System and method for identifying contacts of a target user in a social network
When using Web intelligence (“Webint”) to collect information regarding a target social network user, one of the most valuable pieces of information is the target user's List-Of-Friends (LOF). In some cases, however, the LOF of the target user is not accessible in his profile. Herein are described methods and systems for identifying the LOF of a target user. An analysis system crawls the profiles of social network users, other than the target user, and reconstructs the LOF of the target user from the crawled profiles.
1. A method for determining friends of a target user on a social network, the method comprising:
determining a friend of the target user;
obtaining, from the determined friend's profile, a list of friends (LOF);
calculating a probability for each friend in the LOF, wherein each probability corresponds to the likelihood that each friend in the LOF is also a friend of the target user;
selecting a lead from the LOF that has the highest probability;
determining, from the lead's profile, that the lead is a friend of the target user; and
repeating the obtaining, calculating, selecting, and determining with the lead as the determined friend.
2. The method according to claim 1 , wherein the determining, from the lead's profile, that the lead is a friend of the target user comprises:
querying the lead's list of friends for the target user and finding the target user.
3. The method according to claim 1 , wherein the probability is based on one or more heuristics.
4. The method according to claim 3 , wherein the one or more heuristics comprises a similarity in attribute values between the profile of the target user and each friend in the LOF.
5. The method according to claim 3 , wherein the one or more heuristics comprises the number of other contacts of the target user that each friend in the LOF is connected to.
6. The method according to claim 1 , wherein the repeating terminates after a particular number of iterations.
7. The method according to claim 6 , wherein the particular number of iterations is below value that triggers the social network to utilize throttling and anti-scraping schemes.
8. The method according to claim 1 , further comprising:
adding the lead determined as a friend of the target user to a reconstructed list of friends for the target user.
9. The method according to claim 1 , further comprising:
updating, using the LOF, a currently-known graph (CKG) describing the relationships of profiles in the social network.
10. The method according to claim 1 , further comprising:
determining, from the lead's profile, that the lead is not a friend of the target user;
selecting a lead from the LOF that has the next highest probability or terminating the repeating based on the next highest probability.
11. A system for determining friends of a target user on a social network, the system comprising:
an interface, communicating with one or more social networks; and
a processor communicatively coupled to the interface and executing computer-readable instructions that cause the processor to:
determine a friend of the target user;
obtain, from the determined friend's profile, a list of friends (LOF);
calculate a probability for each friend in the LOF, wherein each probability corresponds to the likelihood that each friend in the LOF is also a friend of the target user;
select a lead from the LOF that has the highest probability;
determine, from the lead's profile, that the lead is a friend of the target user; and
repeat the obtaining, calculating, selecting, and determining with the lead as the determined friend.
12. The system according to claim 11 , wherein to determine, from the lead's profile, that the lead is a friend of the target user comprises:
querying the lead's list of friends for the target user and finding the target user.
13. The system according to claim 11 , wherein the probability is based on one or more heuristics.
14. The system according to claim 13 , wherein the one or more heuristics comprises a similarity in attribute values between the profile of the target user and each friend in the LOF.
15. The system according to claim 13 , wherein the one or more heuristics comprises the number of other contacts of the target user that each friend in the LOF is connected to.
16. The system according to claim 11 , wherein the repeating terminates after a particular number of iterations.
17. The system according to claim 16 , wherein the particular number of iterations is below value that triggers the social network to utilize throttling and anti-scraping schemes.
18. The system according to claim 11 , wherein the processor is further caused to:
add the lead determined as a friend of the target user to a reconstructed list of friends for the target user.
19. The system according to claim 11 , wherein the processor is further caused to:
update, using the LOF, a currently-known graph (CKG) describing the relationships of profiles in the social network.
20. A non-transitory computer readable medium containing computer readable instructions that when executed by a processor of a computer, which is in communication with a social network, to perform a method for determining friends of a target user on the social network, the method comprising:
determining a friend of the target user;
obtaining, from the determined friend's profile, a list of friends (LOF);
calculating a probability for each friend in the LOF, wherein each probability corresponds to the likelihood that each friend in the LOF is also a friend of the target user;
selecting a lead from the LOF that has the highest probability;
determining, from the lead's profile, that the lead is a friend of the target user; and
repeating the obtaining, calculating, selecting, and determining with the lead as the determined friend.