COMMENTARY MANAGEMENT IN A SOCIAL NETWORKING ENVIRONMENT WHICH INCLUDES A SET OF MEDIA CLIPS

• US 20170300492A1
• Filed: 04/14/2016
• Published: 10/19/2017
• Est. Priority Date: 04/14/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bradley, Lisa M., Dunne, Jonathan, Harpur, Liam, Silva, Asima
• Granted Patent: US 10,642,884 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

Disclosed aspects relate to commentary management in a social networking environment. The social networking environment may include a set of media clips. The set of media clips may be analyzed in the social networking environment with respect to a set of commentary typology data. Based on the analyzing, a set of benchmark typology data which indicates a set of commentary norms of the set of media clips may be determined. A set of benchmark typology data may be established for utilization by the social networking environment.

Claims

1. A computer-implemented method for commentary management in a social networking environment which includes a set of media clips that have audio, the method comprising:

analyzing, with respect to a set of commentary typology criteria, the set of media clips in the social networking environment;

determining, based on the analyzing, a set of benchmark typology data which indicates a set of commentary norms of the set of media clips that have audio; and

establishing, for utilization by the social networking environment, the set of benchmark typology data.

2. The method of claim 1, wherein the set of commentary typology criteria includes a selection from a group consisting of at least one of:

a smile criterion, an eye focus criterion, a facial expression criterion, a body language criterion, a gesture rate criterion, a disposition criterion, a style criterion, a mood criterion, a vocal tone criterion, a speech pace criterion, a topic criterion, a theme criterion, a word tone criterion, a language brevity criterion, or a key word criterion.

3. The method of claim 1, wherein the set of benchmark typology data includes a selection from a group consisting of at least one of:

a smile benchmark value, an eye focus benchmark value, a facial expression benchmark value, a body language benchmark value, a gesture rate benchmark value, a disposition benchmark value, a style benchmark value, a mood benchmark value, a vocal tone benchmark value, a speech pace benchmark value, a topic benchmark value, a theme benchmark value, a word tone benchmark value, a language brevity benchmark value, or a key word benchmark value.

4. The method of claim 1, further comprising:

identifying, using the set of benchmark typology data, a target set of typology elements for a new media clip; and

providing, by the social networking environment to a user, the target set of typology elements for the new media clip.

5. The method of claim 4, wherein the target set of typology elements includes:

a smile factor, an eye focus factor, a facial expression factor, a body language factor, and a gesture rate factor.

6. The method of claim 4, wherein the target set of typology elements includes:

a disposition factor, a style factor, a mood factor, a vocal tone factor, and a speech pace factor.

7. The method of claim 4, wherein the target set of typology elements includes:

a topic factor, a theme factor, a word tone factor, a language brevity factor, and a key word factor.

8. The method of claim 4, wherein providing the target set of typology elements for the new media clip:

presents a set of suggested target information in advance of generating the new media clip for utilization to align the new media clip with the set of media clips.

9. The method of claim 1, further comprising:

receiving a new media clip;

computing, based on the new media clip, a computed set of typology elements for the new media clip; and

providing, by the social networking environment to a user, the computed set of typology elements for the new media clip.

10. The method of claim 9, wherein the computed set of typology elements includes:

a smile factor, an eye focus factor, a facial expression factor, a body language factor, and a gesture rate factor.

11. The method of claim 9, wherein the computed set of typology elements includes:

a disposition factor, a style factor, a mood factor, a vocal tone factor, and a speech pace factor.

12. The method of claim 9, wherein the computed set of typology elements includes:

a topic factor, a theme factor, a word tone factor, a language brevity factor, and a key word factor.

13. The method of claim 9, further comprising:

ascertaining, by comparing the computed set of typology elements for the new media clip with the set of benchmark typology data, an alignment score for the new media clip with respect to the set of media clips; and

providing the alignment score to the user.

14. The method of claim 9, wherein providing the computed set of typology elements for the new media clip:

presents a set of computed information in response to receiving the new media clip for utilization to compare alignment of the new media clip with the set of media clips.

15. The method of claim 1, further comprising:

monitoring, by the social networking environment, for a threshold change in the set of benchmark typology data;

detecting, by the social networking environment based on the set of benchmark typology data, the threshold change in the set of benchmark typology data;

determining, based on the threshold change in the set of benchmark typology data, a new arrangement of the set of media clips that have audio, wherein the new arrangement includes both a first subset of the set of media clips and a second subset of the set of media clips; and

constructing, in the social networking environment, the new arrangement to have the first subset of the set of media clips separate from the second subset of the set of media clips.

16. The method of claim 1,

identifying, by the social networking environment, the set of benchmark typology data for a set of users which correlate with the set of media clips;

determining, by the social networking environment based on the set of benchmark typology data for the set of users, a sentiment trend of the set of users which correlate with the set of media clips; and

providing, by the social networking environment to a user, the sentiment trend.

17. The method of claim 1, wherein determining the set of benchmark typology data which indicates the set of commentary norms of the set of media clips that have audio includes:

calculating, using a clustering technique, the set of commentary norms; and

formulating, based on the set of commentary norms, the set of benchmark typology data.

18. A system for commentary management in a social networking environment which includes a set of media clips, the system comprising:

a memory having a set of computer readable computer instructions, and a processor for executing the set of computer readable instructions, the set of computer readable instructions including;

analyzing, with respect to a set of commentary typology criteria, the set of media clips in the social networking environment;

determining, based on the analyzing, a set of benchmark typology data which indicates a set of commentary norms of the set of media clips; and

establishing, for utilization by the social networking environment, the set of benchmark typology data.

19. A computer program product for commentary management in a social networking environment which includes a set of media clips, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:

analyzing, with respect to a set of commentary typology criteria, the set of media clips in the social networking environment;

determining, based on the analyzing, a set of benchmark typology data which indicates a set of commentary norms of the set of media clips; and

establishing, for utilization by the social networking environment, the set of benchmark typology data.

20. The computer program product of claim 19, wherein at least one of:

the program instructions are stored in a computer readable storage medium in a data processing system, and wherein the program instructions were downloaded over a network from a remote data processing system;

or the program instructions are stored in a computer readable storage medium in a server data processing system, and wherein the program instructions are downloaded over a network to a remote data processing system for use in a computer readable storage medium with the remote data processing system.