Determining post velocity

• US 9,548,958 B2
• Filed: 06/16/2015
• Issued: 01/17/2017
• Est. Priority Date: 06/16/2015
• Status: Active Grant

• Current Assignee: Maplebear Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Chakra, Al, Dunne, Jonathan, Harpur, Liam
• Primary Examiner(s): Cordero, Marivelisse Santiago
• Assistant Examiner(s): Ky, Kevin
• Application Number:
  US14/740,626
• Publication Number:
  US 20160373400A1
• Time in Patent Office: 581 Days
• Field of Search: 704/9
• US Class Current: 1/1
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/279 Recognition of textual entities
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: H04L 51/234 for tracking messages
• CPC Class Codes: H04L 51/52 for supporting social networking services

Abstract

Establishing the likely duration and precision with which the post was written is disclosed. An analysis may be used to infer how confident the user is of the subject matter they are writing. A user'"'"'s post (e.g., response, comment for, but not limited to, a thread, blog, community) may be monitored and its subject matter analyzed to determine benchmark style and speed with which a user can comment.

Claims

1. A method of estimating time to compose an electronic correspondence based on subject and target audience, comprising:

monitoring an originator composing a plurality of content posted on a plurality of social networking systems to a target audience to identify an origination time for each content;

running, by a processor, a natural language processing (NLP) technique and analytics to analyze the content from the originator to the target audience in the plurality of social networking system;

determining a content composition target audience style based on analysis performed by running the natural language processing (NLP) technique and analytics;

extracting average sentence length in words, average pause time between words, and average pause time between sentences associated with the content by running the natural language processing (NLP) technique and the analytics;

determining an average time for the originator to create content based on the content composition target audience style, the average sentence length in words, the average pause time between words, and the average pause time between sentences; and

responsive to receiving a new content by the originator with the content composition target audience style, providing an estimate of the time to compose the new content based on the average time.

2. The method of claim 1, wherein the social networking system type comprises at least one selected from the group consisting of instant messaging (IM), short message services (SMS), blog, web site, online social community, news feed, electronic mail (e-mail), and wiki.

3. The method of claim 1, wherein a response time to a request for information on a requesting social networking system by the originator is estimated based on the request, the target audience, and the requesting social networking system.

4. The method of claim 1, where the estimated response time to the request for information is provided to a business processing modeling (BPM) system.

5. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of estimating time to compose an electronic correspondence based on subject and target audience, comprising:

monitoring an originator composing a plurality of content posted on a plurality of social networking systems to a target audience to identify an origination time for each content;

running, by a processor, a natural language processing (NLP) technique and analytics to analyze the content from the originator to the target audience in the plurality of social networking system;

determining a content composition target audience style based on analysis performed by running the natural language processing (NLP) technique and analytics;

extracting average sentence length in words, average pause time between words, and average pause time between sentences associated with the content by running the natural language processing (NLP) technique and the analytics;

determining an average time for the originator to create content based on the content composition target audience style, the average sentence length in words, the average pause time between words, and the average pause time between sentences; and

responsive to receiving a new content by the originator with the content composition target audience style, providing an estimate of the time to compose the new content based on the average time.

6. The computer readable storage medium of claim 5, wherein the social networking system type comprises at least one selected from the group consisting of instant messaging (IM), short message services (SMS), blog, web site, online social community, news feed, electronic mail (e-mail), and wiki.

7. The computer readable storage medium of claim 5, wherein a response time to a request for information on a requesting social networking system by the originator is estimated based on the request, the target audience, and the requesting social networking system.

8. The computer readable storage medium of claim 5, where the estimated response time to the request for information is provided to a business processing modeling (BPM) system.

9. A system for estimating time to compose an electronic correspondence based on subject and target audience, comprising:

at least one hardware processor monitoring an originator composing a plurality of content posted on a plurality of social networking systems to a target audience to identify an origination time for each content,

the at least one hardware processor running a natural language processing (NLP) technique and analytics to analyze the content from the originator to the target audience in the plurality of social networking system,

the at least one hardware processor determining a content composition target audience style based on analysis performed by running the natural language processing (NLP) technique and analytics,

the at least one hardware processor extracting average sentence length in words, average pause time between words, and average pause time between sentences associated with the content by running the natural language processing (NLP) technique and the analytics;

the at least one hardware processor determining an average time for the originator to create content based on the content composition target audience style, the average sentence length in words, the average pause time between words, and the average pause time between sentences

responsive to receiving a new content by the originator with the content composition target audience style, the at least one hardware processor providing an estimate of the time to compose the new content based on the average time.

10. The system of claim 9, wherein one or more factors for estimating the time to compose the new content comprises at least one factor selected from the group consisting of social networking system type, target audience, average sentence length in words, average pause time between words, and average pause time between sentences.

11. The system of claim 10, wherein the social networking system type comprises at least one selected from the group consisting of instant messaging (IM), short message services (SMS), blog, web site, online social community, news feed, electronic mail (e-mail), and wiki.

12. The system of claim 10, wherein a response time to a request for information on a requesting social networking system by the originator is estimated based on the request, the target audience, and the requesting social networking system.

13. The system of claim 10, where the estimated response time to the request for information is provided to a business processing modeling (BPM) system.