SYSTEMS AND METHODS FOR RECOMMENDING ADVERTISEMENT PLACEMENT BASED ON IN NETWORK AND CROSS NETWORK ONLINE ACTIVITY ANALYSIS

• US 20120278164A1
• Filed: 02/23/2012
• Published: 11/01/2012
• Est. Priority Date: 02/23/2011
• Status: Abandoned Application

• Current Assignee: Blazent Incorporated (ServiceNow Incorporated)
• Original Assignee: Blazent Incorporated (ServiceNow Incorporated)
• Inventors: Spivack, Nova, ter Heide, Dominiek
• Application Number:
  US13/403,962
• Publication Number:
  US 20120278164A1
• Time in Patent Office: Days
• US Class Current: 705/14.52
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: H04L 51/212 using filtering or selective blocking
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/53 using third party service providers
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Systems and methods for recommending advertisement placement based on in network and cross network online activity analysis are disclosed. In one aspect, a method for recommending advertisement placement for an advertiser based on trends identified from activities occurring in or across networks, which can be implemented on a system includes, identifying, from the activities occurring in or across networks, commonly or frequently occurring topics and recommending placement of the advertisement at a timing when the trends or the emerging trends deem it suitable. The statistical attributes for the commonly or frequently occurring topics detected from the activities can be computed to identify trends and emerging trends.

Claims

1. A method for aggregating an online identity of a user from activities at social media sites for targeting content, the method comprising:

determining interests of the user by analyzing user content provided during the activities at the social media sites by identifying concepts from the user content;

creating an interest profile for the user using the concepts;

creating the online identity of the user in part using the interest profile;

overlaying the content to be targeted to the user based on the online identity via a platform independent of the social media sites.

2. The method of claim 1, wherein, the content targeted to user is created via the platform independent of the social media sites.

3. The method of claim 1, wherein, the content targeted to the user is created by a third party.

4. The method of claim 1, wherein, the content targeted to the user is created by a third party advertiser or a third party in partnership with the platform.

5. The method of claim 1, further comprising:

optimizing and updating the online identity of the user in real time or near real time based on activities of the user at the social media sites occurring in real time or near real time;

wherein, the content is targeted further based activities of the user at the social media sites occurring in real time or near real time.

6. The method of claim 1, wherein, the content is targeted based on what the user is sending messages about or what the user is posting or tweeting about.

7. The method of claim 1, wherein, the content is targeted further based on geographical locale of the user.

8. The method of claim 1, further comprising:

tracking social relationships of the user in the social media sites;

wherein, the online identity is created further in part based on the social relationships.

9. The method of claim 1, further comprising:

deriving trends for the user based on behavior and the activities at the social media sites;

wherein, the online identity is created further in part based on the trends.

10. The method of claim 1, further comprising:

extracting additional statistics for the user based on the activities at the social media sites;

wherein, the online identity is created further in part based on the additional statistics.

11. The method of claim 10, wherein, the additional statistics include, one or more of, a degree to which a user trusts other people on various topics, a degree to which other people trust the user on various topics, demographics information of a user.

12. The method of claim 10, wherein the additional statistics include, social influence of the user.

13. The method of claim 10, wherein, the additional statistics include, one or more of, sites that the user is interested, content and products that the user is interested in.

14. The method of claim 10, wherein, the additional statistics include, one or more of, statistics about the people the user reposts or replies to, who repost or reply to the user, the people that the user is interested in.

15. The method of claim 1, wherein, the concepts are identified using natural language processing.

16. The method of claim 1, wherein, the content that is targeted includes one or more of, promotional content, sponsored content, advertisements, coupons, e-coupons.

17. A method of recommending advertisement placement for an advertiser based on trends identified from activities occurring in or across networks, the method comprising:

identifying, from the activities occurring in or across networks, commonly or frequently occurring topics;

wherein, statistical attributes for the commonly or frequently occurring topics detected from the activities are computed to identify trends and emerging trends;

recommending placement of the advertisement at a timing when the trends or the emerging trends deem it suitable.

18. The method of claim 17, wherein, the placement of the advertisement is selected at the time when the trends or the emerging trends match or are related to subject of the advertisement or the advertiser.

19. The method of claim 17, wherein, the activities occur on or across social media platforms.

20. The method of claim 17, wherein, the commonly or frequently occurring topics are identified from messages associated with the activities via natural language processing of the messages

21. The method of claim 20, wherein, the messages include one or more of, user profiles, user events, user likes or dislikes, status updates, mentions, feeds, tweets, messages associated links, notes, messages associated with video content, messages associated audio content, messages associated photos, web pages, documents, email messages, comments, chat messages.

22. The method of claim 17, wherein, the advertisement is further user-targeted based on what the user is sending messages about or what the user is posting or tweeting about in real time or near real time on or across the networks.

23. The method of claim 17, wherein, the advertisement is further user-targeted based on what the user is communicating regarding, authoring regarding, browsing/exploring, or reading.

24. The method of claim 17, wherein, the advertisement is further user-targeted based on what the user is presently searching for.

25. The method of claim 17, wherein, the advertisement is further user-targeted based on what the user has searched for in a given time frame.

26. The method of claim 17, wherein, the commonly or frequently occurring topics are identified from the set of messages via natural language processing of the set of messages.

27. A method of using an online identity of a user aggregated from activities at social media sites for targeting content, the method comprising:

optimizing and updating the online identity of the user in real time or near real time based on activities of the user at the social media sites occurring in real time or near real time;

wherein, the content is targeted further based on activities of the user at the social media sites occurring in real time or near real time;

present the content to be targeted to the user based on the online identity via a platform independent of the social media sites.

28. The method of claim 27, wherein, the content is targeted based on what the user is sending messages about or what the user is posting or tweeting about in real time or near real time.

29. A system for aggregating an online identity of a user from activities at social media sites for targeting content, the method comprising:

means for, determining interests of the user by analyzing user content provided during the activities at the social media sites by identifying concepts from the user content;

means for, deriving trends for the user based on behavior and the activities at the social media sites;

means for, creating the online identity of the user in part using the trends derived for the user;

means for, overlaying the content to be targeted to the user based on the online identity via a platform independent of the social media sites.

30. The system of claim 29, further comprising:

means for, creating an interest profile for the user using the concepts and the trends identified for the user.

31. The system of claim 29, wherein, the content targeted to user is created via the platform independent of the social media sites.

32. The system of claim 29, wherein, the content targeted to the user is created by a third party.

33. The system of claim 29, further comprising, means for, enriching third party user profiles using the online identify created for the user.