SYSTEM AND METHOD FOR PROVIDING USERS FEEDBACK REGARDING THEIR READING HABITS

• US 20190018834A1
• Filed: 07/26/2018
• Published: 01/17/2019
• Est. Priority Date: 01/03/2014
• Status: Active Grant

• Current Assignee: Yahoo Assets LLC
• Original Assignee: Oath Inc. (Verizon Communications Inc.)
• Inventors: LIU, Agnes
• Granted Patent: US 10,885,271 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 21/1063 Personalisation
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 3/04817 using icons graphical or visual programming using iconic symbols G06F8/34
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Various embodiments of the present disclosure relate to systems and methods for dynamically modifying images based on the content of articles associated with the images, particularly the emotional content of an article. Among other things, embodiments of the present disclosure allow users to quickly and easily identify the emotional nature of an article based on such an image. Characteristics of an image associated with an article may also be modified in response to comments from viewers regarding the article.

Claims

1-20. -20. (canceled)

21. A method, comprising:

prior to displaying an article on a user device, analyzing content in the article, wherein the article contains an image, and analyzing content in the article includes performing an image recognition process on the image;

modifying, based on analyzing the content, a visual characteristic of the article;

receiving, from at least one social media source, comments regarding the article;

analyzing the comments;

modifying, based on analyzing the comments, the visual characteristic of the article; and

after modifying the visual characteristic of the article based on analyzing the comments, transmitting the article to the user device for display.

22. The method of claim 21, wherein the visual characteristic is at least one of a size, a shape, or a color.

23. The method of claim 21, wherein the visual characteristic is modified at least based on a volume of the received comments.

24. The method of claim 21, wherein the visual characteristic is modified at least based on at least one keyword in the received comments.

25. The method of claim 21, wherein the visual characteristic is modified at least based on a manner in which each viewer responds to the article.

26. The method of claim 25, wherein the manner in which each viewer responds to the article is a respective rating of the article.

27. The method of claim 21, wherein the comments are first comments, the method further comprising:

after modifying the visual characteristic of the article based on analyzing the first comments, receiving second comments regarding the article;

analyzing the second comments;

modifying, based on analyzing the second comments, the visual characteristic of the article; and

after modifying the visual characteristic of the article based on analyzing the second comments, transmitting the article to the user device for display.

28. A system comprising:

a processor; and

a storage medium in communication with the processor for storing thereon computer instructions that, when executed by the processor, cause the system to;

analyze content in a first article, wherein analyzing the content includes performing an image recognition process on an image;

modify, based on analyzing the content, a visual characteristic of the first article;

receive, from at least one social media source, comments regarding the first article;

analyze the comments;

modify, based on analyzing the comments, a visual characteristic of a second article; and

after modifying the visual characteristic of the second article, cause the second article to be presented on a display of a user device.

29. The system of claim 28, wherein the computer instructions further cause the system to:

modify, based on analyzing the comments, the visual characteristic of the first article; and

after modifying the visual characteristic of the first article, cause the first article to be presented on the display of the user device.

30. The system of claim 28, wherein the computer instructions further cause the system to:

identify keywords in the first article; and

assign weights to each of the keywords;

wherein modifying the visual characteristic of at least one of the first article or the second article is based at least on the assigned weights.

31. The system of claim 28, wherein:

analyzing the content in the first article further includes analyzing audio content; and

modifying the visual characteristic of the first article is further based on analyzing the audio content.

32. A non-transitory computer-readable medium storing instructions that, when executed by a processor of a computer system, cause the computer system to:

analyze content in an article, wherein analyzing the content comprises performing an image recognition process;

receive, from at least one social media source, comments regarding the article;

analyze the comments;

modify, based on analyzing the content and analyzing the comments, a visual characteristic of the article; and

after modifying the visual characteristic of the article, transmit the article to a user device for display.

33. The non-transitory computer-readable medium of claim 32, wherein the visual characteristic is a shading, and the instructions further cause the computer system to vary the shading as additional comments are received from the at least one social media source.

34. The non-transitory computer-readable medium of claim 32, wherein the article is transmitted to the user device as part of a content digest.

35. The non-transitory computer-readable medium of claim 32, wherein the visual characteristic is a first visual characteristic, and the instructions further cause the computer system to modify a second visual characteristic of the article based on additional comments received from the at least one social media source.

36. The non-transitory computer-readable medium of claim 32, wherein the article is posted on a website, and the comments regarding the article are received from viewers of the article on the website.

37. The non-transitory computer-readable medium of claim 32, wherein the visual characteristic is modified further based on a volume of the comments.

38. The non-transitory computer-readable medium of claim 37, wherein the visual characteristic is modified further based on at least one keyword in the comments.

39. The non-transitory computer-readable medium of claim 32, wherein the instructions further cause the computer system to:

identify keywords in the article; and

assign weights to each of the keywords;

wherein modifying the visual characteristic is based at least on the assigned weights.

40. The non-transitory computer-readable medium of claim 32, wherein the article is a first article, and the instructions further cause the computer system to:

modify, based on analyzing at least one of the content or the comments, a visual characteristic of a second article; and

after modifying the visual characteristic of the second article, cause the second article to be presented on a display of the user device.