Displaying social networking system user information via a historical newsfeed
The invention provides a display interface in a social networking system that enables the presentation of information related to a user in a timeline or map view. The system accesses information about a user of a social networking system, including both data about the user and social network activities related to the user. The system then selects one or more of these pieces of data and/or activities from a certain time period and gathers them into timeline units based on their relatedness and their relevance to users. These timeline units are ranked by relevance to the user, and are used to generate a timeline or map view for the user containing visual representations of the timeline units organized by location or time. The timeline or map view is then provided to other users of the social networking system that wish to view information about the user.
1. A method comprising:
accessing narrative data related to a viewing user of a social networking system, each item of narrative data associated with a time in a time period for which the viewing user has requested a historical newsfeed;
filtering the narrative data, the filtering comprising:
filtering out at least some narrative data that the user has viewed in the past; and
filtering out narrative data that the viewing user does not have permission to view;
selecting one or more items of the accessed narrative data based on one or more historical affinity scores, wherein each of the historical affinity scores comprises a historical measure of relevance of an item of the accessed narrative data to the viewing user, the relevance being for the time period for which the viewing user has requested the historical newsfeed;
generating one or more stories from the selected one or more items of accessed narrative data;
generating a ranking of the generated stories based on the one or more historical affinity scores;
selecting stories for display from the ranked generated stories based on the ranking; and
sending, to the client device for display to the viewing user, the historical newsfeed comprising displayable representations of the selected stories.
2. The method of claim 1 , further comprising a de-duplication step wherein duplicated narrative data is removed from the generated stories.
3. The method of claim 1 , further comprising a de-duplication step wherein generated stories containing duplicated narrative data are filtered out.
4. The method of claim 1 , wherein each generated story comprises story metadata and one or more references to narrative data, the story metadata comprising information that determines the look and behavior of a displayed story.
5. The method of claim 1 , further comprising a second filtering step wherein a privacy policy is enforced by filtering out the stories that the viewing user does not have permission to view.
6. The method of claim 1 , further comprising:
filtering the ranked generated stories, the filtering comprising:
positively biasing those of the generated stories with story types underrepresented at the top of the story ranking; and
negatively biasing those of the generated stories with story types that are overrepresented at the top of the story ranking; and
wherein the selecting stories for display from the ranked generated stories is further based on the filtering of the ranked generated stories.
7. A method comprising:
accessing narrative data related to a subject user of a social networking system, each item of narrative data associated with a time in a time period for which a historical newsfeed is being generated;
filtering the narrative data, the filtering comprising:
filtering out at least some narrative data that the user has viewed in the past; and
filtering out narrative data that the viewing user does not have permission to view;
selecting one or more items of the accessed narrative data based on one or more historical affinity scores, wherein each of the historical affinity scores a historical measure of relevance of an item of the accessed narrative data to the subject user, the relevance being for the time period for which the historical newsfeed is being generated;
generating one or more stories from the selected one or more items of accessed narrative data;
generating a ranking of the generated stories based on the one or more historical affinity scores;
selecting stories for display from the ranked generated stories based on the ranking; and
sending, to the client device for display to the viewing user, the historical newsfeed comprising displayable representations of the selected stories.
8. The method of claim 7 , further comprising a de-duplication step wherein duplicated narrative data is removed from the generated stories.
9. The method of claim 7 , further comprising a de-duplication step wherein generated stories containing duplicated narrative data are filtered out.
10. The method of claim 7 , wherein each generated story comprises story metadata and one or more references to narrative data, the story metadata comprising information that determines the look and behavior of a displayed story.
11. The method of claim 7 , further comprising a second filtering step wherein a privacy policy is enforced by filtering out the stories that the viewing user does not have permission to view.
12. The method of claim 7 , further comprising:
filtering the ranked generated stories, the filtering comprising:
positively biasing those of the generated stories with story types underrepresented at the top of the story ranking; and
negatively biasing those of the generated stories with story types that are overrepresented at the top of the story ranking; and
wherein the selecting stories for display from the ranked generated stories is further based on the filtering of the ranked generated stories.
13. A non-transitory computer-readable storage medium storing instructions, the instructions when executed by a processor in a social networking system, causes the processor to:
access narrative data related to a viewing user of a social networking system, each item of narrative data associated with a time in a time period for which the viewing user has requested a historical newsfeed;
filter the narrative data, the instructions to filter the narrative data including instructions that cause the processor to:
filter out at least some narrative data that the user has viewed in the past; and
filter out narrative data that the viewing user does not have permission to view;
select one or more items of the accessed narrative data based on one or more historical affinity scores, wherein each of the historical affinity scores comprises a historical measure of relevance of an item of the accessed narrative data to the viewing user, the relevance being for the time period for which the viewing user has requested the historical newsfeed;
generate one or more stories from the selected one or more items of accessed narrative data;
generate a ranking of the generated stories based on the one or more historical affinity scores;
filter the ranked generated stories, the filtering of the ranked generated stories comprising:
positively biasing those of the generated stories with story types underrepresented at the top of the story ranking; and
negatively biasing those of the generated stories with story types that are overrepresented at the top of the story ranking;
select stories for display from the ranked generated stories based on the ranking and filtering of the ranked generated stories; and
send, to the client device for display to the viewing user, the historical newsfeed comprising displayable representations of the selected stories.
14. The non-transitory computer-readable storage medium of claim 13 , further comprising instructions which when executed by the processor, cause the processor to perform a de-duplication step wherein duplicated narrative data is removed from the generated stories.
15. A non-transitory computer-readable storage medium storing instructions, the instructions when executed by a processor in a social networking system, causes the processor to:
access narrative data related to a subject user of a social networking system, each item of narrative data associated with a time in a time period for which a historical newsfeed is being generated;
filter the narrative data, the instructions to filter the narrative data including instructions that cause the processor to:
filter out at least some narrative data that the user has viewed in the past; and
filter out narrative data that the viewing user does not have permission to view;
select one or more items of the accessed narrative data based on one or more historical affinity scores, wherein each of the historical affinity scores a historical measure of relevance of an item of the accessed narrative data to the subject user, the relevance being for the time period for which the historical newsfeed is being generated;
generate one or more stories from the selected one or more items of accessed narrative data;
generate a ranking of the generated stories based on the one or more historical affinity scores;
select stories for display from the ranked generated stories based on the ranking; and
send, to the client device for display to the viewing user, the historical newsfeed comprising displayable representations of the selected stories.
16. The non-transitory computer-readable storage medium of claim 15 , further comprising instructions which when executed by the processor, cause the processor to perform a de-duplication step wherein duplicated narrative data is removed from the generated stories.
17. The non-transitory computer-readable storage medium of claim 15 , further comprising instructions which when executed by the processor, cause the processor to:
filter the ranked generated stories, the filtering comprising:
positively biasing those of the generated stories with story types underrepresented at the top of the story ranking; and
negatively biasing those of the generated stories with story types that are overrepresented at the top of the story ranking; and
wherein the selection of stories for display from the ranked generated stories is further based on the filtering of the ranked generated stories.