Systems and methods for leveraging social queuing to identify and prevent ticket purchaser simulation

1. A computer-implemented method for identifying a simulated user third party data source account history, the method comprising:

querying a third: party data source to obtain user information;

receiving user information associated with a user from the third-party data source;

compiling the user information from the third-party data source to form a user account history;

determining whether the user account history includes one or more parameters that indicate whether the user account history is more similar to a user profile associated with an automated entity or a user profile associated with a human entity;

assigning a first set of pre-determined ticket purchasing opportunities to the user if the user account history is determined as being more similar to a user profile associated with an automated entity; and

assigning a second set of pre-determined ticket purchasing opportunities to the user if the user account history is determined as being more similar to a user profile associated with a human entity.

2. The computer-implemented method of claim 1 , wherein the one or more parameters includes a determination of less than a threshold number of friends associated with the account.

3. The computer-implemented method of claim 1 , wherein the one or more parameters includes at a determination more than a threshold frequency of historic ticket purchases per unit time.

4. The computer-implemented method of claim 1 , wherein the one or more parameters includes a determination of a disparity of location of historic ticket purchases per unit time.

5. The computer-implemented method of claim 1 , wherein the one or more parameters includes a historic record of less than a threshold average reaction time to ticket offers.

6. The computer-implemented method of claim 1 , further comprising monitoring the one or more parameters over a pre-determined period of time.

7. The computer-implemented method of claim 1 , wherein the one or more parameters includes ticket purchasing history over a pre-predetermined period of time.

8. The computer-implemented method of claim 1 , wherein the one or more parameters includes performance attendance over a pre-determined amount of time.

9. A computer-implemented method for identifying a simulated social media account history or a simulated third party data source profile, the method comprising:

querying a social media account associated with a user to obtain social media account information or a third party data source to obtain user information;

receiving social media account information from the social media account or receiving user information from the third party data source;

compiling either or both of the social media account information from the social media account or the user information from the third party data source to form a user account history;

determining whether the user account history includes one or more parameters that indicate whether the user account history is related to an automated entity or a human entity;

assigning a first set of pre-determined ticket purchasing opportunities to the user if the user account history is determined as being related to an automated entity; and

assigning a second set of pre-determined ticket purchasing opportunities to the user if the user account history is determined as being related to a human entity.

10. The computer-implemented method of claim 9 , wherein the one or more parameters include a determination of less than a threshold number of friends associated with the account.

11. The computer-implemented method of claim 9 , wherein the one or more parameters include at a determination more than a threshold frequency of historic ticket purchases per unit time.

12. The computer-implemented method of claim 9 , wherein the one or more parameters include a determination of a disparity of location of historic ticket purchases per unit time.

13. The computer-implemented method of claim 9 , wherein the one or more parameters include a historic record of less than a threshold average reaction time to ticket offers.

14. The computer-implemented method of claim 9 , wherein the one or more parameters are monitored over a pre-determined period of time.

15. The computer-implemented method of claim 9 , wherein the one or more parameters include ticket purchasing history over a pre-predetermined period of time.

16. The computer-implemented method of claim 9 , wherein the one or more parameters include historical performance attendance over a pre-determined amount of time.

17. An article of manufacture comprising a non-transitory computer usable medium having computer readable program code embodied therein, the code when executed by one or more processors for configuring a computer to execute a method to identify automated ticket purchasers, the method comprising:

using a receiver to receive a plurality of logins, each of the logins intended for an event ticket purchase, each of the logins corresponding to user information;

using a processor to retrieve an account history associated with the user information;

using the processor to calculate an index value based on the user information, said index value being based, at least in part, on the retrieved account history;

using the processor to use an algorithm to categorize a first portion of the plurality of logins as human-based logins and a second portion of the plurality of logins as non-human-based logins; and

following a pre-determined amount of time after the categorizing, substantially simultaneously replying to at least portion of the plurality of logins, said replying comprising providing a first set of pre-determined ticket purchasing opportunities to the human-based logins and a second set of pre-determined ticket purchasing opportunities to the non-human-based logins.

18. The method of claim 17 , wherein the plurality of logins are received at least 10 minutes prior to the replying.

19. The method of claim 17 , further comprising using the processor to use a second algorithm to categorize a first portion of the plurality of logins as human-based logins, a second portion of the plurality of logins as non-human-based logins and a third portion of the plurality of logins as human-based priority logins.

20. The method of claim 19 wherein replying comprising providing a first set of pre-determined ticket purchasing opportunities to the human-based logins, a second set of pre-determined ticket purchasing opportunities to the non-human-based logins and a third set of pre-determined ticket purchasing opportunities to the human-based priority logins.