Automated Omnipresent Real-time Credibility Management System and Methods

• US 20140122354A1
• Filed: 12/24/2013
• Published: 05/01/2014
• Est. Priority Date: 07/15/2011
• Status: Abandoned Application

• Current Assignee: Dun & Bradstreet Corp., DUN & Bradstreet Incorporated (Dun & Bradstreet Corp.), Hoover's Incorporated (Dun & Bradstreet Holdings, Inc.)
• Original Assignee: Credibility Corp. (Dun & Bradstreet Corp.)
• Inventors: Stibel, Jeffrey M., Stibel, Aaron B.
• Application Number:
  US14/140,158
• Publication Number:
  US 20140122354A1
• Time in Patent Office: Days
• US Class Current: 705/319
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Some embodiments provide a credibility management system that aggregates user posts from several social media sites contemporaneously with the posts being published to those sites. The system parses each of the aggregated posts to identify an entity that is targeted in each of the posts and presents the posts to the targeted entities in a real-time manner. The credibility management system computes a score to determine the impact that a user post would have on the credibility of a targeted entity. By presenting the computed scores and aggregated posts to the targeted entities, the credibility management system notifies the targeted entities about what is being said about them across social media, identifies the impact of those posts, and provides a platform whereby the targeted entities can reply in order to mitigate or improve the impact that the posts would have on credibility.

Claims

1. A computer-implemented method for facilitating real-time management of entity credibility across a plurality of different online sites, the computer-implemented method comprising:

with at least one machine operating via a processor and non-transitory computer-readable memory;

aggregating a plurality of posts that are published by a plurality of different users to the plurality of online sites;

extracting a set of posts from the plurality of posts, wherein each post of the set of posts comprises within a message body of the post (i) sentiment expressing positivity or negativity and (ii) an entity identifier identifying at least one entity that is at least one of a subject and target of the post;

extracting from the set of posts, (i) a first subset of posts comprising at least two posts from the set of posts that are aggregated from at least two different online sites with the entity identifier identifying a first entity and (ii) a second subset of posts comprising at least two posts from the set of posts that are aggregated from at least two different online sites with the entity identifier identifying a second different entity, wherein the first subset of posts excludes posts from set of posts where the entity identifier does not identify the first entity and the second subset of posts excludes posts from the set of posts where the entity identifier does not identify the second entity; and

presenting the first subset of posts in a unified stream, wherein the unified stream comprises at least a first post from a first user that is published to a first online site of the plurality of online sites and a second post from a second different user that is published to a second different online site of the plurality of online sites.

2. The computer-implemented method of claim 1, wherein presenting the first subset of posts comprises highlighting sentiment expressed in each post of the first subset of posts to differentiate from other words of each post.

3. The computer-implemented method of claim 1 further comprising retrieving a configuration specified by the particular entity for presenting the first subset of posts as a desired subset of posts.

4. The computer-implemented method of claim 1 further comprising restricting the first entity from responding to any post of the first subset of posts that are presented in the unified stream when the first entity is a first level registrant.

5. The computer-implemented method of claim 4 further comprising enabling the first entity to respond to any post of the first subset of posts that are presented in the unified stream when the first entity is a second level registrant, wherein a response to a particular post of the first subset of posts from the first entity is redirected from the machine to an online site from which the particular post is aggregated.

6. The computer-implemented method of claim 1, wherein aggregating the plurality of posts comprises aggregating each post of the plurality of posts, an identifier for a user that publishes the post, and an identifier for an online site to which the post is published by the user.

7. The computer-implemented method of claim 6 wherein presenting the first subset of posts in the unified stream comprises obscuring the identifier for each user that publishes a post of the first subset of posts from the first entity when the particular entity is a first level registrant.

9. The computer-implemented method of claim 1, wherein the unified stream is a first unified stream generated in response to a request for credibility of the first entity, the computer-implemented method further comprising presenting the second subset of posts in a second unified stream that is generated in response to a request for credibility of the second entity.

10. The computer-implemented method of claim 1 further comprising computing a credibility score based on the sentiment that is expressed in each post of the first subset of posts.

11. The computer-implemented method of claim 10 further comprising presenting the credibility score in conjunction with presenting the first subset of posts in the unified stream.

12. The computer-implemented method of claim 1 further comprising adjusting a credibility score of the first entity based on sentiment from the first set of posts and a credibility score of the second entity based on sentiment from the second set of posts.

13. The computer-implemented method of claim 12 further comprising

presenting credibility of the first entity by providing the unified stream comprising the first set of posts and the credibility score for the first entity as adjusted based on the sentiment from the first set of posts;

and

presenting credibility of second entity by providing a second different stream comprising the second set of posts and the credibility score for the second entity as adjusted based on the sentiment from the second set of posts.

14. The computer-implemented method of claim 1 further comprising registering the first entity as a first level registrant and preventing the first entity from responding to any post of the first subset of posts and registering the second entity as a second level registrant that is a paying entity and not a free entity and permitting the second entity to respond to any post of the second subset of posts.

15. The computer-implemented method of claim 14 further comprising adjusting a credibility score of the second entity based on a response from the second entity to at least one post of the second subset of posts.

16. The computer-implemented method of claim 1 further comprising aggregating a new post from an online site of the plurality of online sites, determining that the new post is directed to the second entity based on natural language processing of the new post, and inserting the new post within a second different unified stream such that the new post is presented with the second subset of posts and not the first subset of posts.

17. The computer-implemented method of claim 1, wherein said extracting of the set of posts comprises discarding any posts from the plurality of posts that target the first entity and that do not affect the credibility of the first entity because of a lack of sentiment expressed towards the first entity or an offering of the first entity.

18. The computer-implemented method of claim 1, wherein presenting the first subset of posts in the unified stream comprises graphically differentiating the sentiment expressed in each post of the first subset of posts from other words of the post when presenting the unified stream.

19. The computer-implemented method of claim 1 further comprising computing an impact score for the sentiment of each post of the first subset of posts and presenting the impact score with the corresponding post from which the impact score is computed when presenting the unified stream.

23. The computer-implemented method of claim 1 further comprising receiving from the first entity, a first response to a first post of the first subset of posts and a second response to a second post of the first subset of posts.

24. The computer-implemented method of claim 23 further comprising passing (i) the first response to a user at a first online site that publishes the first post to the first online site and (ii) the second response to a different user at a different second different online that publishes the second post to the second online site without the first entity accessing either of the first online site or second online site.

25. The computer-implemented method of claim 1 further comprising identifying from the first subset of posts, a third subset of posts with each post of the third subset of posts comprising negative sentiment that is directed to (i) the first entity or (ii) an offering of the first entity.

26. The computer-implemented method of claim 25, wherein presenting the first subset of posts in the unified stream comprises presenting each post from the third subset of posts while omitting any post of the first subset of posts that is not also within the third subset of posts.

8. (canceled)

20. (canceled)

21. (canceled)

22. (canceled)