising:
monitoring activity performed by members on the social network, the activity comprising actions other than declaring and undeclaring of connections between members; and
computing a graphical representation of at least a portion of the social network, the graphical representation comprising at least one indication of the monitored activity;
wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network; and
including in the graphical representation connectors between nodes representing members who influence each other in the social network;
wherein a connector between a node representing a first member and a node representing a second member is not included in the graphical representation if the first member has declared a connection with the second member, and/or if the second member has declared a connection with the first member.
31. The apparatus of claim 19 , wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network;
determining proximities between nodes in the graphical representation based at least in part on measures of influence between the members represented by the nodes; and
in response to a request from a user to reduce visual complexity of the graphical representation, altering the graphical representation to decrease the proximities between nodes.
32. The apparatus of claim 31 , wherein altering the graphical representation comprises changing an angular position of a first node relative to a second node in the graphical representation.
33. The apparatus of claim 19 , wherein the method further comprises:
in response to a user selection of a first member of the social network, recomputing the graphical representation as if the first member were not a member of the social network.
34. The apparatus of claim 19 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing a first member and a plurality of other nodes representing other members having influence on the first member in the social network; and
for each of the plurality of other nodes, determining a proximity between the other node and the first node in the graphical representation based at least in part on a measure of influence on the first member of the other member represented by the other node.
35. The apparatus of claim 19 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing a first member and a plurality of other nodes representing other members that the first member influences in the social network; and
for each of the plurality of other nodes, determining a proximity between the other node and the first node in the graphical representation based at least in part on a measure of influence of the first member on the other member represented by the other node.
36. The apparatus of claim 19 , wherein computing the graphical representation comprises:
including in the graphical representation a plurality of nodes, each of the plurality of nodes representing a group of members of the social network; and
positioning the plurality of nodes in the graphical representation to indicate comparative levels of activity of the groups represented by the nodes.
37. At least one non-transitory computer-readable storage medium encoded with instructions that, when executed, perform a method for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network, the method comprising:
monitoring activity performed by members on the social network, the activity comprising actions other than declaring and undeclaring of connections between members; and
computing a graphical representation of at least a portion of the social network, the graphical representation comprising at least one indication of the monitored activity;
wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network; and
visually distinguishing nodes representing members who joined the social network within a specified period of time from nodes representing other members of the at least a portion of the social network.
38. The at least one non-transitory computer-readable storage medium of claim 37 , wherein the monitored activity comprises actions performed for purposes other than analyzing the social network.
39. The at least one non-transitory computer-readable storage medium of claim 37 , wherein the monitoring comprises determining a measure of a first member's influence on a second member in the social network.
40. The at least one non-transitory computer-readable storage medium of claim 39 , wherein the measure of the first member's influence on the second member is determined based at least in part on at least one monitored action selected from the group consisting of:
the second member declaring a connection with the first member;
the first member viewing and/or performing an action on an object contributed by the second member;
the second member viewing and/or performing an action on an object contributed by the first member;
the first member sharing an object with the second member;
the second member sharing an object with the first member;
the first member providing an impression on the second member; and
the second member providing an impression on the first member.
41. The at least one non-transitory computer-readable storage medium of claim 39 , wherein computing the graphical representation comprises including in the graphical representation a node representing the first member, the node having at least one visual characteristic determined based at least in part on the measure of the first member's influence on the second member.
42. The at least one non-transitory computer-readable storage medium of claim 41 , wherein computing the graphical representation comprises determining a size of the node based at least in part on the first member's influence on other members of the social network.
43. The at least one non-transitory computer-readable storage medium of claim 39 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing the first member and a second node representing the second member; and
determining a proximity between the first node and the second node in the graphical representation based at least in part on the measure of the first member's influence on the second member.
44. The at least one non-transitory computer-readable storage medium of claim 39 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing the first member and a second node representing the second member; and
including in the graphical representation a connector between the first node and the second node, the connector having at least one visual characteristic determined based at least in part on the measure of the first member's influence on the second member.
45. The at least one non-transitory computer-readable storage medium of claim 44 , wherein computing the graphical representation comprises determining a thickness of the connector and/or a proximity between the first node and the second node based at least in part on the measure of the first member's influence on the second member and/or on a measure of the second member's influence on the first member.
46. The at least one non-transitory computer-readable storage medium of claim 37 , wherein the method further comprises applying to the graphical representation at least one filter selected from the group consisting of a location filter, an organization filter, a job type filter, a job level filter, and a group filter.
47. The at least one non-transitory computer-readable storage medium of claim 37 , wherein computing the graphical representation comprises:
determining a measure of influence for each of at least some of the plurality of members in the social network;
including in the graphical representation a node representing each of the at least some of the plurality of members; and
visually distinguishing nodes representing members whose measure of influence is above a threshold from nodes representing members whose measure of influence is below the threshold.
48. At least one non-transitory computer-readable storage medium encoded with instructions that, when executed, perform a method for analyzing a social network having a plurality of members, each member having declared a connection with each of one or more other members of the social network, the method comprising:
monitoring activity performed by members on the social network, the activity comprising actions other than declaring and undeclaring of connections between members; and
computing a graphical representation of at least a portion of the social network, the graphical representation comprising at least one indication of the monitored activity;
wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network; and
including in the graphical representation connectors between nodes representing members who influence each other in the social network;
wherein a connector between a node representing a first member and a node representing a second member is not included in the graphical representation if the first member has declared a connection with the second member, and/or if the second member has declared a connection with the first member.
49. The at least one non-transitory computer-readable storage medium of claim 37 , wherein computing the graphical representation comprises:
including in the graphical representation nodes representing members of the at least a portion of the social network;
determining proximities between nodes in the graphical representation based at least in part on measures of influence between the members represented by the nodes; and
in response to a request from a user to reduce visual complexity of the graphical representation, altering the graphical representation to decrease the proximities between nodes.
50. The at least one non-transitory computer-readable storage medium of claim 49 , wherein altering the graphical representation comprises changing an angular position of a first node relative to a second node in the graphical representation.
51. The at least one non-transitory computer-readable storage medium of claim 37 , wherein the method further comprises:
in response to a user selection of a first member of the social network, recomputing the graphical representation as if the first member were not a member of the social network.
52. The at least one non-transitory computer-readable storage medium of claim 37 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing a first member and a plurality of other nodes representing other members having influence on the first member in the social network; and
for each of the plurality of other nodes, determining a proximity between the other node and the first node in the graphical representation based at least in part on a measure of influence on the first member of the other member represented by the other node.
53. The at least one non-transitory computer-readable storage medium of claim 37 , wherein computing the graphical representation comprises:
including in the graphical representation a first node representing a first member and a plurality of other nodes representing other members that the first member influences in the social network; and
for each of the plurality of other nodes, determining a proximity between the other node and the first node in the graphical representation based at least in part on a measure of influence of the first member on the other member represented by the other node.
54. The at least one non-transitory computer-readable storage medium of claim 37 , wherein computing the graphical representation comprises:
including in the graphical representation a plurality of nodes, each of the plurality of nodes representing a group of members of the social network; and
positioning the plurality of nodes in the graphical representation to indicate comparative levels of activity of the groups represented by the nodes.