Ranking content items related to an event

1. A method of dynamic ranking and prioritizing content items over time, comprising:

registering a user vote in a simulated history of a user interaction score over time;

receiving a content item registered in a system, wherein the content item is associated with a seed event, wherein the seed event comprises a situation or a circumstance, and wherein the content item comprises a story, an image, or a video;

calculating a baseline topical relevance score of the content item to the seed event by contributing temporal and geographic proximity of times and locations mentioned in the content item, or attached as metadata to the content item, to times and locations associated with the seed event, wherein the topical relevance score employs a dynamic user rating score, and wherein the dynamic user rating score comprises calculating a user abuse score based on attempts to cram by the user, abusive behavior by the user, abusive language by the user, or any combination thereof;

calculating a user interaction score based on visits by the user, revisits by the user, or any combination thereof;

calculating a user reputation weight based on the user abuse score and the user interaction score;

calculating a user emotional score as a quantitative measure on sentiment, attitude, opinion, or any combination thereof of a piece of content;

matching the content item with existing events to form a group so that the content item is one of a plurality of content items associated with the same event, wherein the matching is based on a relevance score of the content item to the seed event, wherein the relevance score of the content is a dynamically scoring model of a weighted sum of normalized scoring contributions over time, and wherein the relevance score of each event in the group exceeds a predefined threshold value;

creating a new seed event in the event that no matching event is located and updating the user interaction score;

receiving from each of one or more users a user submitted input indicating an opinion of the user with respect to the content item; and

determining, using a processor, a ranking of the content item relative to one or more other content items in the plurality of content items associated with the same event of the group, wherein the ranking is based at least in part on the user submitted input, and wherein a degree to which the ranking of the content item is affected by the user submitted input is based—at least in part on how many users have submitted an input, and wherein the degree to which the ranking of the content item is affected by the user submitted input is based at least in part on the user reputation weight of the user that submitted the user submitted input; and

prioritizing the content item with respect to the plurality of the content items related to the event automatically using the ranking;

updating the user interaction score and recalculating user rating score, user reputation score, the content item score, and the emotional score based on a subsequent user interaction; and

reprioritizing the content items for each seed event based on a combination of the updated user interaction score and the recalculated scores.

2. The method as in claim 1 , wherein the degree to which the user submitted input affects the ranking of the content item is determined by a total user score, wherein the total user score comprises a sum of the user submitted inputs of however many users have submitted user inputs weighted by each user's reputation.

3. The method as in claim 1 , wherein the user reputation weight comprises a weighted sum of a long term user interaction history and a recent user interaction history.

4. The method as in claim 1 , wherein the content item relates to one or more of the following: an event, a location, an image, a video, a blog entry, or a face image.

5. A system for dynamic ranking and prioritizing content items over time, comprising:

a processor configured to:

register a user vote in a simulated history of a user interaction score over time;

receive a content item registered in a system, wherein the content item is associated with a seed event, wherein seed the event comprises a situation or a circumstance, and wherein the content item comprises a story, an image, or a video;

calculate a baseline topical relevance score of the content item to the seed event by contributing temporal and geographic proximity of times and locations mentioned in the content item, or attached as metadata to the content item, to times and locations associated with the seed event, wherein the topical relevance score employs a dynamic user rating score, and wherein the dynamic user rating score comprises calculate a user abuse score based on attempts to cram by the user, abusive behavior by the user, abusive language by the user, or any combination thereof;

calculate a user interaction score based on visits by the user, revisits by the user, or any combination thereof;

calculate a user reputation weight based on the user abuse score and the user interaction score;

calculating a user emotional score as a quantitative measure on sentiment, attitude, opinion, or any combination thereof of a piece of content;

match the content item with existing events to form a group so that the content item is one of a plurality of content items associated with the same event, wherein the matching is based on a relevance score of the content item to the seed event, wherein the relevance score of the content is a dynamically scoring model of a weighted sum of normalized scoring contributions over time, and wherein the relevance score of each event in the group exceeds a predefined threshold value;

create a new seed event in the event that no matching event is located and updating the user interaction score;

receive from each of one or more users a user submitted input indicating an opinion of the user with respect to the content item; and

determine a ranking of the content item relative to one or more other content items in the plurality of content items associated with the same event of the group, wherein the ranking is based on at least in part on the user submitted input, and wherein a degree to which the ranking of the content item is affected by the user submitted input is based—at least in part-on how many users have submitted an input, and wherein the degree to which the ranking of the content item is affected by the user submitted input is based at least in part on the user reputation weight of that submitted the user submitted input; and

prioritize the content item with respect to the plurality of the content items related to the event automatically using the ranking;

update the user interaction score and recalculate user rating score, user reputation score, the content item score, and the emotional score based on a subsequent user interaction; and

reprioritize the content items for each seed event based on a combination of the updated user interaction score and the recalculated scores; and

a memory coupled to the processor and configured to provide the processor with instructions.

6. A computer program product for dynamic ranking and prioritizing content items over time, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

registering a user vote in a simulated history of a user interaction score over time;

receiving a content item registered in a system, wherein the content item is associated with a seed event, wherein the seed event comprises a situation or a circumstance, and wherein the content item comprises a story, an image, or a video;

calculating a baseline topical relevance score of the content item to the seed event by contributing temporal and geographic proximity of times and locations mentioned in the content item, or attached as metadata to the content item, to times and locations associated with the seed event, wherein the topical relevance score employs a dynamic user rating score, and wherein the dynamic user rating score comprises calculating a user abuse score based on attempts to cram by the user, abusive behavior by the user, abusive language by the user, or any combination thereof;

calculating a user interaction score based on visits by the user, revisits by the user, or any combination thereof;

calculating a user reputation weight based on the user abuse score and the user interaction score;

calculating a user emotional score as a quantitative measure on sentiment, attitude, opinion, or any combination thereof of a piece of content;

matching the content item with existing events to form a group so that the content item is one of a plurality of content items associated with the same event, wherein the matching is based on a relevance score of the content item to the seed event, wherein the relevance score of the content is a dynamically scoring model of a weighted sum of normalized scoring contributions over time, and wherein the relevance score of each event in the group exceeds a predefined threshold value;

creating a new seed event in the event that no matching event is located and updating the user interaction score;

receiving from each of one or more users a user submitted input indicating an opinion of the user with respect to the content item; and

determining a ranking of the content item relative to one or more other content items in the plurality of content items associated with the same event of the group, wherein the ranking is based at least in part on the user submitted input, and wherein a degree to which the ranking of the content item is affected by the user submitted input is based at least in part on how many users have submitted an input, and wherein the degree to which the ranking of the content item is affected by the user submitted input is based at least in part on the user reputation weight of the user that submitted the user submitted input; and

prioritizing the content item with respect to the plurality of the content items related to the event automatically using the ranking;

updating the user interaction score and recalculating user rating score, user reputation score, the content item score, and the emotional score based on a subsequent user interaction; and

reprioritizing the content items for each seed event based on a combination of the updated user interaction score and the recalculated scores.

7. The system as in claim 5 , wherein the degree to which the user submitted input affects the ranking of the content item is determined by a total user score, wherein the total user score comprises a sum of the user submitted inputs of however many users have submitted user inputs weighted by each user's reputation.

8. The system as in claim 5 , wherein the user reputation weight comprises a weighted sum of a long term user interaction history and a recent user interaction history.

9. The system as in claim 5 , wherein the content item relates to one or more of the following: an event, a location, an image, a video, a blog entry, or a face image.