Blending connection recommendation streams

A system comprising:

• one or more hardware processors;
• and
• a machine-readable medium for storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising:
• based on a member identifier of a particular member of a Social Networking Service (SNS), accessing a first list of other members of the SNS and a second list of guests, the first list of members including one or more other members who are potential connections of the particular member via a social graph of the particular member, the second list of guests including one or more guests who are not members of the SNS and who are potential connections of the particular member via the social graph;
• for each of the one or more other members, identifying a member probability value that represents a likelihood of the particular member inviting another member of the one or more other members to connect via the social graph of the particular member;
• for each of the one or more guests, identifying a guest probability value that represents a likelihood of the particular member inviting a guest of the one or more guests to connect via the social graph of the particular member;
• generating a blended list of other members and guests for the particular member based on the member probability values associated with the one or more other members, the guest probability values associated with the one or more guests, and a coefficient value selected to control a presence of a type of connections in the blended list;
• and
• generating one or more connection recommendations for the particular member to invite one or more people included in the blended list to connect with the particular member via the social graph.

A non-transitory machine-readable medium comprising instructions that, when executed by one or more hardware processors, cause the one or more hardware processors to perform operations comprising:

• based on a member identifier of a particular member of a Social Networking Service (SNS), accessing a first list of other members of the SNS and a second list of guests, the first list of members including one or more other members who are potential connections of the particular member via a social graph of the particular member, the second list of guests including one or more guests who are not members of the SNS and who are potential connections of the particular member via the social graph;
• for each of the one or more other members, identifying a member probability value that represents a likelihood of the particular member inviting another member of the one or more other members to connect via the social graph of the particular member;
• for each of the one or more guests, identifying a guest probability value that represents a likelihood of the particular member inviting a guest of the one or more guests to connect via the social graph of the particular member;
• generating a blended list of other members and guests for the particular member based on the member probability values associated with the one or more other members, the guest probability values associated with the one or more guests, and a coefficient value selected to control a presence of a type of connections in the blended list;
• and
• generating one or more connection recommendations for the particular member to invite one or more people included in the blended list to connect with the particular member via the social graph.