SMART LISTS IN A GEO-SPATIAL SOCIAL NETWORK

• US 20140136624A1
• Filed: 01/22/2014
• Published: 05/15/2014
• Est. Priority Date: 11/22/2006
• Status: Abandoned Application

• Current Assignee: Raj Abhyanker
• Original Assignee: Raj Abhyanker
• Inventors: Abhyanker, Raj V.
• Application Number:
  US14/160,586
• Publication Number:
  US 20140136624A1
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 51/212 using filtering or selective blocking

Abstract

A method and system of forming smart lists in a geo-spatial social network are disclosed. In one embodiment, a method of organizing a community network includes obtaining member data associated with a first member of the community network, determining a first location associated with the first member based on the member data, storing the member data in a member repository, determining a first number of connections associated with the first member, and obtaining a first region of influence for the first member based on the first location and the first number of connections. The method may further include displaying the first region of influence on a geo-spatial map. The method may also include bounding the first region of influence based on a connectedness of the first member in the first region of influence.

Claims

1. A method comprising:

associating a user with an address at which the user physically lives in a residential home;

verifying that the address at which the user physically lives in the residential home is trusted using a processor and a memory;

automatically organizing the user and a set of connected users to the user in a list of a geo-spatial social network based on geographic proximity of each user of the set of connected users with each other;

filtering a set of feeds associated with each of the set of connected users based on a residential address of each of the set of users being geographically proximate of each user of the set of connected users; and

displaying the filtered set of feeds to each user of the set of connected users.

2. The method of claim 1 further comprising:

forming the list based on an activity level of each user of the set of connected users in interacting with each other through the geo-spatial social network; and

permitting the user to designate individual members of the list as a close friends list of the user based on a real-world friendship, such that the filtered set of feeds regularly displays stories generated in the feed by members that are the close friends of the user.

3. The method of claim 2 further comprising:

permitting the user to designate individual members the list as an acquaintance list of users that information associated with the list rarely shows up in the filtered set of feeds.

4. The method of claim 3 further comprising:

restricting the list in a private list based on individuals added any one of the acquaintance list and the close friends list to view only selected ones of photographs associated with the user; and

masking notification to users added to the private list such that users added to the private list are not notified when added to the private list.

5. The method of claim 4 further comprising:

automatically adding users to the list when a trait of the user and other users is shared comprising a friendship, a common school, a common job, and a common city.

6. The method of claim 5 further, comprising:

obtaining member data associated with a first member of the community network, wherein the first member is the user;

determining a first location associated with the first member based on the member data, wherein the first location is the residential home of the user;

storing the member data in a member repository;

determining a first number of connections associated with the first member; and

obtaining a first region of influence for the first member based on the first location and the first number of connections.

7. The method of claim 6, further comprising:

displaying the first region of influence on a geo-spatial map; and

bounding the first region of influence based on a connectedness of the first member in the first region of influence.

8. The method of claim 7, further comprising:

obtaining a second location associated with a second member of the community network;

determining a second number of connections associated with the second member;

obtaining a second region of influence for the second member based on the second location and the second number of connections; and

bounding the first region of influence by the second region of influence based on an inequality between the first number of connections and the second number of connections, wherein the first number of connections is based on an activity level of the first member.

9. The method of claim 8 further comprising:

obtain a personal address privacy preference from each user, the personal address privacy preference specifying if the address should be displayed to other users.

10. The method of claim 9 further comprising:

authenticating a particular user of a third-party application as being a verified user of the neighborhood communication system having a verified residential address in the neighborhood communication system;

communicating a social graph of the particular user based on the personal address privacy preference of the particular user to the third-party application;

providing the verified residential address to the third-party application based on the authentication of the particular user of the third-party application as being the verified user of the neighborhood communication system.

11. A method comprising:

automatically organizing the user and a set of connected users to the user in a list of a geo-spatial social network based on geographic proximity of each user of the set of connected users with each other using a processor and a memory;

filtering a set of feeds associated with each of the set of connected users based on a residential address of each of the set of users being geographically proximate of each user of the set of connected users;

generating the filtered set of feeds to each user of the set of connected users; and

automatically adding users to the list when a trait of the user and other users is shared comprising a friendship, a common school, a common job, and a common city.

12. The method of claim 11 further comprising:

forming the list based on an activity level of each user of the set of connected users in interacting with each other through the geo-spatial social network; and

permitting the user to designate individual members of the list as a close friends list of the user based on a real-world friendship, such that the filtered set of feeds regularly displays stories generated in the feed by members that are the close friends of the user.

13. The method of claim 12 further comprising:

permitting the user to designate individual members the list as an acquaintance list of users that information associated with the list rarely shows up in the filtered set of feeds.

14. The method of claim 13 further comprising:

restricting the list in a private list based on individuals added any one of the acquaintance list and the close friends list to view only selected ones of photographs associated with the user; and

masking notification to users added to the private list such that users added to the private list are not notified when added to the private list.

15. The method of claim 14 further comprising:

associating a user with an address at which the user physically lives in a residential home; and

verifying that the address at which the user physically lives in the residential home is trusted.

16. The method of claim 15 further, comprising:

obtaining member data associated with a first member of the community network, wherein the first member is the user;

determining a first location associated with the first member based on the member data, wherein the first location is the residential home of the user;

storing the member data in a member repository;

determining a first number of connections associated with the first member; and

obtaining a first region of influence for the first member based on the first location and the first number of connections.

17. The method of claim 16, further comprising:

displaying the first region of influence on a geo-spatial map; and

bounding the first region of influence based on a connectedness of the first member in the first region of influence.

18. The method of claim 17, further comprising:

obtaining a second location associated with a second member of the community network;

determining a second number of connections associated with the second member;

obtaining a second region of influence for the second member based on the second location and the second number of connections; and

bounding the first region of influence by the second region of influence based on an inequality between the first number of connections and the second number of connections, wherein the first number of connections is based on an activity level of the first member.

19. The method of claim 18 further comprising:

obtain a personal address privacy preference from each user, the personal address privacy preference specifying if the address should be displayed to other users.

20. The method of claim 19 further comprising:

authenticating a particular user of a third-party application as being a verified user of the neighborhood communication system having a verified residential address in the neighborhood communication system;

communicating a social graph of the particular user based on the personal address privacy preference of the particular user to the third-party application;

providing the verified residential address to the third-party application based on the authentication of the particular user of the third-party application as being the verified user of the neighborhood communication system.

21. A method comprising:

automatically organizing the user and a set of connected users to the user in a list of a geo-spatial social network based on geographic proximity of each user of the set of connected users with each other;

filtering a set of feeds associated with each of the set of connected users based on a residential address of each of the set of users being geographically proximate of each user of the set of connected users using a processor and a memory;

displaying the filtered set of feeds to each user of the set of connected users;

forming the list based on an activity level of each user of the set of connected users in interacting with each other through the geo-spatial social network; and

permitting the user to designate individual members of the list as a close friends list of the user based on a real-world friendship, such that the filtered set of feeds regularly displays stories generated in the feed by members that are the close friends of the user.

22. The method of claim 21 further comprising:

associating a user with an address at which the user physically lives in a residential home;

verifying that the address at which the user physically lives in the residential home is trusted;

23. The method of claim 22 further comprising:

permitting the user to designate individual members the list as an acquaintance list of users that information associated with the list rarely shows up in the filtered set of feeds.

24. The method of claim 23 further comprising:

restricting the list in a private list based on individuals added any one of the acquaintance list and the close friends list to view only selected ones of photographs associated with the user; and

masking notification to users added to the private list such that users added to the private list are not notified when added to the private list.

25. The method of claim 24 further comprising:

automatically adding users to the list when a trait of the user and other users is shared comprising a friendship, a common school, a common job, and a common city.

26. The method of claim 25 further, comprising:

obtaining member data associated with a first member of the community network, wherein the first member is the user;

determining a first location associated with the first member based on the member data, wherein the first location is the residential home of the user;

storing the member data in a member repository;

determining a first number of connections associated with the first member; and

obtaining a first region of influence for the first member based on the first location and the first number of connections.

27. The method of claim 26, further comprising:

displaying the first region of influence on a geo-spatial map; and

bounding the first region of influence based on a connectedness of the first member in the first region of influence.

28. The method of claim 27, further comprising:

obtaining a second location associated with a second member of the community network;

determining a second number of connections associated with the second member;

obtaining a second region of influence for the second member based on the second location and the second number of connections; and

bounding the first region of influence by the second region of influence based on an inequality between the first number of connections and the second number of connections, wherein the first number of connections is based on an activity level of the first member.

29. The method of claim 28 further comprising:

obtain a personal address privacy preference from each user, the personal address privacy preference specifying if the address should be displayed to other users.

30. The method of claim 29 further comprising:

authenticating a particular user of a third-party application as being a verified user of the neighborhood communication system having a verified residential address in the neighborhood communication system;

communicating a social graph of the particular user based on the personal address privacy preference of the particular user to the third-party application;

providing the verified residential address to the third-party application based on the authentication of the particular user of the third-party application as being the verified user of the neighborhood communication system.