IP Library Granted Patent US 9,208,248
Granted Patent B2
US 9,208,248 · App. 13/969,099 · Granted Dec 8, 2015

Social network posting analysis using degree of separation correlation

Inventors: Kelley L. Anders (East New Market, MD); Trudy L. Hewitt (Cary, NC)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06F17/3089G06Q50/01
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Quick Facts
Patent No.
US 9,208,248
App. No.
13/969,099
Granted
Dec 8, 2015
Kind
B2
Abstract

A degree of social network separation of a social network user that generated expressive content of a social media posting is identified relative to a specified social network user for each of a group of social media postings. Social media postings with an equivalent identified degree of social network separation relative to the specified social network user are grouped. Differences between the expressive content of the grouped social media postings at different degrees of social network separation are determined. The determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation are rendered.

Claims (22)

1. A method, comprising:

identifying, via a processor, 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;

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

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

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

2. The method of claim 1 , where identifying, via the processor, 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 comprises identifying the degree of social network separation across multiple social networks.

3. The method 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 determining the differences between the expressive content of the grouped social media postings at the different degrees of social network separation comprises:

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

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

4. The method of claim 3 , where determining the differences between the expressive content of the grouped social media postings at the different degrees of social network separation further comprises:

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

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

5. The method of claim 1 , where:

determining the differences between the expressive content of the grouped social media postings at the different degrees of social network separation comprises determining a trend of opinion change across the different degrees of social network separation; and

rendering the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation comprises graphically rendering the determined trend of opinion change across the different degrees of social network separation.

6. The method of claim 1 , where determining the differences between the expressive content of the grouped social media postings at the different degrees of social network separation comprises:

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

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

identifying 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 method of claim 1 , further comprising:

identifying, 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 rendering the determined differences between the expressive content of the grouped social media postings at the different degrees of social network separation comprises graphically rendering the identified degree of separation at which to focus the efforts to influence opinion change.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 3, 2024
From: BEIJING PIANRUOJINGHONG TECHNOLOGY CO., LTD.
To: BEIJING ZITIAO NETWORK TECHNOLOGY CO., LTD.
Reel/Frame 066565/0952 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 4, 2023
From: AWEMANE LTD.
To: BEIJING PIANRUOJINGHONG TECHNOLOGY CO., LTD.
Reel/Frame 064501/0498 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 2, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: AWEMANE LTD.
Reel/Frame 057991/0960 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 16, 2013
From: ANDERS, KELLEY L.; HEWITT, TRUDY L.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 031027/0828 →
Continuity (2)
Continuation 13964767 · Aug 12, 2013
Related Publication 20150046454A1 · Feb 12, 2015