Estimating probability of spreading information by users on micro-weblogs

A method of predicting the spread of information, comprising:

• determining a current spread of information comprising source users who have shared a target document and edge users who have received the target document;
• for each edge user, determining a likelihood that the user will re-share the target document, by:
• extracting keywords from a historical set of documents addressed to the user;
• weighting the extracted keywords from the historical set of documents according a metric for the user's interest in the extracted keywords' respective source documents to create an interest model;
• and
• determining a likelihood that the user will re-share the target document using a processor, said likelihood being based on the interest model and the one or more keywords present in the new document;
• and
• projecting an estimated future information spread based on the determined likelihood for each user.

A system for estimating a probability of re-sharing information, comprising:

• a historical data table comprising a social graph map and a set of documents that each of a plurality of users have been exposed to;
• a keyword extraction module configured to extract keywords from a set of documents addressed to each user;
• an interest model generator configured to weight the extracted keywords according a metric for the user's interest in the keywords' respective source documents and to create an interest model from the weighted keywords;
• and
• a probability estimator comprising a processor configured to determine a likelihood that the user will re-share a new document, said likelihood being based on the interest model and one or more keywords present in the new document.