Analyzing content demand using social signals
View Patent ↗Software at an online contributor website receives a list of websites having online publications. The software gathers counts of user signals for each online publication on each of the websites on the list. And the software determines content descriptors for each of the online publications. The software then counts the online publications at each website associated with each of the content descriptors and counts the user signals at each website associated with each content descriptor. The software displays the content descriptors for each website in a graphic in a graphical user interface, where the size of each content descriptor in the graphic reflects the count of online publications associated with the content descriptor and where the color of each content descriptor in the graphic reflects the count of user signals associated with the content descriptor.
1. A method for evaluating content descriptors for online publications, comprising the operations of:
receiving a list of websites having online publications;
gathering counts of user signals for each online publication on each website;
determining content descriptors for each online publication;
counting the online publications at each website associated with each content descriptor; and
counting the user signals at each website associated with each content descriptor, wherein each operation of the method is executed by one or more processors.
2. The method of claim 1 , further comprising the operation of displaying the content descriptors for each website in a graphic in a graphical user interface, wherein the size of each content descriptor in the graphic reflects the count of online publications associated with the content descriptor and wherein the color of each content descriptor in the graphic reflects the count of user signals associated with the content descriptor.
3. The method of claim 1 , wherein the counts associated with content descriptors are used to recommend topics in a graphical user interface displayed to editors or contributors by a website for an online contributor network.
4. The method of claim 1 , wherein the content descriptors are keywords.
5. The method of claim 1 , wherein the user signals are social signals.
6. The method of claim 1 , wherein the user signals are selected from the group consisting of likes, shares, comments, tweets, favorites, and upvotes.
7. The method of claim 1 , wherein the user signals are pageviews.
8. The method of claim 1 , wherein the gathering of counts of user signals involves accessing an application programming interface.
9. The method of claim 8 , wherein the application programming interface is provided by a social networking website.
10. A computer-readable storage medium persistently storing a program, wherein the program, when executed, instructs one or more processors to perform the following operations:
receive a list of websites having online publications;
gather counts of user signals for each online publication on each website;
determine content descriptors for each online publication;
count the online publications at each website associated with each content descriptor; and
count the user signals at each website associated with each content descriptor.
11. The computer-readable storage medium of claim 10 , further comprising the operation of displaying the content descriptors for each website in a graphic in a graphical user interface, wherein the size of each content descriptor in the graphic reflects the count of online publications associated with the content descriptor and wherein the color of each content descriptor in the graphic reflects the count of user signals associated with the content descriptor.
12. The computer-readable storage medium of claim 10 , wherein the counts associated with content descriptors are used to recommend topics in a graphical user interface displayed to editors or contributors by a website for an online contributor network.
13. The computer-readable storage medium of claim 10 , wherein the content descriptors are keywords.
14. The computer-readable storage medium of claim 10 , wherein the user signals are social signals.
15. The computer-readable storage medium of claim 10 , wherein the user signals are selected from the group consisting of likes, shares, comments, tweets, favorites, and upvotes.
16. The computer-readable storage medium of claim 10 , wherein the user signals are pageviews.
17. The computer-readable storage medium of claim 10 , wherein the gathering of counts of user signals involves accessing an application programming interface.
18. The computer-readable storage medium of claim 17 , wherein the application programming interface is provided by a social networking website.
19. A method for recommending topics to editors or contributors to an online contributor network, comprising the operations of:
receiving a list of websites having online publications;
gathering counts of social signals for each online publication on each website, through one or more application programming interfaces;
determining keywords for each online publication;
counting the online publications at each website associated with each keyword;
counting the social signals at each website associated with each keyword; and
recommending topics to editors or contributors to an online contributor network based at least in part on the counts, wherein each operation of the method is executed by one or more processors.
20. The method of claim 19 , wherein the recommending includes displaying the keyword for each website in a graphic in a graphical user interface and wherein the size of ach keyword in the graphic reflects the count of online publications associated with the keyword and wherein the color of each keyword in the graphic reflects the count of social signals associated with the keyword.