Facebook, Inc.

Janaka Liyanage

David Gross-Baser

Danilo Torres De Sa Resende

Ajoy Joseph Frank

Ami Vora

Srikant Ramakrishna Ayyar

Wenrui Zhao

Louis Eisenberg

Eric Michel Giovanola

Eric Michael Giovanola

A social networking system includes pages created by users for providing content related to topics of interest. An interaction engine captures data and maintains analytical information about how users interact with pages and posts. When a user takes an action such as liking a page or a post, the interaction engine updates the page's activity history to reflect the activity and information about the user who took the action. The interaction engine also measures the reach of pages and posts, by determining how and from where each user viewed the page and its contents. The interaction engine further tracks the community's interest in pages and posts by determining how many unique users create stories that include a page or its content. An insights module uses the data obtained by the interaction engine to synthesize graphical reports about page interactions and present the reports to page administrators.

Measuring page viewership in a social network

Unique user impressions of advertisements on a social networking system may be tracked and approximated by the social networking system. After an advertisement is delivered to a user, identifying information about the advertisement is associated with the user if the advertisement was not previously presented to the user. An impression count records the number of unique impressions of the advertisement by users of the social networking system up to a predetermined threshold. After the predetermined threshold is reached, the social networking system records a sampling of the unique impressions. Upon request for the number of unique impressions for an advertisement, the social networking system may extrapolate the recorded unique impressions based on the predetermined threshold. In one embodiment, a time degradation factor may be applied to the sampling rate so that recent impressions are sampled more than older impressions.

Approximating unique advertisement impressions on a social networking system

A user posting content to a social networking system provides a conversion definition along with the content. The conversion definition identifies a type of interaction associated with the content, such as type of interaction with the content that the user would like to track. After the content is presented to additional users, the social networking system identifies additional users performing the type of interaction with the content identified by the conversion definition. One or more metrics describing the interactions of the type of interaction associated with the content are provide to the user that posted the content.

Conversion tracking of organic content in a social networking system

An online system allows creators and owners of content items presented within the system to view real-time metrics related to the content items. The online system stores data describing user interactions with content items in one or more activity logs and processes the activity logs in a distributed manner activity to identify user interactions with content items. For example, activity logs are divided into several portions that are processed in parallel using aggregation operators to generate user interaction aggregations. An aggregation includes one or more user interactions associated with the same content item and sharing certain criteria. From the user interaction aggregations, the online system determines one or more requested metrics, and may combine user interaction aggregations related to different content items when computing metrics.

Generating metrics for content items presented in an online system

A social networking system generates one or more metrics describing user interactions with objects to describe the popularity of the objects among users. Data describing actions performed by social networking system users on objects stored by the social networking system to identify an action, the user performing the action and the object on which the action was performed. Stored actions performed on a selected object are retrieved and a subset of the actions is generated by sampling the stored actions at a sampling rate. A number of unique users included in the subset is determined and used along with the sampling rate to determine the number of unique users included in the retrieved actions, which is used to derive a metric describing user interaction with the selected object.

Growing community of inventors

Mountain View, CA, United States of America

Janaka Liyanage