Social network posting analysis using degree of separation correlation

1. A system, comprising:

a output device; and

a processor programmed to:

identify, relative to a specified social network user for each of a plurality of social media postings, a degree of social network separation of a social network user that generated expressive content of the respective social media posting;

group social media postings that comprise an equivalent identified degree of social network separation relative to the specified social network user;

determine differences between the expressive content of the grouped social media postings at different degrees of social network separation; and

render, via the output device, the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation.

2. The system of claim 1 , where, in being programmed to identify, relative to the specified social network user for each of the plurality of social media postings, the degree of social network separation of the social network user that generated the expressive content of the respective social media posting, the processor is programmed to identify the degree of social network separation across multiple social networks.

3. The system of claim 1 , where the expressive content of the grouped social media postings comprises expressed opinions within the social media postings related to a topic, and where, in being programmed to determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the processor is programmed to:

correlate, within each group of social media postings, similar expressed opinions of social media postings into expressed opinion sets; and

determine differences between the correlated expressed opinion sets within each group of social media postings.

4. The system of claim 3 , where, in being programmed to determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the processor is further programmed to:

determine a predominant opinion among the correlated expressed opinion sets within each group of social media postings; and

determine differences between the predominant opinions across the groups of social media postings at the different degrees of social network separation.

5. The system of claim 1 , where, in being programmed to:

determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the processor is programmed to determine a trend of opinion change across the different degrees of social network separation; and

render, via the output device, the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the processor is programmed to graphically render, via the output device, the determined trend of opinion change across the different degrees of social network separation.

6. The system of claim 1 , where, in being programmed to determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the processor is programmed to:

analyze text of the expressive content of the social media postings within each group of social media postings;

categorize the expressive content based upon a frequency of similar expressive content within each group of social media postings; and

identify a highest-frequency expressive content within each group of social media postings as a predominant expressive content of social network users in each group of social media postings.

7. The system of claim 1 , where the processor is further programmed to:

identify, among the different degrees of social network separation, a degree of separation at which to focus efforts to influence opinion change based upon a greatest deviation of opinion within the expressive content relative to a target configured opinion; and

where, in being programmed to render, via the output device, the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the processor is programmed to graphically render, via the output device, the identified degree of separation at which to focus the efforts to influence opinion change.

8. A computer program product, comprising:

a non-transitory computer readable storage medium having computer readable program code embodied therewith, where the computer readable program code when executed on a computer causes the computer to:

identify, relative to a specified social network user for each of a plurality of social media postings, a degree of social network separation of a social network user that generated expressive content of the respective social media posting;

group social media postings that comprise an equivalent identified degree of social network separation relative to the specified social network user;

determine differences between the expressive content of the grouped social media postings at different degrees of social network separation; and

render the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation.

9. The computer program product of claim 8 , where, in causing the computer to identify relative to the specified social network user for each of the plurality of social media postings, the degree of social network separation of the social network user that generated the expressive content of the respective social media posting, the computer readable program code when executed on the computer causes the computer to identify the degree of social network separation across multiple social networks.

10. The computer program product of claim 8 , where the expressive content of the grouped social media postings comprises expressed opinions within the social media postings related to a topic, and where, in causing the computer to determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the computer readable program code when executed on the computer causes the computer to:

correlate, within each group of social media postings, similar expressed opinions of social media postings into expressed opinion sets; and

determine differences between the correlated expressed opinion sets within each group of social media postings.

11. The computer program product of claim 10 , where, in causing the computer to determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the computer readable program code when executed on the computer further causes the computer to:

determine a predominant opinion among the correlated expressed opinion sets within each group of social media postings; and

determine differences between the predominant opinions across the groups of social media postings at the different degrees of social network separation.

12. The computer program product of claim 8 , where, in causing the computer to:

determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the computer readable program code when executed on the computer causes the computer to determine a trend of opinion change across the different degrees of social network separation; and

render the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the computer readable program code when executed on the computer causes the computer to graphically render the determined trend of opinion change across the different degrees of social network separation.

13. The computer program product of claim 8 , where, in causing the computer to determine the differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the computer readable program code when executed on the computer causes the computer to:

analyze text of the expressive content of the social media postings within each group of social media postings;

categorize the expressive content based upon a frequency of similar expressive content within each group of social media postings; and

identify a highest-frequency expressive content within each group of social media postings as a predominant expressive content of social network users in each group of social media postings.

14. The computer program product of claim 8 , where the computer readable program code when executed on the computer further causes the computer to:

identify, among the different degrees of social network separation, a degree of separation at which to focus efforts to influence opinion change based upon a greatest deviation of opinion within the expressive content relative to a target configured opinion; and

where, in causing the computer to render the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation, the computer readable program code when executed on the computer causes the computer to graphically render the identified degree of separation at which to focus the efforts to influence opinion change.