IP Library Granted Patent US 10,303,801
Granted Patent B2
US 10,303,801 · App. 15/390,239 · Granted May 28, 2019

Visual meme tracking for social media analysis

Inventors: Matthew L. Hill (Yonkers, NY); John R. Kender (Leonia, NJ); Apostol I. Natsev (Harrison, NY); John R. Smith (New York, NY); Lexing Xie (White Plains, NY)
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
G06F17/3079G06F17/30017G06F17/30781G06F17/30867G06F17/30958G06F17/30964
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Quick Facts
Patent No.
US 10,303,801
App. No.
15/390,239
Granted
May 28, 2019
Kind
B2
Abstract

A system and method for analyzing visual memes includes identifying visual memes associated with at least one topic in a data source. The visual memes propagated over time are tracked to extract information associated with identified visual memes. The information associated with the visual memes is analyzed to determine at least one of generation, propagation, and use of the identified memes.

Claims (29)

1. A method for visual meme tracking for social media analysis, comprising:

identifying at least one visual meme from one or more social media platforms, the visual meme being non-textual and associated with at least one topic in a data source;

tracking the at least one visual meme, propagated over time, the tracking including performing visual feature matching by extracting visual features associated with identified visual memes and modeling the identified visual memes as links in people-content networks and as words in multimedia collections, the visual features including one or more color-correlograms extracted from one or more normalized frames for determining a similarity metric; and

analyzing, using a processor, the similarity metric and the visual features associated with the identified visual memes, the analyzing determining at least one of generation, propagation, and use of the identified memes, and further determining meanings of the identified visual memes using cross modal matching.

2. The method as recited in claim 1 , wherein tracking includes performing visual feature matching including employing one or more visual features including one or more of color-correlograms, local interest points, and thumbnail vectors.

3. The method as recited in claim 1 , wherein tracking includes both visual feature matching and temporal alignment.

4. The method as recited in claim 1 , wherein tracking includes matching visual memes using a high-dimensional indexing method.

5. The method as recited in claim 4 , wherein the high-dimensional indexing method includes one or more of a kd-tree, a k-means tree, ball tree, and an approximate nearest-neighbor method.

6. The method as recited in claim 1 , wherein analyzing includes determining an influence score for pieces of content based on meme graphs constructed on at least one of authors and content.

7. The method as recited in claim 1 , wherein analyzing includes identifying influential users based on a diffusion index on meme graphs constructed on one of authors and content.

8. The method as recited in claim 1 , wherein tracking includes tracking content trends using a multimodal topic analysis.

9. The method as recited in claim 1 , wherein tracking includes tracking a content distribution using topic graphs created on visual memes.

10. The method as recited in claim 1 , wherein analyzing includes identifying influential users based on timing and popularity of posted memes.

11. The method as recited in claim 1 , wherein analyzing include tagging the visual memes with other words in text or other memes derived from one or more of graph and topic analyses.

12. A computer readable storage medium comprising a computer readable program for visual meme tracking for social media analysis, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:

identifying at least one visual meme from one or more social media platforms, the visual meme being non-textual and associated with at least one topic in a data source;

tracking the at least one visual meme, propagated over time, the tracking including performing visual feature matching by extracting visual features associated with identified visual memes and modeling the identified visual memes as links in people-content networks and as words in multimedia collections, the visual features including one or more color-correlograms extracted from one or more normalized frames for determining a similarity metric; and

analyzing, using a processor, the similarity metric and the visual features associated with the identified visual memes, the analyzing determining at least one of generation, propagation, and use of the identified memes, and further determining meanings of the identified visual memes using cross modal matching.

13. The computer readable storage medium as recited in claim 12 , wherein tracking includes performing visual feature matching including employing one or more visual features.

14. The computer readable storage medium as recited in claim 12 , wherein tracking includes both visual feature matching and temporal alignment.

15. The computer readable storage medium as recited in claim 12 , wherein tracking includes matching visual memes using a high-dimensional indexing method.

16. The computer readable storage medium as recited in claim 12 , wherein analyzing includes determining an influence score for pieces of content based on meme graphs constructed on at least one of authors and content.

17. The computer readable storage medium as recited in claim 12 , wherein analyzing includes identifying influential users based on a diffusion index on meme graphs constructed on one of authors and content.

18. The computer readable storage medium as recited in claim 12 , wherein tracking includes tracking content trends using a multimodal topic analysis.

19. The computer readable storage medium as recited in claim 12 , wherein tracking includes tracking a content distribution using topic graphs created on visual memes.

20. A system for visual meme tracking for social media analysis, comprising:

a memory coupled to a processor, the memory storing an analysis module configured to identify and track visual memes from one or more social media platforms, the visual memes being non-textual and associated with at least one topic in a data source, the analysis module further comprising:

a tracking module configured to collect visual features associated with identified visual memes, the tracking module being further configured to perform visual feature matching by extracting visual features associated with identified visual memes as the visual memes are propagated over time, and to generate models for the identified visual memes as links in people-content networks and as words in multimedia collections, the visual features including one or more color-correlograms extracted from one or more normalized frames for determining a similarity metric; and

a trend determination module configured to discover trends by analyzing the similarity metric and the visual features associated with the visual meme to determine at least one of generation, propagation, and use of the identified memes, and further to determine meanings of the identified visual memes using cross modal matching.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 15, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: AIRBNB, INC.
Reel/Frame 056427/0193 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 2, 2017
From: KENDER, JOHN R.; NATSEV, APOSTOL I.; SMITH, JOHN R.; XIE, LEXING; HILL, MATTHEW L.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 044015/0335 →
Continuity (2)
Continuation 12909137 · Oct 21, 2010
Related Publication 20170109360A1 · Apr 20, 2017