Systems and methods for ranking ephemeral content item collections associated with a social networking system

Systems, methods, and non-transitory computer readable media can perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection, each ephemeral content item collection of the plurality of ephemeral content item collections including one or more ephemeral content items. One or more ephemeral content item collections from the first ranking can be provided in an ephemeral content feed of the user. A selection by the user of an ephemeral content item collection provided in the ephemeral content feed can be received. A second ranking to rank each ephemeral content item collection of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection based on a probability of the user spending time on the ephemeral content item collection can be performed.

FIELD OF THE INVENTION

The present technology relates to the field of social networks. More particularly, the present technology relates to computer networking techniques for ranking content items associated with social networking systems.

BACKGROUND

Today, people often utilize computing devices (or systems) for a wide variety of purposes. Users can use their computing devices, for example, to interact with one another, create content, share content, and view content. In some cases, a user can utilize his or her computing device to access a social networking system (or service). The user can provide, post, share, and access various content items, such as status updates, images, videos, articles, and links, via the social networking system.

A social networking system may provide resources through which users may publish content items. In one example, a content item can be presented on a profile page of a user. As another example, a content item can be presented through a feed for a user.

SUMMARY

Various embodiments of the present disclosure can include systems, methods, and non-transitory computer readable media configured to obtain a plurality of ephemeral content item collections, wherein each ephemeral content item collection of the plurality of ephemeral content item collections includes one or more ephemeral content items. A score for each ephemeral content item collection of the plurality of ephemeral content item collections can be determined based on a probability of a user selecting the ephemeral content item collection and a probability of the user spending time on the ephemeral content item collection. The plurality of ephemeral content item collections can be ranked based on the respective scores of the plurality of ephemeral content item collections.

In some embodiments, each of one or more ephemeral content items included in an ephemeral content item collection of the plurality of ephemeral content item collections is accessible only for a predetermined time period.

In certain embodiments, an ephemeral content item collection of the plurality of ephemeral content item collections is accessible only when at least one of one or more ephemeral content items included in the ephemeral content item collection is accessible.

In an embodiment, one or more machine learning models can be trained based on features relating to one or more of: ephemeral content item collection attributes, ephemeral content item attributes, or user attributes, and the trained machine learning models can be applied to determine the score for each ephemeral content item collection of the plurality of ephemeral content item collections.

In some embodiments, the training the one or more machine learning models includes: training a first machine learning model to determine a score indicative of a probability of a particular user selecting an ephemeral content item collection; and training a second machine learning model to determine a score indicative of a probability of a particular user spending time on an ephemeral content item collection.

In certain embodiments, the score for each ephemeral content item collection of the plurality of ephemeral content item collections is determined as a product of a score for the ephemeral content item collection based on the first machine learning model and a score for the ephemera content item collection based on the second machine learning model.

In an embodiment, at least some of the ranked plurality of ephemeral content item collections can be provided in an ephemeral content feed of the user.

In some embodiments, the at least some of the ranked plurality of ephemeral content item collections include ephemeral content item collections having scores that satisfy a threshold value.

In certain embodiments, the at least some of the ranked plurality of ephemeral content item collections include a predetermined number of top ranked ephemeral content item collections.

In an embodiment, the probability of the user selecting the ephemeral content item collection and the probability of the user spending time on the ephemeral content item collection is determined as a product of the probability of the user selecting the ephemeral content item collection and an estimated amount of time the user is likely to spend on the ephemeral content item collection if the ephemeral content item collection is selected by the user.

Various embodiments of the present disclosure can include systems, methods, and non-transitory computer readable media configured to perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection, wherein each ephemeral content item collection of the plurality of ephemeral content item collections includes one or more ephemeral content items. One or more ephemeral content item collections from the first ranking to provide in an ephemeral content feed of the user can be selected. A second ranking to rank each ephemeral content item collection of the plurality of ephemeral content item collections other than the selected ephemeral content item collections from the first ranking based on a probability of the user spending time on the ephemeral content item collection can be performed. One or more ephemeral content item collections from the second ranking to provide in the ephemeral content feed of the user can be selected.

In some embodiments, the selected ephemeral content item collections from the first ranking and the selected ephemeral content item collections from the second ranking can be provided in the ephemeral content feed, wherein the selected ephemeral content item collections from the first ranking are provided based on an order of the first ranking and the selected ephemeral content item collections from the second ranking are provided based on an order of the second ranking.

In certain embodiments, the selected ephemeral content item collections from the first ranking are provided in the ephemeral content feed before the selected ephemeral content item collections from the second ranking.

In an embodiment, playback of one or more ephemeral content items of an ephemeral content item collection included in the ephemeral content feed can be initiated in response to user selection of the ephemeral content item collection, wherein playback of one or more ephemeral content items of the selected ephemeral content item collections from the first ranking and one or more ephemeral content items of the selected ephemeral content item collections from the second ranking in the immersive viewer is performed based on an order in which the selected ephemeral content item collections from the first ranking and the selected ephemeral content item collections from the second ranking are provided in the ephemeral content feed.

In some embodiments, the selected ephemeral content item collections from the first ranking are initially displayed in the ephemeral content feed, and the selected ephemeral content item collections from the second ranking in the ephemeral content feed are displayed in response to user navigation in the ephemeral content feed.

In certain embodiments, one or more machine learning models can be trained based on features relating to one or more of: ephemeral content item collection attributes, ephemeral content item attributes, or user attributes, and the trained machine learning models can be applied to determine one or more scores for an ephemeral content item collection.

In an embodiment, the training the one or more machine learning models includes: training a first machine learning model to determine a score indicative of a probability of a particular user selecting an ephemeral content item collection; and training a second machine learning model to determine a score indicative of a probability of a particular user spending time on an ephemeral content item collection.

In some embodiments, the first ranking is performed based on scores of the plurality of ephemeral content item collections as determined by the first machine learning model, and the second ranking is performed based on scores of the plurality of ephemeral content item collections other than the selected ephemeral content item collections from the first ranking as determined by the second machine learning model.

In certain embodiments, the selected ephemeral content item collections from the first ranking include one or more of: ephemeral content item collections from the first ranking having scores that satisfy a threshold value or a predetermined number of top ranked ephemeral content item collections from the first ranking.

In an embodiment, the selected ephemeral content item collections from the second ranking include one or more of: ephemeral content item collections from the second ranking having scores that satisfy a threshold value or a predetermined number of top ranked ephemeral content item collections from the second ranking.

Various embodiments of the present disclosure can include systems, methods, and non-transitory computer readable media configured to perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection, wherein each ephemeral content item collection of the plurality of ephemeral content item collections includes one or more ephemeral content items. One or more ephemeral content item collections from the first ranking can be provided in an ephemeral content feed of the user. A selection by the user of an ephemeral content item collection provided in the ephemeral content feed can be received. A second ranking to rank each ephemeral content item collection of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection based on a probability of the user spending time on the ephemeral content item collection can be performed.

In some embodiments, initiating playback of one or more ephemeral content items of the selected ephemeral content item collection in an immersive viewer in response to receiving the selection by the user.

In certain embodiments, playback in the immersive viewer of one or more ephemeral content items of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection is performed based on an order of the second ranking.

In an embodiment, the providing of the one or more ephemeral content item collections from the first ranking increases a likelihood of the user selecting the ephemeral content item collections provided in the ephemeral content feed, and the performing the playback of the one or more ephemeral content items of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection based on the order of the second ranking increases a likelihood of the user spending time on the ephemeral content item collections provided in the ephemeral content feed within the immersive viewer.

In some embodiments, one or more machine learning models can be trained based on features relating to one or more of: ephemeral content item collection attributes, ephemeral content item attributes, or user attributes, and the trained machine learning models can be applied to determine one or more scores for an ephemeral content item collection.

In certain embodiments, the training the one or more machine learning models includes: training a first machine learning model to determine a score indicative of a probability of a particular user selecting an ephemeral content item collection; and training a second machine learning model to determine a score indicative of a probability of a particular user spending time on an ephemeral content item collection.

In an embodiment, the first ranking is performed based on scores of the plurality of ephemeral content item collections as determined by the first machine learning model, and the second ranking is performed based on scores of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection as determined by the second machine learning model.

In some embodiments, the ephemeral content item collections provided from the first ranking include one or more of: ephemeral content item collections from the first ranking having scores that satisfy a threshold value or a predetermined number of top ranked ephemeral content item collections from the first ranking.

In certain embodiments, each of one or more ephemeral content items included in an ephemeral content item collection of the plurality of ephemeral content item collections is accessible only for a predetermined time period.

In an embodiment, an ephemeral content item collection of the plurality of ephemeral content item collections is accessible only when at least one of one or more ephemeral content items included in the ephemeral content item collection is accessible.

DETAILED DESCRIPTION

Ranking Ephemeral Content Item Collections Associated with a Social Networking System

People use computing devices (or systems) for a wide variety of purposes. Computing devices can provide different kinds of functionality. Users can utilize their computing devices to produce information, access information, and share information. In some cases, users can utilize computing devices to interact or engage with a conventional social networking system (e.g., a social networking service, a social network, etc.). A social networking system may provide resources through which users may publish content items. In one example, a content item can be presented on a profile page of a user. As another example, a content item can be presented through a feed for a user to access.

In some cases, content items available in a social networking system can be ephemeral. For example, a content item can only be accessible for a period of time and expire after the period of time. In some embodiments, ephemeral content items can be organized as or in an ephemeral content item collection. For example, an ephemeral content item collection associated with a user can include one or more ephemeral content items created by the user. Ephemeral content item collections may be provided via an ephemeral content feed of a user. Conventional approaches specifically arising in the realm of computer technology can rank ephemeral content item collections to be included in an ephemeral content feed of a user in chronological order or reverse chronological order. However, ranking ephemeral content item collections in chronological order or reverse chronological order may not result in presentation of ephemeral content item collections that include ephemeral content items the user is most likely to find interesting.

An improved approach rooted in computer technology can overcome the foregoing and other disadvantages associated with conventional approaches specifically arising in the realm of computer technology. Based on computer technology, the disclosed technology can rank ephemeral content item collections to include in an ephemeral content feed of a user in order to increase a likelihood of engagement by the user with ephemeral content item collections. The disclosed technology can rank the ephemeral content item collections in various ways. As an example, each ephemeral content item collection in a set of ephemeral content item collections can be ranked based on a probability of a user selecting the ephemeral content item collection and a probability of a user spending time on the ephemeral content item collection. As another example, each ephemeral content item collection in a set of ephemeral content item collections can be ranked initially based on a probability of a user selecting the ephemeral content item collection, and one or more top ranked ephemeral content item collections can be selected for inclusion in the user's ephemeral content feed. Each ephemeral content item collection in the set of ephemeral content item collections other than the selected ephemeral content item collections can be re-ranked based on a probability of the user spending time on the ephemeral content item collection, and one or more top ranked ephemeral content item collections can be included in the user's ephemeral content feed based on the ranking. As a further example, each ephemeral content item collection in a set of ephemeral content item collections can be ranked based on a probability of a user selecting the ephemeral content item collection, and one or more top ranked ephemeral content item collections can be selected for inclusion in the user's ephemeral content feed. When an ephemeral content item collection in the user's ephemeral content feed is selected by the user and viewed within an immersive viewer, each ephemeral content item collection of ephemeral content item collections in the user's ephemeral content feed other than the selected ephemeral content item collection can be re-ranked based on a probability of the user spending time on the ephemeral content item collection. The disclosed technology can rank ephemeral content item collections based on machine learning techniques. For example, one or more machine learning models can be trained to predict a likelihood of a user engaging with an ephemeral content item collection based on any one or more of the various ways of ranking described above. In this manner, the disclosed technology can rank and provide ephemeral content item collections that a user is most likely to find interesting. Additional details relating to the disclosed technology are provided below.

FIG. 1illustrates an example system100including an example ephemeral content ranking module102configured to rank ephemeral content associated with a content providing platform, such as a social networking system, according to an embodiment of the present disclosure. The ephemeral content ranking module102can include an ephemeral content item generation module104and an ephemeral content item collection ranking module106. In some instances, the example system100can include at least one data store120. The components (e.g., modules, elements, steps, blocks, etc.) shown in this figure and all figures herein are exemplary only, and other implementations may include additional, fewer, integrated, or different components. Some components may not be shown so as not to obscure relevant details. In various embodiments, one or more of the functionalities described in connection with the ephemeral content ranking module102can be implemented in any suitable combinations. While the disclosed technology is described in connection with ephemeral content associated with a social networking system for illustrative purposes, the disclosed technology can apply to any other type of system and/or content.

The ephemeral content provision module104can provide one or more ephemeral content items and/or ephemeral content item collections. Ephemeral content can refer to any type of content that is accessible only for a predetermined time period (e.g., second(s), minute(s), hour(s), day(s), etc.) or for a predetermined number of times (e.g., once, twice, etc.). For example, ephemeral content can expire after the predetermined time period passes or upon viewing by a user. In some instances, ephemeral content may be removed from servers and/or storage devices after expiration so that they are not accessible after their expiration. Examples of ephemeral content can include images, videos, audio, etc. As used herein, any content that is not ephemeral content can be referred to as non-ephemeral content. An ephemeral content item can refer to a content item that is ephemeral. One or more ephemeral content items created by users can be organized as or in ephemeral content item collections. An ephemeral content item collection can include one or more ephemeral content items and can be referred to as a “story.” In some embodiments, ephemeral content items of an ephemeral content item collection can be collectively referred to as a “reel.” For instance, ephemeral content items of an ephemeral content item collection can be considered to constitute a reel of the ephemeral content item collection. In some embodiments, an ephemeral content item collection may be associated with a particular user, and the ephemeral content item collection can include one or more ephemeral content items created by the particular user. An ephemeral content item collection associated with a particular user can be referred to as a “user-based ephemeral content item collection.” In other embodiments, an ephemeral content item collection may be associated with a subject matter or a topic, rather than a particular user, and the ephemeral content item collection can include one or more ephemeral content items from different users that relate to the topic. An ephemeral content item collection associated with a topic can be referred to as a “topic-based ephemeral content item collection.” Examples of a topic can include a geographical location, an event, a theme, etc.

The ephemeral content provision module104can provide ephemeral content item collections via an ephemeral content feed of a user. For example, an ephemeral content feed can be presented in a region of a user interface of a computing device running an application associated with the social networking system. A user who is associated with an ephemeral content item collection or creates an ephemeral content item included in an ephemeral content item collection can be referred to as an “authoring user.” A user who has access to an ephemeral content item collection and/or an ephemeral content item in an ephemeral content feed can be referred to as a “viewing user.” Various ephemeral content item collections can be provided in an ephemeral content feed of a viewing user. For example, the ephemeral content feed of the viewing user can include one or more user-based ephemeral content item collections, one or more topic-based ephemeral content item collections, and an ephemeral content item collection of the viewing user. The ephemeral content provision module104can provide ephemeral content item collections using various representations. For example, an ephemeral content item collection can be represented in a user interface by an avatar of a user, an icon, an image, an animation, a video, etc. Ephemeral content items of an ephemeral content item collection can be accessed by selecting a representation of the ephemeral content item collection. An ephemeral content item collection can appear or be accessible in an ephemeral content feed until all ephemeral content items included in the ephemeral content item collection expire. In some embodiments, an ephemeral content item collection can appear or be accessible in an ephemeral content feed for a predetermined time period (e.g., second(s), minute(s), hour(s), day(s), etc.). In some embodiments, the ephemeral content feed of the viewing user may display a predetermined number of ephemeral content item collections, and additional ephemeral content item collections can be displayed in response to navigation by the viewing user. For example, the viewing user can scroll through the ephemeral content feed.

A viewing user can engage with an ephemeral content item collection in the viewing user's ephemeral content feed by selecting the ephemeral content item collection. A viewing user can select an ephemeral content item collection in various manners, for example, by a click, a touch gesture, etc. Upon selection of an ephemeral content item collection by a viewing user, an immersive viewer can be provided in a user interface displaying the viewing user's ephemeral content feed, and the viewing user can view ephemeral content items of ephemeral content item collections. An immersive viewer can indicate any viewer and/or user interface for presenting a content item. For example, if a viewing user selects an ephemeral content item collection in the viewing user's ephemeral content feed, the immersive viewer can be launched and initiate playback of the selected ephemeral content item collection. One or more ephemeral content items of the selected ephemeral content item collection can be played back. If playback of the selected ephemeral content item collection ends, playback of another ephemeral content item collection can start. Playback of ephemeral content item collections within the immersive viewer can be performed based on an order or sequence of playback. The viewing user may transition within the immersive viewer between ephemeral content item collections and/or ephemeral content items displayed in the viewing user's ephemeral content feed. For example, the viewing user may skip or abandon an ephemeral content item collection and/or an ephemeral content item before playback of the ephemeral content item collection and/or the ephemeral content item ends. All examples herein are provided for illustrative purposes, and there can be many variations and other possibilities.

The ephemeral content item collection ranking module106can rank ephemeral content item collections based on various techniques. The ephemeral content item collection ranking module106can rank ephemeral content item collections based on one or more machine learning models. The ephemeral content item collection ranking module106is described in more detail herein.

In some embodiments, the ephemeral content ranking module102can be implemented, in part or in whole, as software, hardware, or any combination thereof. In general, a module as discussed herein can be associated with software, hardware, or any combination thereof. In some implementations, one or more functions, tasks, and/or operations of modules can be carried out or performed by software routines, software processes, hardware, and/or any combination thereof. In some cases, the ephemeral content ranking module102can be, in part or in whole, implemented as software running on one or more computing devices or systems, such as on a server system or a client computing device. In some instances, the ephemeral content ranking module102can be, in part or in whole, implemented within or configured to operate in conjunction or be integrated with a social networking system (or service), such as a social networking system630ofFIG. 6. Likewise, in some instances, the ephemeral content ranking module102can be, in part or in whole, implemented within or configured to operate in conjunction or be integrated with a client computing device, such as the user device610ofFIG. 6. For example, the ephemeral content ranking module102can be implemented as or within a dedicated application (e.g., app), a program, or an applet running on a user computing device or client computing system. The application incorporating or implementing instructions for performing functionality of the ephemeral content ranking module102can be created by a developer. The application can be provided to or maintained in a repository. In some cases, the application can be uploaded or otherwise transmitted over a network (e.g., Internet) to the repository. For example, a computing system (e.g., server) associated with or under control of the developer of the application can provide or transmit the application to the repository. The repository can include, for example, an “app” store in which the application can be maintained for access or download by a user. In response to a command by the user to download the application, the application can be provided or otherwise transmitted over a network from the repository to a computing device associated with the user. For example, a computing system (e.g., server) associated with or under control of an administrator of the repository can cause or permit the application to be transmitted to the computing device of the user so that the user can install and run the application. The developer of the application and the administrator of the repository can be different entities in some cases, but can be the same entity in other cases. It should be understood that many variations are possible.

The data store120can be configured to store and maintain various types of data, such as the data relating to support of and operation of the ephemeral content ranking module102. The data maintained by the data store120can include, for example, information relating to ephemeral content, ephemeral content feeds, ephemeral content item collections, ephemeral content items, machine learning models, ranking data, etc. The data store120also can maintain other information associated with a social networking system. The information associated with the social networking system can include data about users, social connections, social interactions, locations, geo-fenced areas, maps, places, events, groups, posts, communications, content, account settings, privacy settings, and a social graph. The social graph can reflect all entities of the social networking system and their interactions. As shown in the example system100, the ephemeral content ranking module102can be configured to communicate and/or operate with the data store120. In some embodiments, the data store120can be a data store within a client computing device. In some embodiments, the data store120can be a data store of a server system in communication with the client computing device.

FIG. 2illustrates an example ephemeral content item collection ranking module202configured to rank ephemeral content item collections associated with a social networking system, according to an embodiment of the present disclosure. In some embodiments, the ephemeral content item collection ranking module106ofFIG. 1can be implemented with the example ephemeral content item collection ranking module202. As shown in the example ofFIG. 2, the example ephemeral content item collection ranking module202can include a ranking method determination module204, a machine learning training module206, and a machine learning evaluation module208.

The ephemeral content item collection ranking module202can rank ephemeral content item collections that are candidates for inclusion in a viewing user's ephemeral content feed. For example, the ephemeral content item collection ranking module202can rank ephemeral content item collections to predict a likelihood of a viewing user engaging with ephemeral content item collections. A score can be determined for each ephemeral content item collection, and the score can be indicative of a likelihood of a viewing user engaging with the ephemeral content item collection. The ephemeral content item collection ranking module202can rank ephemeral content item collections based on respective scores. The ephemeral content item collection ranking module202can rank different types of ephemeral content item collections, such as user-based ephemeral content item collections and topic-based ephemeral content item collections. One or more ranked ephemeral content item collections can be provided in an ephemeral content feed based on an order of ranking.

The ranking method determination module204can determine a ranking method for ranking ephemeral content item collections. Ephemeral content item collections to include in a viewing user's ephemeral content feed can be ranked in various ways. The ranking method selection module204can select a ranking method as appropriate. In some cases, a ranking method can be defined or determined such that a likelihood of a viewing user selecting an ephemeral content item collection is maximized in an ephemeral content feed. For example, the viewing user can select an ephemeral content item collection presented in the ephemeral content feed in various manners, for example, by a click, a touch gesture, etc. In other cases, a ranking method can be defined or determined such that a likelihood of a viewing user spending time on an ephemeral content item collection is maximized in an immersive viewer or such that a selected or predetermined amount of time spent by a viewing user on an ephemeral content item collection is maximized in an immersive viewer. For example, the viewing user can spend time on the ephemeral content item collection by viewing one or more ephemeral content items of the ephemeral content item collection in the immersive viewer. As such, the likelihood of the viewing user spending time on the ephemeral content item collection can be considered to be a likelihood of the viewing user spending time on one or more ephemeral content items of the ephemeral content item collection within the immersive viewer. Similarly, the selected or predetermined amount of time spent by the viewing user on the ephemeral content item collection can be considered to be a selected or predetermined amount of time spent by the viewing user on one or more ephemeral content items of the ephemeral content item collection within the immersive viewer. For example, playback of one or more ephemeral content items of an ephemeral content item collection can begin in the immersive viewer when the viewing user selects the ephemeral content item collection in the ephemeral content feed or when the ephemeral content item collection is to be played back based on an order of playback within the immersive viewer. In some instances, the viewing user may select an ephemeral content item collection, but may not spend much time viewing ephemeral content items of the ephemeral content item collection. For example, the viewing user may skip one or more ephemeral content items and/or ephemeral content item collections or exit the immersive viewer. In certain cases, a ranking method can be defined or determined such that a likelihood of a viewing user selecting an ephemeral content item collection is maximized in an ephemeral content feed and such that a likelihood of a viewing user spending time, or a selected or predetermined amount of time spent by a viewing user, on an ephemeral content item collection is maximized in an immersive viewer.

In some embodiments, according to a first ranking method, each ephemeral content item collection in a set of ephemeral content item collections can be ranked based on a probability of a viewing user selecting the ephemeral content item collection and a probability of the viewing user spending time on the ephemeral content item collection. For example, a score of an ephemeral content item collection can be determined as follows:
score=P(select)*P(time)  (1),
where score indicates a score assigned to an ephemeral content item collection, P(select) indicates a probability of a viewing user selecting the ephemeral content item collection, and P(time) indicates a probability of the viewing user spending time on the ephemeral content item collection once the ephemeral content item collection is selected. In some embodiments, P(time) can be described in terms of an estimated amount of time the viewing user is likely to spend on the ephemeral content item collection. For instance, P(time) can be specified in a unit of time, such as second(s), minute(s), hour(s), etc. In certain embodiments, P(select)*P(time) can be determined as an estimated amount of time a viewing user is likely to spend on an ephemeral content item collection. For instance, a score of an ephemeral content item collection can be determined as follows:
score=E(time)=P(select)*E(time|select)  (1a),
where score indicates a score assigned to an ephemeral content item collection, E(time) indicates an estimated amount of time a viewing user is likely to spend on the ephemeral content item collection, P(select) indicates a probability of the viewing user selecting the ephemeral content item collection, and E(time|select) indicates an estimated amount of time the viewing user is likely to spend on the ephemeral content item collection given that the ephemeral content item collection is selected. In some embodiments, E(time|select) can be a sum or an average of an estimated amount of time the viewing user is likely to spend on each ephemeral content item in the ephemeral content item collection. An estimated amount of time can be specified in an appropriate unit of time, such as second(s), minute(s), hour(s), etc. One or more ephemeral content item collections ranked according to equation (1) or (1a) can be provided in the viewing user's ephemeral content feed based on the order of the ranking. For instance, ephemeral content item collections having scores that satisfy a threshold value can be included in the viewing user's ephemeral content feed. In other instances, a predetermined number of top ranked ephemeral content item collections can be included in the viewing user's ephemeral content feed. If the viewing user selects an ephemeral content item collection in the ephemeral content feed, an immersive viewer can be provided, and playback of ephemeral content items of ephemeral content item collections can be performed based on the order in which the ephemeral content item collections are provided in the ephemeral content feed, starting with ephemeral content items of the selected ephemeral content item collection. Scores of ephemeral content item collections according to equations (1) and (1a) can be determined based on machine learning models. For example, one or more machine learning models can be trained to determine the scores, as described below.

In other embodiments, according to a second ranking method, each ephemeral content item collection in a set of ephemeral content item collections can be ranked initially based on a probability of a viewing user selecting the ephemeral content item collection. One or more ephemeral content item collections from the initial ranking can be selected for inclusion in the ephemeral content feed based on the ranking. Ephemeral content item collections selected based on the initial ranking can be referred to as “initial ranking selected ephemeral content item collections.” Then, each ephemeral content item collection in the set of ephemeral content item collections that is not selected for inclusion in the ephemeral content feed from the initial ranking can be re-ranked based on a probability of the viewing user spending time on the ephemeral content item collection. One or more ephemeral content item collections from the re-ranking can be selected for inclusion in the ephemeral content feed based on the ranking. Ephemeral content item collections selected based on the re-ranking can be referred to as “re-ranking selected ephemeral content item collections.” Initial ranking selected ephemeral content item collections can be provided in the ephemeral content feed before re-ranking selected ephemeral content item collections. For example, the order of the initially selected ephemeral content item collections in the ephemeral content feed can be prioritized over or appear before the re-ranking selected ephemeral content item collections. In some cases, the initial ranking selected ephemeral content item collections can be displayed in the ephemeral content feed when the viewing user accesses the ephemeral content feed, and the re-ranking selected ephemeral content item collections can be displayed in the ephemeral content feed when the viewing user navigates through or scrolls the ephemeral content feed to access additional ephemeral content item collections.

In these embodiments, according to the second ranking method, a score of an ephemeral content item collection can be determined initially as follows:
score=P(select)  (2a),
where score indicates a score assigned to an ephemeral content item collection and P(select) indicates a probability of a viewing user selecting the ephemeral content item collection. One or more ephemeral content item collections ranked according to equation (2a) can be selected for inclusion in the viewing user's ephemeral content feed and provided based on the order of the ranking. For instance, ephemeral content item collections having scores that satisfy a threshold value can be selected, or a predetermined number of top ranked ephemeral content item collections can be selected. Subsequently, ephemeral content item collections, excluding ephemeral content item collections selected based on ranking according to equation (2a), can be re-ranked. For example, a score of an ephemeral content item collection can be determined as follows:
score=P(time)  (2b),
where score indicates a score assigned to an ephemeral content item collection and P(time) indicates a probability of a viewing user spending time on the ephemeral content item collection. For example, P(time) can be determined based on ephemeral content items included in the ephemeral content item collection. In some embodiments, P(time) can be described in terms of an estimated amount of time the viewing user is likely to spend on the ephemeral content item collection. For instance, P(time) can be specified in a unit of time, such as second(s), minute(s), hour(s), etc. One or more ephemeral content item collections ranked according to equation (2b) can be selected for inclusion in the viewing user's ephemeral content feed and provided based on the order of the ranking. For instance, ephemeral content item collections having scores that satisfy a threshold value can be selected, or a predetermined number of top ranked ephemeral content item collections can be selected. If the viewing user selects an ephemeral content item collection in the ephemeral content feed, an immersive viewer can be provided, and playback of ephemeral content items of ephemeral content item collections can be performed based on the order in which the ephemeral content item collections are provided in the ephemeral content feed, starting with ephemeral content items of the selected ephemeral content item collection. In these embodiments, ephemeral content item collections selected based on equation (2a) can appear first in the viewing user's ephemeral content feed and ephemeral content item collections selected based on equation (2b) can appear subsequent to the ephemeral content item collections selected based on equation (2a). In this way, ephemeral content item collections that the viewing user is likely to select can be displayed more prominently in the ephemeral content feed, which can increase a likelihood of the viewing user selecting an ephemeral content item collection and viewing ephemeral content items of ephemeral content item collections in an immersive viewer. Within the immersive viewer, after playback of ephemeral content items of the ephemeral content item collections that the viewing user is likely to select, ephemeral content items of ephemeral content item collections that the viewing user is likely to spend time on can be played back, for example, automatically, which can lead to the viewing user spending more time on ephemeral content item collections within the immersive viewer. Scores of ephemeral content item collections according to equations (2a) and (2b) can be determined based on machine learning models. For example, one or more machine learning models can be trained to determine the scores, as described below.

In certain embodiments, according to third a ranking method, each ephemeral content item collection in a set of ephemeral content item collections can be ranked based on a probability of a viewing user selecting the ephemeral content item collection, and one or more ranked ephemeral content item collections can be included in the viewing user's ephemeral content feed based on the ranking. When the viewing user selects an ephemeral content item collection in the ephemeral content feed, an immersive viewer is provided to initiate playback of the selected ephemeral content item collection. In order to determine an order of playback of the ephemeral content item collections within the immersive viewer, each ephemeral content item collection of ephemeral content item collections included in the ephemeral content feed can be re-ranked based on a probability of the viewing user spending time on the ephemeral content item collection. For example, remaining ephemeral content item collections other than the selected ephemeral content item collection can be re-ranked, and playback of the remaining ephemeral content item collections can be performed based on the order of the re-ranking. When the viewing user is viewing ephemeral content items of the selected ephemeral content item collection in the immersive viewer, the viewing user may not necessarily expect the order of playback of ephemeral content item collections in the immersive viewer to be the same as the order in which the ephemeral content item collections are displayed in the ephemeral content feed. Accordingly, for playback in the immersive viewer, each ephemeral content item collection of the remaining ephemeral content item collections can be re-ranked based on a probability of the viewing user spending time on the ephemeral content item collection. The order in which the ephemeral content item collections are displayed in the ephemeral content feed can stay the same even though the remaining ephemeral content item collections are re-ranked for playback in the immersive viewer.

In these embodiments, according to the third ranking method, a score of an ephemeral content item collection can be determined as follows:
score=P(select)  (3a),
where score indicates a score assigned to an ephemeral content item collection and P(select) indicates a probability of a viewing user selecting the ephemeral content item collection. Equation (3a) is the same as equation (2a) above. One or more ephemeral content item collections ranked according to equation (3a) can be provided in the viewing user's ephemeral content feed based on the order of the ranking. For instance, ephemeral content item collections having scores that satisfy a threshold value can be included in the viewing user's ephemeral content feed. In other instances, a predetermined number of top ranked ephemeral content item collections can be included in the viewing user's ephemeral content feed. Once the viewing user selects an ephemeral content item collection in the ephemeral content feed and the immersive viewer is launched to initiate playback of the selected ephemeral content item collection, scores of remaining ephemeral content item collections included in the ephemeral content feed other than the selected ephemeral content item collection can be determined as follows:
score=P(time)  (3b),
where score indicates a score assigned to an ephemeral content item collection and P(time) indicates a probability of a viewing user spending time on the ephemeral content item collection. For example, P(time) can be determined based on ephemeral content items included in the ephemeral content item collection. In some embodiments, P(time) can be described in terms of an estimated amount of time the viewing user is likely to spend on the ephemeral content item collection. For instance, P(time) can be specified in a unit of time, such as second(s), minute(s), hour(s), etc. Equation (3b) is the same as equation (2b) above. The remaining ephemeral content item collections can be ranked based on respective scores as determined based on equation (3b). Within the immersive viewer, playback of the remaining ephemeral content item collections can be performed according to the ranking based on equation (3b). For example, when playback of the selected ephemeral content item collection ends, playback of a subsequent ephemeral content item collection according to the ranking based on equation (3b) can start. In some embodiments, since ephemeral content items of an ephemeral content item collection can be considered to be a reel of the ephemeral content item collection, as mentioned above, re-ranking of ephemeral content item collections to determine order of playback can be considered to be re-ranking of reels of ephemeral content item collections. In this way, in the ephemeral content feed, a likelihood of the viewing user selecting an ephemeral content item collection can be increased, and in the immersive viewer, a likelihood of the viewing user spending time on ephemeral content item collections can be increased. In certain embodiments, ephemeral content items of ephemeral content item collections can also be ranked based on a probability of the viewing user spending time on the ephemeral content items in order to determine an order for playback. Scores of ephemeral content item collections according to equations (3a) and (3b) can be determined based on machine learning models. For example, one or more machine learning models can be trained to determine the scores, as described below. Many variations are possible.

The machine learning training module206can train a machine learning model to rank ephemeral content item collections for a viewing user's ephemeral content feed. For instance, the machine learning training module206can train one or more machine learning models to determine scores of ephemeral content item collections based on equations (1), (1a), (2a), (2b), (3a), and/or (3b) above. The machine learning training module206can train a separate machine learning model for each equation or each component of an equation, such as P(select), P(time), E(time), and/or E(time|select).

The machine learning training module206can train a machine learning model to rank ephemeral content item collections based on various types of training data. The training data can include various features. For example, features can relate to ephemeral content item collection attributes, ephemeral content item attributes, user attributes, etc. Ephemeral content item collection attributes can include any attributes associated with ephemeral content item collections. Examples of ephemeral content item collection attributes can include an authoring user of an ephemeral content item collection and/or an ephemeral content item, one or more ephemeral content items included in an ephemeral content item collection, a number of ephemeral content items included in an ephemeral content item collection, one or more viewing users of an ephemeral content item collection and/or an ephemeral content item, a rate of selection of an ephemeral content item collection by viewing users, a selection of an ephemeral content item collection by a specific viewing user, a rate of selection of an ephemeral content item by viewing users, a selection of an ephemeral content item by a specific viewing user, historical information associated with an ephemeral content item collection, visual characteristics of a representation of an ephemeral content item collection, whether an ephemeral content item collection includes a live ephemeral content item, whether an ephemeral content item collection includes an expiring ephemeral content item, etc. Historical information associated with an ephemeral content item collection can include whether a viewing user has selected an ephemeral content item collection of a particular authoring user at one or more previous times when the ephemeral content item collection of the authoring user was included in the viewing user's ephemeral content feed, a ranking or position of an ephemeral content item collection of a particular authoring user at one or more previous times when the ephemeral content item collection was included in the viewing user's ephemeral content feed, etc. Visual characteristics of a representation of an ephemeral content item collection can include a color, one or more objects included in the representation, a subject matter or topic included in the representation, etc.

Ephemeral content item attributes can include any attributes associated with ephemeral content items. Examples of ephemeral content item attributes can include content attributes, such as a type of media (e.g., an image, a video, an audio, text, etc.), a length of content, a subject matter or topic, one or more objects represented in content, a popularity of content (e.g., many users interacting with content), etc. Examples ephemeral content item attributes can also include whether viewing users spent time on an ephemeral content item, an amount of time viewing users spent on an ephemeral content item, whether viewing users spent a threshold amount of time on an ephemeral content item, etc.

User attributes can include any attributes associated with users. User attributes can include attributes associated with authoring users and attributes associated with viewing users. Examples of user attributes can include a location (e.g., a country, state, county, city, etc.), an age, an age range, a gender, a language, a number of connections (e.g., friends or followers), an interest (e.g., topics in which a user has expressed interest), a computing device, an operating system (OS), etc. User attributes can also include attributes associated with connections between authoring users and viewing users. For example, a user can be a connection of another user (e.g., a friend or a follower), and a coefficient or weight can be associated with the connection. The coefficient can be indicative of a strength of the connection. In some embodiments, a connection between two users is two-way such that when the connection is established between a first user and a second user, the two users are connections of each other. In other embodiments, a connection between two users can be one-way such that a first user is a connection of a second user, but the second user is not a connection of the first user. In these embodiments, users can be subscribers or followers of other users. User attributes can further include attributes associated with interactions between authoring users and viewing users. Examples of interactions between authoring users and viewing users can include whether a viewing user liked a content item in an authoring user's feed or profile, whether a viewing user sent a direct message to an authoring user, etc. Many variations are possible.

The training data can include various labels. The labels can include labels indicating whether viewing users selected ephemeral content item collections, labels indicating whether viewing users spent time on ephemeral content item collections and/or ephemeral content items, labels indicating an amount of time viewing users spent on ephemeral content item collections and/or ephemeral content items, and/or labels indicating whether viewing users spent a threshold amount of time on ephemeral content item collections and/or ephemeral content items.

The machine learning training module206can determine weights associated with various features used to train a machine learning model based on, for example, regression techniques. In some embodiments, the machine learning model can be a neural network. The machine learning training module206can determine which features are most successful in predicting engagement with ephemeral content item collections by viewing users. Features for training the machine learning model can vary for different types of ephemeral content item collections, such as user-based ephemeral content item collections and topic-based ephemeral content item collections. For example, attributes associated with interactions between authoring users and viewing users may not be as important to topic-based ephemeral content item collections, compared to user-based ephemeral content item collections, since authoring users and viewing users of topic-based ephemeral content item collections generally are not connections of each other.

The machine learning evaluation module208can apply the trained machine learning model to rank ephemeral content item collections for a viewing user's ephemeral content feed. For example, the trained machine learning model can be applied to feature data relating to an ephemeral content item collection, one or more ephemeral content items of the ephemeral content item collection, and a viewing user to determine a score for the ephemeral content item collection. For example, the score can be based on any of the equations described above, such as equations (1), (1a), (2a), (2b), (3a), and/or (3b). Ephemeral content item collections can be ordered according to their respective scores. In some embodiments, the machine learning evaluation module208can rank ephemeral content item collections for a viewing user's ephemeral content feed each time the ephemeral content feed is refreshed. In these embodiments, ephemeral content item collections and/or ordering of ephemeral content item collections displayed to the viewing user may change each time. One or more machine learning models discussed in connection with the ephemeral content ranking module102and its components can be implemented separately or in combination, for example, as a single machine learning model, as multiple machine learning models, as one or more staged machine learning models, as one or more combined machine learning models, etc. All examples herein are provided for illustrative purposes, and there can be many variations and other possibilities.

FIG. 3illustrates an example scenario300for providing ranked ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. The example scenario300illustrates a computing device302displaying a user interface304associated with a social networking system. The user interface304includes an ephemeral content feed306of a user, which includes one or more user-based ephemeral content item collections310. In the example scenario300, the user can be a viewing user, and user-based ephemeral content item collections can be ranked as candidates for inclusion in the user's ephemeral content feed306. The ranking of ephemeral content item collections can be performed by the ephemeral content ranking module102, as discussed herein. The user's ephemeral content feed306can include the user's own user-based ephemeral content item collection310aand a predetermined number of top ranked user-based ephemeral content item collections310b,310c,310d. The example scenario300illustrates user-based ephemeral content item collections310a,310b,310c, and310din the user's ephemeral content feed306. The user's ephemeral content feed306can be scrolled right in order to show more user-based ephemeral content item collections. In some embodiments, the user's ephemeral content feed306can also include one or more topic-based ephemeral content item collections. The user interface304also includes a feed308of the user, which can include non-ephemeral content items. All examples herein are provided for illustrative purposes, and there can be many variations and other possibilities.

FIG. 4Aillustrates an example scenario400for ranking ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. The example scenario400shows an ephemeral content feed405of a viewing user that includes ephemeral content item collections410a-d. The ephemeral content feed405can be the same as or similar to the ephemeral content feed306inFIG. 3. Ephemeral content item collections can be ranked by the ephemeral content ranking module102, as described above. In the example scenario400, each ephemeral content item collection in a set of ephemeral content item collections is ranked based on a probability of a viewing user selecting the ephemeral content item collection, P(select), and a probability of the viewing user spending time on the ephemeral content item collection, P(time). For example, each ephemeral content item collection in the set of ephemeral content item collections can be ranked based on equation (1). The ephemeral content item collections410a-dcan represent ephemeral content item collections that are selected for inclusion in the ephemeral content feed405based on P(select)*P(time). In some embodiments, as mentioned above, P(select)*P(time) can be considered in terms of E(time), which is equal to P(select)*E(time|select). In these embodiments, each ephemeral content item collection in the set of ephemeral content item collections can be ranked based on equation (1 a). In these embodiments, the ephemeral content item collections410a-dcan represent ephemeral content item collections that are selected for inclusion in the ephemeral content feed405based on P(select)*E(time|select). All examples herein are provided for illustrative purposes, and there can be many variations and other possibilities.

FIG. 4Billustrates an example scenario420for ranking ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. The example scenario420shows an ephemeral content feed425of a viewing user that includes ephemeral content item collections430a-h. The ephemeral content feed425can be the same as or similar to the ephemeral content feed306inFIG. 3. Ephemeral content item collections can be ranked by the ephemeral content ranking module102, as described above. In the example scenario420, each ephemeral content item collection in a set of ephemeral content item collections is ranked initially based on a probability of a viewing user selecting the ephemeral content item collection, P(select). For example, each ephemeral content item collection in the set of ephemeral content item collections can be ranked based on equation (2a). Ephemeral content item collections430a-dare selected for inclusion in the ephemeral content feed425from the initial ranking. Each ephemeral content item collection in the set of ephemeral content item collections other than the ephemeral content item collections430a-dis then re-ranked based on a probability of the viewing user spending time on the ephemeral content item collection, P(time). For example, each ephemeral content item collection in the set of ephemeral content item collections other than the ephemeral content item collections430a-dcan be ranked based on equation (2b). Ephemeral content item collections430e-hare selected for inclusion in the ephemeral content feed425based on the re-ranking. In some embodiments, the ephemeral content item collections430e-hare not initially displayed in the ephemeral content feed425, but can be displayed when the viewing user navigates through the ephemeral content feed425to access additional ephemeral content item collections, for example, by scrolling. In the example ofFIG. 4B, a portion of the ephemeral content feed425that is not currently displayed is shown in dashed lines, and ephemeral content item collections included in this portion (e.g., the ephemeral content item collections430e-h) are also shown in dashed lines. All examples herein are provided for illustrative purposes, and there can be many variations and other possibilities.

FIG. 4Cillustrates an example scenario440for ranking ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. The example scenario440shows an ephemeral content feed445of a viewing user that includes ephemeral content item collections450a-d. The ephemeral content feed445can be the same as or similar to the ephemeral content feed306inFIG. 3. Ephemeral content item collections can be ranked by the ephemeral content ranking module102, as described above. In the example scenario440, each ephemeral content item collection in a set of ephemeral content item collections are ranked initially, for example, at time T0, based on a probability of a viewing user selecting the ephemeral content item collection, P(select). For example, each ephemeral content item collection in the set of ephemeral content item collections can be ranked based on equation (3a). Ephemeral content item collections450a-dare selected for inclusion in the ephemeral content feed445from the initial ranking. The ephemeral content item collections450a-dcan each include one or more ephemeral content items. For example, the ephemeral content item collection450aincludes ephemeral content items460a, the ephemeral content item collection450bincludes ephemeral content items460b, the ephemeral content item collection450cincludes ephemeral content items460c, and the ephemeral content item collection450dincludes ephemeral content items460d. The ephemeral content items460a-dcan each be referred to as a reel of the respective ephemeral content item collections450a-d. If the viewing user selects one of the ephemeral content item collections450a-d, an immersive viewer can be provided, for example, in a user interface in which the ephemeral content feed445is provided, and playback of ephemeral content items of the selected ephemeral content item collection can begin. In the example ofFIG. 4C, an immersive viewer455is represented as a block that shows a sequence of ephemeral content items460a-dof the ephemeral content item collections450a-din an order of playback. In the example ofFIG. 4C, an ephemeral content item collection450bis selected by the viewing user, and playback of ephemeral content items460bof the ephemeral content item collection450bbegins in the immersive viewer455. At this time, for example, at time the ephemeral content item collections450a,450c,450dcan each be re-ranked based on a probability of the viewing user spending time on the ephemeral content item collection, P(time). For example, the ephemeral content item collections450a,450c,450dcan each be ranked based on equation (3b). Playback of ephemeral content items of the ephemeral content item collections450a,450c,450dcan be performed based on the re-ranked order of the ephemeral content item collections450a,450c,450d. For example, the ephemeral content items460ccan be played after the ephemeral content items460b, the ephemeral content items460dafter that, and the ephemeral content items460aafter that. In some embodiments, the re-ranking of the ephemeral content item collections450a,450c,450din the immersive viewer455can be considered to be re-ranking of reels of the ephemeral content item collections450a,450c,450d. All examples herein are provided for illustrative purposes, and there can be many variations and other possibilities.

FIG. 5Aillustrates an example first method500for ranking ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. It should be understood that there can be additional, fewer, or alternative steps performed in similar or alternative orders, or in parallel, based on the various features and embodiments discussed herein unless otherwise stated.

At block502, the example method500can obtain a plurality of ephemeral content item collections, wherein each ephemeral content item collection of the plurality of ephemeral content item collections includes one or more ephemeral content items. At block504, the example method500can determine a score for each ephemeral content item collection of the plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection and a probability of the user spending time on the ephemeral content item collection. At block506, the example method500can rank the plurality of ephemeral content item collections based on the respective scores of the plurality of ephemeral content item collections. Other suitable techniques that incorporate various features and embodiments of the present disclosure are possible.

FIG. 5Billustrates an example second method520for ranking ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. It should be understood that there can be additional, fewer, or alternative steps performed in similar or alternative orders, or in parallel, based on the various features and embodiments discussed herein unless otherwise stated.

At block522, the example method520can perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection, wherein each ephemeral content item collection of the plurality of ephemeral content item collections includes one or more ephemeral content items. At block524, the example method520can select one or more ephemeral content item collections from the first ranking to provide in an ephemeral content feed of the user. At block526, the example method520can perform a second ranking to rank each ephemeral content item collection of the plurality of ephemeral content item collections other than the selected ephemeral content item collections from the first ranking based on a probability of the user spending time on the ephemeral content item collection. At block528, the example method520can select one or more ephemeral content item collections from the second ranking to provide in the ephemeral content feed of the user. Other suitable techniques that incorporate various features and embodiments of the present disclosure are possible.

FIG. 5Cillustrates an example third method540for ranking ephemeral content associated with a social networking system, according to an embodiment of the present disclosure. It should be understood that there can be additional, fewer, or alternative steps performed in similar or alternative orders, or in parallel, based on the various features and embodiments discussed herein unless otherwise stated.

At block542, the example method540can perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection, wherein each ephemeral content item collection of the plurality of ephemeral content item collections includes one or more ephemeral content items. At block544, the example method540can provide one or more ephemeral content item collections from the first ranking in an ephemeral content feed of the user. At block546, the example method540can receive a selection by the user of an ephemeral content item collection provided in the ephemeral content feed. At block548, the example method540can perform a second ranking to rank each ephemeral content item collection of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection based on a probability of the user spending time on the ephemeral content item collection. Other suitable techniques that incorporate various features and embodiments of the present disclosure are possible.

It is contemplated that there can be many other uses, applications, features, possibilities, and/or variations associated with various embodiments of the present disclosure. For example, users can, in some cases, choose whether or not to opt-in to utilize the disclosed technology. The disclosed technology can, for instance, also ensure that various privacy settings, preferences, and configurations are maintained and can prevent private information from being divulged. In another example, various embodiments of the present disclosure can learn, improve, and/or be refined over time.

Social Networking System—Example Implementation

The user device610comprises one or more computing devices that can receive input from a user and transmit and receive data via the network650. In one embodiment, the user device610is a conventional computer system executing, for example, a Microsoft Windows compatible operating system (OS), Apple OS X, and/or a Linux distribution. In another embodiment, the user device610can be a device having computer functionality, such as a smart-phone, a tablet, a personal digital assistant (PDA), a mobile telephone, etc. The user device610is configured to communicate via the network650. The user device610can execute an application, for example, a browser application that allows a user of the user device610to interact with the social networking system630. In another embodiment, the user device610interacts with the social networking system630through an application programming interface (API) provided by the native operating system of the user device610, such as iOS and ANDROID. The user device610is configured to communicate with the external system620and the social networking system630via the network650, which may comprise any combination of local area and/or wide area networks, using wired and/or wireless communication systems.

The external system620includes one or more web servers that include one or more web pages622a,622b, which are communicated to the user device610using the network650. The external system620is separate from the social networking system630. For example, the external system620is associated with a first domain, while the social networking system630is associated with a separate social networking domain. Web pages622a,622b, included in the external system620, comprise markup language documents614identifying content and including instructions specifying formatting or presentation of the identified content.

In some embodiments, the social networking system630can include an ephemeral content ranking module646. The ephemeral content ranking module646can be implemented with the ephemeral content ranking module102, as discussed in more detail herein. In some embodiments, one or more functionalities of the ephemeral content ranking module646can be implemented in the user device610.

Hardware Implementation