Two-stage content item selection process incorporating brand value

An online system presents content in videos to users. Content providers may value having their content injected into videos from certain sources more than others. This preference is quantified as a brand value score. The brand value score is determined as a function of user engagement with a source of the video and, to account for brand value, the system performs a two-stage auction. First, the system determines whether to inject any content into a video by determining a distribution of brand value of videos per demand for videos in a previous period and filling a projected demand for the content in a current period to determine a brand value threshold. Then, any videos having a brand value above the threshold are eligible for the second stage of the selection process where the system performs an auction where projected benefit of presenting the content is compared to projected loss.

BACKGROUND

This disclosure relates generally to identifying content items for presentation to users of an online system, and more particularly to performing a two-stage selection process for presenting content items in videos that incorporates a brand value associated with a source of the videos.

Online systems, such as social networking systems, allow users to connect to and to communicate with other users of the online system. Users may create profiles on an online system that are tied to their identities and include information about the users, such as interests and demographic information. The users may be individuals or entities such as corporations or charities. Online systems allow users to easily communicate and to share content with other online system users by providing content to an online system for presentation to other users. Content provided to an online system by a user may be declarative information provided by a user, status updates, check-ins to locations, images, photographs, videos, text data, or any other information a user wishes to share with additional users of the online system. An online system may also generate content for presentation to a user, such as content describing actions taken by other users on the online system.

Additionally, many online systems commonly allow users (e.g., businesses) to sponsor presentation of content on an online system to gain public attention for a user's products or services or to persuade other users to take an action regarding the publishing user's products or services. Content for which the online system receives compensation in exchange for presenting to users is referred to as “sponsored content.” Many online systems receive compensation from a user for presenting online system users with certain types of sponsored content provided by this type of user. Frequently, online systems charge a user for each presentation of sponsored content to an online system user or for each interaction with sponsored content by an online system user. For example, an online system receives compensation from a user each time a content item provided by the publishing user is displayed to another user on the online system or each time another user is presented with a content item on the online system and interacts with the content item (e.g., selects a link included in the content item), or each time another user performs another action after being presented with the content item.

Content items may be associated with targeting criteria that identify characteristics of online system users eligible to be presented with the content item. For example, a content item is eligible to be presented to an online system user having characteristics satisfying at least a threshold amount of targeting criteria associated with the content item; however, the content item is not eligible to be presented to another online system user having characteristics satisfying less than the threshold amount of targeting criteria associated with the content item. Targeting criteria associated with a content item are often specified by a user providing the content item to an online system, and allow an online system to identify users who are most likely to be interested in being presented with a particular content item as eligible be presented with the content item.

SUMMARY

An online system receives content items for presentation in videos to users of the online system. Each content item may include targeting criteria and a bid amount. A content item provider, such as an advertiser, may want to present their content items or advertisements for their products or services with videos from certain sources more than others and this preference is quantified as a brand value score. The brand value score, in one embodiment, is determined as a function of user engagement with a source of the video, such as a brand page within the online system, or other content related to the source. Each brand, in one embodiment, has a brand page in the online system and their brand value is determined as a metric for determining whether it is worthwhile or not to present a content item within videos provided by this brand.

Accordingly, the online system obtains a number of video views for each of a number of videos presented to users of the online system for a previous time period (e.g., the last hour, last 24 hours, etc.). The online system also obtains user interactions corresponding to users of the online system interacting with the source (e.g., brand page, company, website, etc.) of these videos and the user interactions are performed by users in association with the source. In one embodiment, user interactions with the brand page of a source are used as a proxy for the brand value for a given video. The user interactions include users commenting on the brand page, sharing the brand page with at least one other user, re-posting or sharing content posted by or on the brand page, expressing a preference for the brand representing the brand page, and so forth. High user interaction with a source and, in particular, repeated engagement with the source over a period of time (e.g., the same user regularly commenting and/or sharing content from the source over time, etc.), is a relevant indication of user interest and, therefore, brand value.

To account for brand value, the online system performs a two-stage auction, where the online system first determines whether to inject any content item into a video. In one embodiment, this is a binary determination made by determining a distribution of brand value of videos per demand for videos (e.g., in a previous period) and filling a projected content item demand in a current period to determine the brand value threshold or cutoff. Then, any videos having a brand value above the brand value threshold will be eligible to have content items injected therein. In a second stage, the online system performs an auction in which the projected benefit (e.g., ECPM bid plus organic score) is compared to the projected loss (e.g., engagement loss plus brand value) to determine whether the content item will be injected at certain locations in the video.

With the user interactions, the online system first determines a brand value for each video and the distribution of brand value video views is generated in order to determine the brand value threshold. In one embodiment, the distribution of brand values is a histogram of video views by the brand value of each video. However, the brand value video views can be ranked from highest brand value to lowest brand value instead. The online system then determines, for a current time period, a content item inventory. The online system determines the brand value threshold for the current time period based on the content item inventory by allocating each content item in inventory to a video view from the previous time period. For example, each content item in the content item inventory is allocated to a video view from the previous time period starting with the highest brand value video views first until all the content items in the content item inventory have been allocated to a video view from the previous time period. Accordingly, the brand value of the lowest allocated video view defines the brand value threshold.

Accordingly, for each video impression opportunity to present a content item within a video to a user in the current time period, the online system determines the brand value for the video corresponding to the video impression opportunity. Then, the online system determines whether the brand value for the video is greater than the brand value threshold.

If the brand value for the video being greater than the brand value threshold, the online system performs a selection process to select a content item for inclusion within the video. In one embodiment, the selection process includes computing an affinity score between the user and candidate content items based on the targeting criteria associated with each of the candidate content items and selecting a candidate content item for inclusion in the video based on the computed affinity score and a bid amount associated with the candidate content item. However, if the brand value for the video is less than the brand value threshold, the process ends, the online system does not perform the selection process and instead allows the video to be presented to a viewing user without a content item therein.

Accordingly, the two-stage selection process for presenting content items in videos that incorporates a brand value associated with a source of the videos addresses a problem that arises specifically in online content distribution systems, which is how to pair an inventory of content items with a projected demand for a larger set of video views. The first stage determination of whether to participate in the selection process provides a first content filter that is faster and more computationally efficient to initially perform than to perform in conjunction with the content item selection stage (second stage). Thus, using the first stage as a condition for conducting the second stage beneficially improves system performance, particularly, for the delivery of videos that would not have passed the first stage filter.

DETAILED DESCRIPTION

Overview

An online system presents content items in videos delivered to users of the online system. A content item provider may value having their content items presented with videos from certain sources more than others and this preference is quantified as a brand value score. The brand value score may be determined as a function of user engagement with a source of the video, such as a brand page within the online system, or other content related to the source. For example, the video could be highlights from a football game provided by the brand and the source could be the brand page within (or maintained by) the online system. Each brand associated with these brand pages may provide video content to users of the online system and their brand value is determined as a metric for determining whether it is worthwhile or not to present a content item within videos they provide.

The online system obtains video views for at least a subset of videos presented to users during a previous time period (e.g., the last hour, last 24 hours, etc.). The online system also obtains user interactions corresponding to users of the online system interacting with the source of these videos. The source, in one embodiment, is a brand page providing one or more videos to the users of the online system and the user interactions are performed by users in association with the brand page. The user interactions include users commenting on a video, expressing a preference for the video, sharing the video with at least one other user, posting the video to their user profile, and so forth. The user interactions, however, are not limited to the videos themselves and may additionally or instead be directed at the brand page itself. These interactions include commenting on the brand page, sharing the brand page with at least one other user, re-posting or sharing content posted by or on the brand page, expressing a preference for the brand representing the brand page, and so forth. High user interaction with a source and, in particular, repeated engagement with the source over a period of time (e.g., the same user regularly commenting and/or sharing content from the source over time, etc.), is a relevant indication of user interest and, therefore, brand value. Thus, the brand value is quantified as a function of user engagement, retention, and/or loyalty. Prior scoring models have not accounted for the brand value and, yet, this is a source of value motivating content item insertion in many videos.

Accordingly, in order to account for the brand value of these brands in determining whether to present a content item in a video, the online system performs a two-stage selection process. Thus, for a particular opportunity to present a content item in a video to a user, the online first determines whether to present the content item in the video at all by filling a projected content item demand in a current period to determine a cutoff brand value or threshold. This determination is made by determining a distribution of brand values of videos per demand for videos in a previous period (e.g., the last 24 hours, week, etc.). Then, any videos having a brand value above the cutoff are eligible to have content items presented therein. In a second stage, the system performs an auction in which the projected benefit is compared to the projected loss to determine whether the content item will be presented with the video.

A distribution of brand value of video views is determined in order to determine the cutoff brand value or brand value threshold.FIG. 1shows a brand value histogram100of a number of video views by brand value, in accordance with an embodiment. As described above, the brand value is determined for each brand (Brand A, Brand B . . . , Brand Z) and brand value histogram100shows each brand ranked from highest brand value to lowest brand value based on the number of video views per million. A height of each column102in the brand value histogram100represents the number of views for that particular range of brand values. For example, Brand value histogram100shows that there were 6 million video views in this time period for brands with a brand value between 0 and 1 by this scale. There were also 3.5 million video views for brands with a brand value between 1 and 2; 2.5 million video views for brands with a brand value between 2 and 3; 5.5 million video views for brands with a brand value between 3 and 4; 5.5 million video views for brands with a brand value between 4 and 5; 3 million video views for brands with a brand value between 5 and 6; 2 million video views for brands with a brand value between 6 and 7, 1 million video views for brands with a brand value between 7 and 8; 1.5 million video views for brands with a brand value between 8 and 9; and 1 million video views for brands with a brand value between 9 and 10. Each different patterned segment in each column102represents a different brand in that column102. In total, there were 31.5 million video views for this time period.

For a current time period, the online system obtains content item inventory for content items to be present within the videos in order to determine the brand value threshold. Accordingly, the online system determines the brand value threshold by allocating each content item in the content item inventory to a video view from the previous time period. This is achieved by mapping the total number of videos views (from the previous time period) to the total number of content items in inventory (for the current time period) by filling or allocating the content items to the video views with the highest brand value until all the content items have been allocated. The resulting brand value of the lowest allocated video view, therefore, defines the brand value threshold for the first stage selection process.

Referring toFIG. 1, the online system has 14 million content items to present to users within videos for the current time period and there were 31.5 million video views in the previous period. Thus, in order to determine the brand value threshold for the current item period, content items in inventory for the current time period are allocated to views from the previous time period starting with the views having the highest brand value first. Accordingly, inventory covers all views corresponding to video views with brand values between 9 and 10 (e.g., 1 million), 8 and 9 (e.g., 1.5 million), 7 and 8 (e.g., 1 million), 6 and 7 (e.g., 2 million), 5 and 6 (e.g., 3 million), and 4 and 5 (e.g., 5.5 million). However, there are no more content items in inventory for video views having a brand value less than 4, which is assigned the brand value threshold106for the current period. Therefore, videos originating from a source having a brand value greater than 4, in this example, is part of a participation segment110and videos originating from a source having a brand value less than 4 are part of a do-not-participate segment108.

As described in greater detail below, video impression opportunities for videos from a source with a brand value greater than or at least equal to the brand value threshold106for the current period are eligible to have content items presented therein with the videos. Accordingly, in a second stage, the online system then performs an auction in which the projected benefit (e.g., ECPM bid plus organic score) of presenting the content item with the video is compared to the projected loss (e.g., engagement loss plus brand value) of presenting the content item with the video to determine whether it is worthwhile to present the content item with the video.

System Architecture

FIG. 2is a block diagram of a system environment200for an online system240. The system environment200shown byFIG. 2comprises one or more client devices210, a network220, one or more third-party systems230, and the online system240. In alternative configurations, different and/or additional components may be included in the system environment200. For example, the online system240is a social networking system, a content sharing network, or another system providing content to users.

The client devices210are one or more computing devices capable of receiving user input as well as transmitting and/or receiving data via the network220. In one embodiment, a client device210is a conventional computer system, such as a desktop or a laptop computer. Alternatively, a client device210may be a device having computer functionality, such as a personal digital assistant (PDA), a mobile telephone, a smartphone, or another suitable device. A client device210is configured to communicate via the network220. In one embodiment, a client device210executes an application allowing a user of the client device210to interact with the online system240. For example, a client device210executes a browser application to enable interaction between the client device210and the online system240via the network220. In another embodiment, a client device210interacts with the online system240through an application programming interface (API) running on a native operating system of the client device210, such as IOS® or ANDROID™.

One or more third party systems230may be coupled to the network220for communicating with the online system240, which is further described below in conjunction withFIG. 3. In one embodiment, a third party system230is an application provider communicating information describing applications for execution by a client device210or communicating data to client devices210for use by an application executing on the client device. In other embodiments, a third party system230provides content or other information for presentation via a client device210. A third party system230may also communicate information to the online system240, such as advertisements, content, or information about an application provided by the third party system230.

The online system240is also capable of linking a variety of entities. For example, the online system240enables users to interact with each other as well as external websites provided by the third party systems230or other entities through an API or other communication channels. Thus, the online system240generates and maintains a “social graph” comprising a plurality of nodes interconnected by a plurality of edges. Each node in the social graph may represent an entity that can act on another node and/or that can be acted on by another node. The social graph may include various types of nodes. Examples of types of nodes include users, non-person entities, content items, web pages, groups, events, messages, concepts, and any other things that can be represented by an object in the online system240. An edge between two nodes in the social graph represents a particular kind of connection between the two nodes, which may result from an action that was performed by one of the nodes on the other node. For example, when a first user identifies a second user as a friend, an edge in the social graph is generated connecting a node representing the first user and a second node representing the second user. As various nodes interact with each other, the online system240modifies edges connecting the various nodes to reflect the interactions.

FIG. 3is a block diagram of an architecture of the online system240. The online system240shown inFIG. 3includes a user profile store305, a content store310, an action logger315, an action log320, an edge store325, brand value module330, auction participation module335, auction module340, and a web server345. In other embodiments, the online system240may include additional, fewer, or different components for various applications. Conventional components such as network interfaces, security functions, load balancers, failover servers, management and network operations consoles, and the like are not shown so as to not obscure the details of the system architecture.

While user profiles in the user profile store305are frequently associated with individuals, allowing individuals to interact with each other via the online system240, user profiles may also be stored for entities such as businesses or organizations. This allows an entity to establish a presence on the online system240for connecting and exchanging content, such as videos, with other online system users. The entity may post information about itself, about its products or provide other information to users of the online system240using a brand page associated with the entity's user profile. Other users of the online system240may connect to the brand page to receive information posted to the brand page or to receive information from the brand page. A user profile associated with the brand page may include information about the entity itself, providing users with background or informational data about the entity. As described above, each of the brands associated with a brand pages may provide video content to users of the online system and their brand value is determined as a metric for determining whether it is worthwhile or not to present a content item within videos provided by these entities or sources.

One or more content items included in the content store310include in-stream content for presentation to a user in a video and a bid amount associated with the presentation of the content item in the video. In one embodiment, the content item is an advertisement provided by an advertiser, the bid amount is included in a content item by the advertiser, and is used to determine an expected value, such as monetary compensation, provided by the advertiser to the online system240if the content item is presented in a video to a user, if the content item receives a user interaction when presented, or if any suitable condition is satisfied when content in the content item is presented to a user. For example, the bid amount included in a content item specifies a monetary amount that the online system240receives from a user who provided the content item to the online system240if content in the content item is displayed. In some embodiments, the expected value to the online system240of presenting the content from the content item may be determined by multiplying the bid amount by a probability of the content of the content item being accessed by a user.

In various embodiments, a content item includes various components capable of being identified and retrieved by the online system240. Example components of a content item include: a title, text data, image data, audio data, video data, a landing page, a user associated with the content item, or any other suitable information. The online system240may retrieve one or more specific components of a content item for presentation in some embodiments. For example, the online system240may identify a title and image data from a content item and provide the title and the image data for presentation rather than the content item in its entirety.

Various content items may include an objective identifying an interaction that a user associated with a content item desires other users to perform when presented with content included in the content item. Example objectives include: installing an application associated with a content item, indicating a preference for a content item, sharing a content item with other users, interacting with an object associated with a content item, or performing any other suitable interaction. As content from a content item is presented to online system users, the online system240logs interactions between users presented with the content item or with objects associated with the content item. Additionally, the online system240receives compensation from a user associated with content item as online system users perform interactions with a content item that satisfy the objective included in the content item.

Additionally, a content item may include one or more targeting criteria specified by the source, entity, or user who provided the content item to the online system240. Targeting criteria included in a content item request specify one or more characteristics of users eligible to be presented with the content item. For example, targeting criteria are used to identify users having user profile information, edges, or actions satisfying at least one of the targeting criteria. Hence, targeting criteria allow a user to identify users having specific characteristics, simplifying subsequent distribution of content to different users.

In one embodiment, targeting criteria may specify actions or types of connections between a user and another user or object of the online system240. Targeting criteria may also specify interactions between a user and objects performed external to the online system240, such as on a third party system230. For example, targeting criteria identifies users that have taken a particular action, such as sent a message to another user, used an application, joined a group, left a group, joined an event, generated an event description, purchased or reviewed a product or service using an online marketplace, requested information from a third party system230, installed an application, or performed any other suitable action. Including actions in targeting criteria allows users to further refine users eligible to be presented with content items. As another example, targeting criteria identifies users having a connection to another user or object or having a particular type of connection to another user or object.

The action log320may be used by the online system240to track user actions on the online system240, as well as actions on third party systems230that communicate information to the online system240. Users may interact with various objects on the online system240, and information describing these interactions is stored in the action log320. Examples of interactions with objects include: commenting on posts, sharing links, checking-in to physical locations via a client device210, accessing content items, and any other suitable interactions. Additional examples of interactions with objects on the online system240that are included in the action log320include: commenting on a photo album, communicating with a user, establishing a connection with an object, joining an event, joining a group, creating an event, authorizing an application, using an application, expressing a preference for an object (“liking” the object), and engaging in a transaction. Additionally, the action log320may record a user's interactions with advertisements on the online system240as well as with other applications operating on the online system240. In some embodiments, data from the action log320is used to infer interests or preferences of a user, augmenting the interests included in the user's user profile and allowing a more complete understanding of user preferences.

The action log320may also store user actions taken on a third party system230, such as an external website, and communicated to the online system240. For example, an e-commerce website may recognize a user of an online system240through a social plug-in enabling the e-commerce website to identify the user of the online system240. Because users of the online system240are uniquely identifiable, e-commerce web sites, such as in the preceding example, may communicate information about a user's actions outside of the online system240to the online system240for association with the user. Hence, the action log320may record information about actions users perform on a third party system230, including webpage viewing histories, advertisements that were engaged, purchases made, and other patterns from shopping and buying. Additionally, actions a user performs via an application associated with a third party system230and executing on a client device210may be communicated to the action logger315by the application for recordation and association with the user in the action log320.

In one embodiment, the edge store325stores information describing connections between users and other objects on the online system240as edges. Some edges may be defined by users, allowing users to specify their relationships with other users. For example, users may generate edges with other users that parallel the users' real-life relationships, such as friends, co-workers, partners, and so forth. Other edges are generated when users interact with objects in the online system240, such as expressing interest in a page on the online system240, sharing a link with other users of the online system240, and commenting on posts made by other users of the online system240. Edges may connect two users who are connections in a social network, or may connect a user with an object in the system. In one embodiment, the nodes and edges form a complex social network of connections indicating how users are related or connected to each other (e.g., one user accepted a friend request from another user to become connections in the social network) and how a user is connected to an object due to the user interacting with the object in some manner (e.g., “liking” a page object, joining an event object or a group object, etc.). Objects can also be connected to each other based on the objects being related or having some interaction between them.

The brand value module330determines a brand value for videos being presented to users of the online system240. The brand value module330obtains user interactions and/or connections from action log320and/or edge store325and computes a brand value for the source of each video based at least in part on a number of user interactions with the source. As described above, the source, in one embodiment, is a brand page of an entity providing or making the video accessible to the users of the online system240. The user interactions include users commenting on a video, users expressing a preference for the video, users sharing the video with at least one other user, users posting the video to their user profile, commenting on the brand page, sharing the brand page with at least one other user, re-posting or sharing content posted by or on the brand page, expressing a preference for the brand representing the brand page, and so forth. High user interaction with a source and, in particular, repeated engagement with the source over a period of time (e.g., the same user regularly commenting and/or sharing content from the source over time, etc.), is a relevant indication of user interest and, therefore, brand value. Thus, the BV is quantified as a function of user engagement, retention, and/or loyalty. In one embodiment, repeated engagement, retention, or loyalty is quantified as each subsequent user interaction performed by a user with a page within a specified time period being weight heavier than a first user interaction performed by the user with the page.

In one embodiment, the brand value module330determines the brand value of a source relative to other sources, such as in a Gaussian or normal distribution of cumulative user interactions within some previous period of time (e.g., the last 24 hours, week, month, etc.). In another example, the brand value of a source is determined as a function of cumulative user interactions and repeated engagement of the users with the source (e.g., a user's second interaction with the source within a particular time period is weighted heavier relative to their first interaction).

The auction participation module335is the first of a two-stage selection process for determining whether a content item is presented in-stream with a video based on the brand value of the source of the video. Accordingly, auction participation module335obtains a number of video views for a previous time period (e.g., the last hour, last 24 hours, etc.) from the action log320, identifies the source of each video (e.g., an entity associated with a page in the online system240), obtains a content item inventory of content items for a current time period from the content store310, and determines the brand value threshold106for the current time period based on the brand values associated with the videos and the content item inventory. In one embodiment, the brand value threshold106for the current time period is determined by ranking each of the video views by the brand value of the source of the video and allocating each content item in the content item inventory to a video view from the previous time period starting with the highest brand value video views first until all the content items in the content item inventory have been allocated to a video view from the previous time period. The ranking, in one embodiment, includes generating a histogram of video views by the brand value of each video. If there are more video views than content items in inventory, then the brand value of the source for the lowest allocated video view is used as the brand value threshold for the current time period. In one embodiment, the number of video views for the previous time period is estimated as the projected demand for the videos in the current time period. Thus, the brand value threshold106is determined such that the projected demand for the videos (i.e., video views in the previous time period) in the current time period for sources having a brand value at least meeting the brand value threshold equals a number of content items in the content item inventory. Thus, the brand value threshold can change from one time period to another and is not necessarily constant, but dynamic based on the ever changing brand values of the sources as interactions with their content fluctuates, but also based on current content item inventory, which is also not static.

Accordingly, for a given video impression opportunity to present a content item within a video, auction participation module335additionally determines whether it is worthwhile for the online system240to inject a content item into the video corresponding to the video impression opportunity based on the determined brand value threshold. The video impression opportunity corresponds to an opportunity where the online system240may include a content item for presentation with the video; however, it is not always worthwhile to present a content item with the video. Thus, the auction participation module335of online system240first identifies a source of the video for the video impression opportunity, determines the brand value of the source, and, if the brand value is greater than the brand value threshold for the current time period, auction participation module335determines that it is worthwhile for the online system240to inject a content item into the video for this video impression opportunity and a content item is then selected in a second stage of the two-stage selection process by auction module340, as discussed below. However, if the brand value of the source of the video for the video impression opportunity is less than the brand value threshold, auction participation module335determines that it is not worthwhile for the online system240to inject a content item into the video for this video impression opportunity, the process ends at this stage, and a content item is not selected in the second stage of the two-stage selection process.

In response to the brand value for the video being greater than the brand value threshold, the auction module340selects a single content item for presentation with the video for the impression opportunity from a number of candidate content items. The auction module340performs an auction in which the projected benefit (e.g., ECPM bid plus organic score) of presenting the content item with the video is compared to the projected loss (e.g., engagement loss plus brand value) of presenting the content item with the video to determine whether it is worthwhile to present the content item with the video. Each content item is associated with targeting criteria and a bid amount. The online system240uses the auction process to select a content item to present within the video to a viewing user and the auction module uses the targeting criteria and the bid amount of a content item to select the optimal content item for the viewing user from among the candidate content items. Selecting the optimal content item includes computing an affinity score or organic score between the user and each of the candidate content items based on the targeting criteria associated with each of the candidate content items and selecting a content item for inclusion in the video based on the computed affinity score and the bid amount (e.g., ECPM bid) associated with the candidate content item.

The auction module340, in one embodiment, may additionally calculate an engagement loss associated with presenting the content item within the video. The engagement loss is the probability of the viewing user selecting the content item to the detriment of finishing the video. While this is a benefit of the provider of the content item or advertiser, in one embodiment, this is a detriment to the video source. Thus, in one embodiment, auction module340determines whether to present a content item within a video if the bid amount and affinity score for presenting the content item to the viewing user outweighs the engagement loss and brand value of the video source (i.e., [ECPM+Organic_Score]>[Engagement_Loss+BV]). However, if the bid amount and affinity score for presenting the content item is less than the engagement loss and brand value of the video source, the content item will not be presented with the video.

The web server345links the online system240via the network220to the one or more client devices210, as well as to the one or more third party systems230. The web server345serves web pages, as well as other content, such as JAVA®, FLASH®, XML and so forth. The web server345may receive and route messages between the online system240and the client device210, for example, instant messages, queued messages (e.g., email), text messages, short message service (SMS) messages, or messages sent using any other suitable messaging technique. A user may send a request to the web server345to upload information (e.g., images or videos) that are stored in the content store310. Additionally, the web server345may provide application programming interface (API) functionality to send data directly to native client device operating systems, such as IOS®, ANDROID™, or BlackberryOS.

Presenting Content Items within Videos Based on the Brand Value of the Video Sources

FIG. 4is a flowchart illustrating a process400of presenting a content item within a video based on the brand value of a source of the video, in accordance with an embodiment. The process400may be performed by a single system or two other entities may perform some or all of the steps of the process in other embodiments. Likewise, embodiments may include different and/or additional steps, or perform the steps in different orders.

An online system receives405content items for presentation in videos to users of the online system. Each content item may include targeting criteria and a bid amount. A content item provider, such as an advertiser, may want to present their content items or advertisements (e.g., video advertisements) for their products or services with videos from certain sources more than others and this preference is quantified as a brand value score. The brand value score, in one embodiment, is determined as a function of user engagement with a source of the video, such as a brand page within the online system240, or other content related to the source. As described above, the video could be game highlights provided by the NFL and the source would then correspond to the NFL brand page maintained by the online system240. Each brand, in one embodiment, has a brand page in the online system240and their brand value is determined as a metric for determining whether it is worthwhile or not to present a content item or advertisement within videos provided by this brand. Each video then is associated with a brand page in the online system240that provided the video to users of the online system240.

Accordingly, the online system obtains410a number video views for each of a number of videos presented to users of the online system240for a previous time period (e.g., the last hour, last 24 hours, etc.). The online system also obtains415user interactions corresponding to users of the online system interacting with the brand page of these videos and the user interactions are performed by users in association with the brand page. In one embodiment, user interactions with the brand page are used as a proxy for the brand value for a given video. The user interactions include users commenting on the brand page, sharing the brand page with at least one other user, re-posting or sharing content posted by or on the brand page, expressing a preference for the brand representing the brand page, and so forth. High user interaction with a source and, in particular, repeated engagement with the source over a period of time (e.g., the same user regularly commenting and/or sharing content from the source over time, etc.), is a relevant indication of user interest and, therefore, brand value.

To account for brand value, the online system240performs a two-stage auction, where the online system240first determines whether to inject any content item into a video. This is a binary determination made by determining a distribution of brand value of videos per demand for videos (e.g., in a previous period) and filling a projected content item demand in a current period to determine the brand value threshold or cutoff. Then, any videos having a brand value above the brand value threshold will be eligible to have content items injected therein. In a second stage, the online system240performs an auction in which the projected benefit (e.g., ECPM bid plus organic score) is compared to the projected loss (e.g., engagement loss plus brand value) to determine whether the content item will be injected at certain locations in the video.

With the user interactions, the online system240first determines420a brand value for each video and the distribution of brand value video views is generated in order to determine the brand value threshold. In one embodiment, the distribution of brand values is a histogram of video views by the brand value of each video. However, the brand value video views can be ranked from highest brand value to lowest brand value instead. The online system240then determines425, for a current time period, a content item inventory. The online system determines430the brand value threshold for the current time period based on the content item inventory by allocating each content item in inventory to a video view from the previous time period. For example, each content item in the content item inventory is allocated to a video view from the previous time period starting with the highest brand value video views first until all the content items in the content item inventory have been allocated to a video view from the previous time period. Accordingly, the brand value of the lowest allocated video view defines the brand value threshold. For example, referring back toFIG. 1, the brand value of the lowest allocated video view is between 4 and 5. Therefore, the lowest possible brand value allocated to a video view is 4, in this example, which is the brand value threshold106. Put another way, the number of video views in the previous time period is estimated as the projected demand for the videos in the current time period and the brand value threshold106is determined such that the projected demand for the videos in the current time period for sources having a brand value at least meeting the brand value threshold equals a number of content items in the content item inventory.

Accordingly, for each video impression opportunity to present a content item within a video to a user in the current time period, the online system240determines435the brand value for the video corresponding to the video impression opportunity. Then, the online system240determines whether the brand value for the video is greater than the brand value threshold440. If the brand value for the video being great than the brand value threshold, the online system240performs445a selection process to select a content item for inclusion within the video. In one embodiment, the selection process includes computing an affinity score between the user and candidate content items based on the targeting criteria associated with each of the candidate content items and selecting a candidate content item for inclusion in the video based on the computed affinity score and the bid amount associated with the candidate content item. However, if the brand value for the video is less than the brand value threshold440, the process ends and the online system240does not perform450the selection process. No content item is selected for inclusion within the video. The video is instead presented to the user without the inclusion of a content item.

CONCLUSION