Event mining in social networks
First Claim
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1. A method for detecting an event from a social stream, the method comprising the steps of:
- receiving a social stream from a social networks;
wherein said social stream comprises at least one object; and
wherein said object comprises a text, sender information of said text, and recipient information of said text;
clustering each object;
monitoring changes in at least one of said clusters; and
triggering an alarm when said changes in at least one of said clusters exceed a first threshold value;
assigning said object to an existing cluster if a similarity value between said object and said existing cluster is greater than a second threshold value;
creating a new cluster with said object if said similarity value between said object and said existing cluster is less than a second threshold value; and
replacing a stale cluster with said new cluster;
wherein said similarity value is determined by calculating a structural similarity value and a value selected from a group consisting of content-based similarity value, temporal similarity value and combinations thereof,wherein said structural similarity value is calculated by using structural components of said social network; and
wherein said structural components comprises nodes and node frequencies;
wherein at least one of the steps is carried out using a computer device.
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Abstract
A method and system for detecting an event from a social stream. The method includes the steps of: receiving a social stream from a social network, where the social stream includes at least one object and the object includes a text, sender information of the text, and recipient information of the text; assigning said object to a cluster based on a similarity value between the object and the clusters; monitoring changes in at least one of the clusters; and triggering an alarm when the changes in at least one of the clusters exceed a first threshold value, where at least one of the steps is carried out using a computer device.
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Citations
15 Claims
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1. A method for detecting an event from a social stream, the method comprising the steps of:
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receiving a social stream from a social networks; wherein said social stream comprises at least one object; and wherein said object comprises a text, sender information of said text, and recipient information of said text; clustering each object; monitoring changes in at least one of said clusters; and triggering an alarm when said changes in at least one of said clusters exceed a first threshold value; assigning said object to an existing cluster if a similarity value between said object and said existing cluster is greater than a second threshold value; creating a new cluster with said object if said similarity value between said object and said existing cluster is less than a second threshold value; and replacing a stale cluster with said new cluster; wherein said similarity value is determined by calculating a structural similarity value and a value selected from a group consisting of content-based similarity value, temporal similarity value and combinations thereof, wherein said structural similarity value is calculated by using structural components of said social network; and wherein said structural components comprises nodes and node frequencies; wherein at least one of the steps is carried out using a computer device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 15)
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8. A system for detecting an event from a social stream, the system comprising:
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a memory; a processor communicatively coupled to the memory, and a receiving module for receiving a social stream from a social network, communicatively coupled to the memory and the processor, wherein the receiving module is configured to perform the steps of a method comprising; wherein said social stream comprises at least one object; and wherein said object comprises a text, sender information of said text, and recipient information of said text; clustering each object; a monitoring module for monitoring changes in at least one of said clusters; and a trigger module for triggering an alarm when said changes in at least one of said clusters exceed a first threshold value; an existing cluster module for assigning said object to an existing cluster if a similarity value between said object and said existing cluster is greater than a second threshold value; a new cluster module for creating a new cluster with said object if said similarity value between said object and said existing cluster is less than a second threshold value; and a replacement module for replacing a stale cluster with said new cluster wherein said similarity value is determined by calculating a structural similarity value and a value selected from a group consisting of content-based similarity value, temporal similarity value and combinations thereof, wherein said structural similarity value is calculated by using structural components said social network; and wherein said structural components comprises nodes and node frequencies. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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Specification