Creation and use of closely-matched groups to aid in initiating and sustaining behavioral change

• US 9,514,495 B2
• Filed: 09/12/2013
• Issued: 12/06/2016
• Est. Priority Date: 09/12/2013
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Erickson, Thomas, Farrell, Robert G., Kellogg, Wendy A.
• Primary Examiner(s): Rostami, Mohammad S
• Application Number:
  US14/024,678
• Publication Number:
  US 20150074109A1
• Time in Patent Office: 1,181 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A method and system for sharing data between a plurality of users in an online group on a communications system includes receiving data from a plurality of users. The data includes personal characteristics about the users. The personal characteristics are analyzed to determine groups of personal characteristics. The users are clustered into closely matched groups based on the groups of personal characteristics. A plurality of activity information is generated about the users in each of the closely matched groups. The activity information may include a physical activity, a location, and a time of day. User may be allowed access to the activity information about other users in each of the closely matched groups, respectively.

Claims

1. A method for sharing data between a plurality of users in an online group on a communications system, comprising the steps of:

receiving data, using a computer, from a plurality of users communicating on a communications system, the data including personal characteristics about the users, the personal characteristics including one or more of;

an interest, an occupation, a marital status, an age, an education level, an experience area, and a goal;

segmenting the personal characteristics and generating aggregate personal characteristic data pertaining to targeted dispositions of users;

analyzing the personal characteristics to determine a plurality of groups of personal characteristics, using the computer;

recording availability of the users for communication and computing overlap of the availability for the users;

clustering the users into closely matched groups respective to the groups of personal characteristics, the users being clustered into a maximum number of the closely matched groups;

after the recording of availability of the users and the clustering of the users into closely matched groups, generating a plurality of activity information about each of the users in the closely matched groups, respectively, the activity information including one or more of;

a physical activity, a location, and a time of day;

next, allowing access to the users in each of the closely matched groups to the activity information about other users in each of the closely matched groups, respectively, using the computer;

recording behavior of the users toward respective goals and computing common characteristics for the users;

computing a social affinity for a group of users of the users based on the common characteristics and the overlap of availability of the users;

generating a projected success rate of a behavioral change for each of the closely matched groups and the users in the groups, respectively, based on an analysis of the activity information; and

generating a suggested activity change to achieve a behavioral change for a closely match group and the users of the closely matched group based on an analysis of the activity information.

2. The method of claim 1, wherein the users access the activity information using a user interface.

3. The method of claim 1, wherein the plurality of activity information includes a first type of information or a second type of information, or a combination of the first and second types of information, as selected by the user.

4. The method of claim 1, wherein the goals include one or more patterns of human activity, which includes:

a repeated physical activity.

5. The method of claim 1, wherein the data about the user is supplied by the user using an input device.

6. The method of claim 1, wherein the data about the user is from a sensor, the data including time and location stamps.

7. A computer program product for sharing data between a plurality of users in an online group on a communications system, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code being readable/executable by a processor to perform a method, comprising:

receiving data from a plurality of users communicating on a communications system, the data including personal characteristics about the users, the personal characteristics including one or more of;

an interest, an occupation, a marital status, an age, an education level, an experience area, and a goal;

segmenting the personal characteristics and generating aggregate personal characteristic data pertaining to targeted dispositions of users;

analyzing the personal characteristics to determine a plurality of groups of personal characteristics;

recording availability of the users for communication and computing overlap of the availability for the users;

clustering the users into closely matched groups respective to the groups of personal characteristics, the users being clustered into a maximum number of the closely matched groups;

after the recording of availability of the users and the clustering of the users into closely matched groups, generating a plurality of activity information about each of the users in the closely matched groups, respectively, the activity information including one or more of;

a physical activity, a location, and a time of day;

next, allowing access to the users in each of the closely matched groups to the activity information about other users in each of the closely matched groups, respectively,

recording behavior of the users toward respective goals and computing common characteristics for the users;

computing a social affinity for a group of users of the users based on the common characteristics and the overlap of availability of the users;

generating a projected success rate of a behavioral change for each of the closely matched groups and the users in the groups, respectively, based on an analysis of the activity information; and

generating a suggested activity change to achieve a behavioral change for a closely match group and the users of the closely matched group based on an analysis of the activity information.

8. The computer program product of claim 7, wherein the plurality of activity information includes a first type of information or a second type of information, or a combination of the first and second types of information, as selected by the user.

9. A system for sharing data between a plurality of users in an online group on a communications system, comprising:

a computer system comprising a computer processor, a computer-readable storage medium, and program instructions stored on the computer-readable storage medium for execution by the processor, the computer system comprising;

a communications module of the program instructions being configured to receive data from a plurality of users communicating on a communications system, the data including personal characteristics about the users, the personal characteristics including one or more of;

an interest, an occupation, a marital status, an age, an education level, an experience area, and a goal;

an analysis module of the program instructions of the computer system being configured to analyze the personal characteristics to determine a plurality of groups of personal characteristics, the computer system being configured to clusters the users into closely matched groups respective to the groups of personal characteristics, the users being clustered into a maximum number of the closely matched groups, the analysis module being configured to segment the personal characteristics and generate aggregate personal characteristic data pertaining to targeted dispositions of users, and record availability of the users for communication and compute overlap of the availability for the users;

after the recording of availability of the users and the clustering of the users into closely matched groups, the analysis module of the program instructions being configured to generate a plurality of activity information about each of the users in the closely matched groups, respectively, the activity information including one or more of;

a physical activity, a location, and a time of day; and

the communications module further being configured to allow access to the users in each of the closely matched groups to the activity information about other users in each of the closely matched groups, respectively, subsequent to generating of a plurality of activity information about each of the users in the closely matched groups;

the analysis module further being configured to;

record behavior of the users toward respective goals and compute common characteristics for the users;

compute a social affinity for a group of users of the users based on the common characteristics and the overlap of availability of the users;

the analysis module further being configured to generate a projected success rate of a behavioral change for each of the closely matched groups and the users in the groups, respectively, based on an analysis of the activity information; and

the analysis module further being configured to generate a suggested activity change to achieve a behavioral change for a closely match group and the users of the closely matched group based on an analysis of the activity information.