On May 7, 2015, the U.S. Patent & Trademark Office published a patent application from Apple that reveals a new kind of social network for lifestyle-based groups. While all of the technical aspects for this new lifestyle-based social groups network are presented, I think it may take a series of Apple videos to help us better understand why we'd want to use such a new social network in the future.

Apple's Patent Background

Today, one of the most popular media for learning about people is online social networks. On a social network website, people can post information about themselves. The information can include, for example, hobbies, pictures, links to favorite websites, and writings about places visited. This information can be harvested to understand a person's interests. However, this information may not be sufficient to determine a person's everyday lifestyle.

Typically, a person does not post information useful for determining the person's everyday lifestyle, e.g., the person's work, commute, or other daily routines. People generally do not believe that this information is of interest to an audience in a social network and, as a result, they don't blog about this information.

Apple Invents Lifestyle-Based Social Groups

Apple's invention generally relates to social networking and techniques for lifestyle-based social groups. A user device can learn movement patterns of the user device. Based on the movement pattern, and a user activity history, a computer system can determine a lifestyle of a user, or a meaning of a location.

The system can create a social group based on the lifestyle and the meaning of location. The system can designate the lifestyle or meaning as a theme of the social group. The social group can be an ad hoc social network. For example, the social group can be created without an explicit user request, can be anonymous, and can be lifestyle and location based.

The features described in this specification can be implemented to achieve one or more advantages. For example, a user device can learn a user's movement pattern, and provide assistance according to the movement pattern. The user device can provide the assistance based on the movement pattern without requiring additional user input. The user device can predict a user action, anticipating a location and a task at a given time. The user device can then provide the assistance ahead of the given time.

A system (e.g., a user device, a server, or both) implementing lifestyle-based social groups can help people socialize. The system can create ad hoc and anonymous social groups. The social groups can be based on similar activities and interests of members, even if the members do not post the activities and interests on a social networking website. The system can invite a user to join the social group as an anonymous member based on a location of the user and a movement pattern of the user.

Accordingly, a user of the system may have a better experience using services, especially location-based services, of system. For example, a user device can determine that a user usually goes to a place at 5:00 pm on weekdays. Based on various information (e.g., a business name corresponding to the location), the mobile device can determine that the place is a gymnasium. Accordingly, the mobile device can provide exercise related information to the user, or create an ad hoc "gym" social group for the user to join.

Apple's patent FIG. 1 shown below is a diagram illustrating exemplary techniques of creating an ad hoc social group based on similar lifestyles. Server #102 can be coupled to user devices #104, #106, and #108 by communications network #110. The server can include one or more computers programmed to receive device information from user devices (104, 106, and 108).

Each of user devices can be a mobile device (e.g., a laptop or tablet computer, a smart phone, or a wearable computing device) that can be carried by a person or a vehicle.

The device information can include location information and activity information. The location information can include time-based device locations. The activity information can include user activities, including, for example, search history, application launching history, or content playing history.

After determining a social group, a server can allow members of a social group to share information, post announcements, and communicate with one another. Compared to a conventional social group, where members typically post information of significant events (e.g., vacations, memorable experiences, or movies), the social group can be more utilitarian, relating to people's everyday life. Accordingly, a server can provide information that may be helpful in everyday life to the social group, for example, by posting traffic condition near a location during hours in which most people visit a location in social group.

According to Apple, user activity records can include a user's search history, content view history, website visit history, communication history, and application launching history.

For example, a server can determine that the anonymized user activity records in user activity information from at least one device of user devices include a user search on bicycle accessories, viewing cycling related videos, visiting sites selling the bicycle accessories, posting cycling announcements on a public cycling forum, or downloading and executing application programs for calculating calorie burning rate of cycling.

Apple's patent FIG. 3 noted below is a diagram illustrating exemplary techniques of managing ad hoc social groups based on different lifestyles. Location #302 can have multiple meanings and can be visited by people having different lifestyles.

For example, location #302 can be a shopping mall having various sections (e.g., a dining section and a grocery shopping section), or a city having various districts. Based on analysis of location information and user activity information from multiple user devices, a server (e.g., server 102 of FIG. 1) can create multiple ad hoc social groups associated with the location, each having a different theme corresponding to a meaning or a lifestyle.

In patent FIG. 4 noted below we see is a diagram illustrating exemplary techniques of managing ad hoc social groups based on movement patterns.

Upon determining the commonality, the server can determine ad hoc social group #410. The server can determine a theme of the social group based on the movement patterns, and designate the theme as "ride sharing" theme. The server can provide ride sharing (e.g., carpooling) information, including a bulletin board where a user can specify where and when the user wish to pick up passengers (or to be picked up) to travel from location #406 to location #408.

Apple's patent FIG. 6 noted below is a block diagram illustrating an exemplary structure of a social group analyzer configured to determine an ad hoc social group.

Social group analyzer #512 can include human movement analyzer #602. The human movement analyzer is a component of the social group analyzer configured to receive input data and determine, based on the input data, lifestyle #604. Lifestyle #604 can include one or more actions a user or a group of users perform, or one or more locations the user or the group of users visit, with regularity (e.g., daily, weekly, or monthly).

The social group analyzer can include activity analyzer #612. The activity analyzer is a component of social group analyzer #512 configured to receive user activity data and determine, based on the user activity data, lifestyle #614.

The user activity data can include application history #618, which can include a history of downloading applications and executing the applications. The user activity data can include online and offline purchase history #620, which can include online store visits, items purchased, and frequency of purchase. The user activity data can include download history #621, which can include history of content (e.g., digital images, music, and video) downloaded or streamed to a user device.

The social group analyzer can include semantic analyzer #622. The semantic analyzer is a component of social group analyzer #512 configured to receive input including lifestyles #604 and #614, and location attributions #624, and to determine output #626 that includes a meaning of a location or a lifestyle of a group of users associated with a location.

The location attributes can include data from a map database associating location features with geographic locations. The location features can include businesses (e.g., a bicycle shop), landmarks (e.g., a bike trail), or crowd-sourced point-of-interest locations (e.g., paragliding launch sites). The semantic analyzer can determine a meaning of a location or a lifestyle by cross-mapping location attributes #624, lifestyle #604 based on movement patterns, and lifestyle #614 based on user activities. A single location can be associated with multiple meanings or lifestyles.

There's a lot to explore in this patent application and you can review it all here.

Patent Credits

Apple credits Lucas Marti, Shannon Ma and Michael Dal Santo as the inventors of patent application 20150127728 which was originally filed in Q4 2013. Considering that this is a patent application, the timing of such a product to market is unknown at this time.

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