Method and system for supplementing job postings with social network data

Abstract

The present application present systems and methods for leveraging existing sources of information to supplement and enhance job opening postings and other types of business postings. A plurality of sources, including social network sites, talent profiles, and/or surveys and questionnaires are accessed in order to retrieve data relating to a business object. The retrieved data is transformed, such that it may be used to supplement job opening postings and other types of postings with job description data, work culture data, and other business-related data in order to build a social brand for the business.

What is claimed is: 
     
         1 . method implemented with a processor for performing social branding for a post object, comprising:
 accessing a plurality of data sources stored on a plurality of computing systems, wherein the plurality of data sources includes a public social network source and a private social network source, wherein a private social network comprises a social network internal to a specific company and a public social network is not internal to the specific company;   retrieving content from the plurality of data sources generated by a plurality of users;   identifying a posting to be supplemented based on at least some of the content from the plurality of data sources, the posting comprising a post object created by the specific company and corresponding to the specific company;   analyzing the content from the plurality of data sources to identify a subset of the content related to the post object, wherein a first content from the public social network source is filtered differently than a second content from the private social network source by subjecting both the first content and the second content to semantic filtering, wherein a first level of semantic filtering is imposed on the first content and a second level of semantic filtering is imposed on the second content, the first level of semantic filtering reducing a greater amount of irrelevant data than the second level of semantic filtering;   performing a transformation on the subset of the content related to the post object to form transformed content; and   supplementing the posting with at least some of the transformed content by adding the transformed content to the post object, the transformed content being based at least in part on the subset of the content related to the post object and comprising information corresponding to the posting or an organization that posted the posting.   
     
     
         2 . The method of  claim 1 , wherein the plurality of data sources comprises social network sources. 
     
     
         3 . The method of  claim 2 , wherein the subset of the content related to the post object comprises one or more social network conversations. 
     
     
         4 . The method of  claim 2 , wherein the subset of the content related to the post object comprises profile information corresponding to one or more users of the plurality of users, wherein the one or more users are associated with the post object. 
     
     
         5 . The method of  claim 3 , wherein performing a transformation on the subset of the content related to the post object comprises identifying an excerpt of a conversation of the one or more social network conversations, wherein the excerpt of the conversation is used to supplement the posting. 
     
     
         6 . The method of  claim 4 , wherein performing a transformation on the subset of the content related to the post object comprises aggregating the subset of the content related to the post object to produce one or more pieces of aggregated content. 
     
     
         7 . The method of  claim 3 , wherein analyzing the content from the plurality of data sources comprises performing semantic analysis on the one or more social network conversations, and applying one or more tags to the one or more social network conversations based at least in part upon a result of the semantic analysis. 
     
     
         8 . The method of  claim 3 , wherein analyzing the content from the plurality of data sources comprises identifying a conversation of the one or more social network conversations based at least in part upon one or more tags associated with the conversation. 
     
     
         9 . The method of  claim 3 , wherein analyzing the content from the plurality of data sources comprises identifying a user of the plurality of users related to the post object, and wherein the one or more social network conversations comprise conversations participated in by the user. 
     
     
         10 . A non-transitory computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process for performing social branding for a post object comprising:
 accessing a plurality of data sources stored on a plurality of computing systems, wherein the plurality of data sources includes a public social network source and a private social network source, wherein a private social network comprises a social network internal to a specific company and a public social network is not internal to the specific company;   retrieving content from the plurality of data sources generated by a plurality of users;   identifying a posting to be supplemented based on at least some of the content from the plurality of data sources, the posting comprising a post object created by the specific company and corresponding to the specific company;   analyzing the content from the plurality of data sources to identify a subset of the content related to the post object, wherein a first content from the public social network source is filtered differently than a second content from the private social network source by subjecting both the first content and the second content to semantic filtering, wherein a first level of semantic filtering is imposed on the first content and a second level of semantic filtering is imposed on the second content, the first level of semantic filtering reducing a greater amount of irrelevant data than the second level of semantic filtering;   performing a transformation on the subset of the content related to the post object to form transformed content; and   supplementing the posting with at least some of the transformed content by adding the transformed content to the post object, the transformed content being based at least in part on the subset of the content related to the post object and comprising information corresponding to the posting or an organization that posted the posting.   
     
     
         11 . The computer readable medium of  claim 10 , wherein the plurality of data sources comprises social network sources. 
     
     
         12 . The computer readable medium of  claim 11 , wherein the subset of the content related to the post object comprises one or more social network conversations. 
     
     
         13 . The computer readable medium of  claim 11 , wherein the subset of the content related to the post object comprises profile information corresponding to one or more users of the plurality of users, wherein the one or more users are associated with the post object. 
     
     
         14 . The computer readable medium of  claim 12 , wherein performing a transformation on the subset of the content related to the post object comprises identifying an excerpt of a conversation of the one or more social network conversations, wherein the excerpt of the conversation is used to supplement the posting. 
     
     
         15 . The computer readable medium of  claim 13 , wherein performing a transformation on the subset of the content related to the post object comprises aggregating the subset of the content related to the post object to produce one or more pieces of aggregated content. 
     
     
         16 . The computer readable medium of  claim 12 , wherein analyzing the content from the plurality of data sources comprises performing semantic analysis on the one or more social network conversations, and applying one or more tags to the one or more social network conversations based at least in part upon a result of the semantic analysis. 
     
     
         17 . The computer readable medium of  claim 12 , wherein analyzing the content from the plurality of data sources comprises identifying a conversation of the one or more social network conversations based at least in part upon one or more tags associated with the conversation. 
     
     
         18 . The computer readable medium of  claim 12 , wherein analyzing the content from the plurality of data sources comprises identifying a user of the plurality of users related to the post object, and wherein the one or more social network conversations comprise conversations participated in by the user. 
     
     
         19 . A system, comprising:
 a processor;   a memory comprising computer code executed using the processor, in which the computer code implements:
 accessing a plurality of data sources stored on a plurality of computing systems, wherein the plurality of data sources includes a public social network source and a private social network source, wherein a private social network comprises a social network internal to a specific company and a public social network is not internal to the specific company; 
 retrieving content from the plurality of data sources generated by a plurality of users; 
 identifying a posting to be supplemented based on at least some of the content from the plurality of data sources, the posting comprising a post object created by the specific company and corresponding to the specific company; 
 analyzing the content from the plurality of data sources to identify a subset of the content related to the post object, wherein a first content from the public social network source is filtered differently than a second content from the private social network source by subjecting both the first content and the second content to semantic filtering, wherein a first level of semantic filtering is imposed on the first content and a second level of semantic filtering is imposed on the second content, the first level of semantic filtering reducing a greater amount of irrelevant data than the second level of semantic filtering; 
 performing a transformation on the subset of the content related to the post object to form transformed content; and 
 supplementing the posting with at least some of the transformed content by adding the transformed content to the post object, the transformed content being based at least in part on the subset of the content related to the post object and comprising information corresponding to the posting or an organization that posted the posting. 
   
     
     
         20 . The system of  claim 19 , wherein the plurality of data sources comprises social network sources. 
     
     
         21 . The system of  claim 20 , wherein the subset of the content related to the post object comprises one or more social network conversations. 
     
     
         22 . The system of  claim 20 , wherein the subset of the content related to the post object comprises profile information corresponding to one or more users of the plurality of users, wherein the one or more users are associated with the post object. 
     
     
         23 . The system of  claim 21 , wherein performing a transformation on the subset of the content related to the post object comprises identifying an excerpt of a conversation of the one or more social network conversations, wherein the excerpt of the conversation is used to supplement the posting. 
     
     
         24 . The system of  claim 22 , wherein performing a transformation on the subset of the content related to the post object comprises aggregating the subset of the content related to the post object to produce one or more pieces of aggregated content. 
     
     
         25 . The system of  claim 21 , wherein analyzing the content from the plurality of data sources comprises performing semantic analysis on the one or more social network conversations, and applying one or more tags to the one or more social network conversations based at least in part upon a result of the semantic analysis. 
     
     
         26 . The system of  claim 21 , wherein analyzing the content from the plurality of data sources comprises identifying a conversation of the one or more social network conversations based at least in part upon one or more tags associated with the conversation. 
     
     
         27 . The system of  claim 21 , wherein analyzing the content from the plurality of data sources comprises identifying a user of the plurality of users related to the post object, and wherein the one or more social network conversations comprise conversations participated in by the user.