Cognitive monitoring of online user profiles to detect changes in online behavior
According to one or more embodiments of the present invention, a computer-implemented method includes creating a baseline online behavior profile of a user at a time t 1 based on a usage of a social network by the user. The method further includes continuously monitoring an online behavior profile of the user on the social network and in response to detecting a deviation between the online behavior profile and the baseline online behavior profile, creating a changed online behavior profile of the user at a time t 2 , t 2 >t 1 . The method further includes extracting keywords from a plurality of online posts associated with the user, the online posts being from time t 1 until time t 2 . The method further includes determining an event associated with the extracted keywords. The method further includes in response to the event being of a predetermined type, sending a notification to another user.
1. A computer-implemented method comprising:
creating a baseline online behavior profile of a user at a time t 1 based on a usage of a social network by the user;
continuously monitoring an online behavior profile of the user on the social network;
in response to detecting a deviation between the online behavior profile and the baseline online behavior profile, creating a changed online behavior profile of the user at a time t 2 , t 2 >t 1 ;
extracting keywords from a plurality of online posts associated with the user, the online posts being from time t 1 until time t 2 ;
determining an event associated with the extracted keywords;
determining a confidence level for the event as cause of the deviation between the online behavior profile and the baseline online behavior profile by comparing the event with a measurement of stress level of the user from one or more activity monitoring devices of the user, where the confidence level is based on the stress level being within a predetermined range that is associated with the event;
in response to the confidence level being below a predetermined threshold, corroborating an occurrence of the event that is determined by receiving a verification from a second user, wherein the second user verifies that the event occurred via an electronic confirmation; and
in response to the corroboration from the second user, and in response to the event being of a predetermined type, sending a notification to a designated caretaker of the user.
2. The computer-implemented method of claim 1 , wherein the event is detected by correlating the extracted keywords with a taxonomy repository of keywords and events.
3. The computer-implemented method of claim 2 , wherein the taxonomy repository is generated by analyzing a plurality of online posts.
4. The computer-implemented method of claim 1 , wherein the deviation between the online behavior profile and the baseline online behavior profile is detected based on a change in at least one data parameter from a plurality of data parameters from the online behavior profile.
5. The computer-implemented method of claim 4 , the online behavior profile comprising a sentiment analysis, and an average frequency of usage of the social network by the user.
6. The computer-implemented method of claim 1 , further comprising generating content specifically for the user based on the event.
7. A system comprising:
an online social network;
a memory; and
a processor configured to monitor the online social network for a change in online behavior of a user when using the online social network by performing a method comprising:
creating a baseline online behavior profile of a user at a time t 1 based on a usage of a social network by the user;
continuously monitoring an online behavior profile of the user on the social network;
in response to detecting a deviation between the online behavior profile and the baseline online behavior profile, creating a changed online behavior profile of the user at a time t 2 , t 2 >t 1 ;
extracting keywords from a plurality of online posts associated with the user, the online posts being from time t 1 until time t 2 ;
determining an event associated with the extracted keywords;
determining a confidence level for the event as cause of the deviation between the online behavior profile and the baseline online behavior profile by comparing the event with a measurement of stress level of the user from one or more activity monitoring devices of the user, where the confidence level is based on the stress level being within a predetermined range that is associated with the event;
in response to the confidence level being below a predetermined threshold, corroborating an occurrence of the event that is determined by receiving a verification from a second user, wherein the second user verifies that the event occurred via an electronic confirmation; and
in response to the corroboration from the second user, and in response to the event being of a predetermined type, sending a notification to a designated caretaker of the user.
8. The system of claim 7 , wherein the event is detected by correlating the extracted keywords with a taxonomy repository of keywords and events.
9. The system of claim 8 , wherein the taxonomy repository is generated by analyzing a plurality of online posts.
10. The system of claim 7 , wherein the deviation between the online behavior profile and the baseline online behavior profile is detected based on a change in at least one data parameter from a plurality of data parameters from the online behavior profile.
11. The system of claim 10 , the online behavior profile comprising a sentiment analysis, and an average frequency of usage of the social network by the user.
12. The system of claim 7 , wherein the method further comprises generating content specifically for the user based on the event.
13. A computer program product comprising a computer readable storage medium having stored thereon program instructions executable by one or more processing devices to perform a method comprising:
creating a baseline online behavior profile of a user at a time t 1 based on a usage of a social network by the user;
continuously monitoring an online behavior profile of the user on the social network;
in response to detecting a deviation between the online behavior profile and the baseline online behavior profile, creating a changed online behavior profile of the user at a time t 2 , t 2 >t 1 ;
extracting keywords from a plurality of online posts associated with the user, the online posts being from time t 1 until time t 2 ;
determining an event associated with the extracted keywords;
determining a confidence level for the event as cause of the deviation between the online behavior profile and the baseline online behavior profile by comparing the event with a measurement of stress level of the user from one or more activity monitoring devices of the user, where the confidence level is based on the stress level being within a predetermined range that is associated with the event;
in response to the confidence level being below a predetermined threshold, corroborating an occurrence of the event that is determined by receiving a verification from a second user, wherein the second user verifies that the event occurred via an electronic confirmation; and
in response to the corroboration from the second user, and in response to the event being of a predetermined type, sending a notification to a designated caretaker of the user.
14. The computer program product of claim 13 , wherein the event is detected by correlating the extracted keywords with a taxonomy repository of keywords and events, the taxonomy repository is generated by analyzing a plurality of online posts.
15. The computer program product of claim 13 , wherein the deviation between the online behavior profile and the baseline online behavior profile is detected based on a change in at least one data parameter from a plurality of data parameters from the online behavior profile.
16. The computer program product of claim 15 , the online behavior profile comprising a sentiment analysis, and an average frequency of usage of the social network by the user.
17. The computer program product of claim 13 , the method further comprising generating content specifically for the user based on the event.