Abstract: Content presented to a user of an online system is presented along with an option allowing the user to view one or more reasons for presentation of the advertisement content to the user and one or more characteristics of the user satisfying targeting criteria associated with the content. For example, a description identifying one or more selected characteristics of the user satisfying the targeting criteria is presented along with the content. The online system selects the one or more characteristics presented along with the content by applying one or more rules to characteristics of the user satisfying targeting criteria included in the content. The rules may account for accuracy of models used to determine whether the user has characteristics, revenue received by the online system from presenting content associated with targeting criteria identifying various characteristics, or prevalence of characteristics among users or targeting criteria of content.

Abstract: Advertisement content presented to a user of an online system is presented along with an option allowing the user to view one or more reasons for presentation of the advertisement content to the user. If the user selects the option, based on targeting criteria associated with the advertisement content and characteristics associated with the user, the online system selects one or more characteristics of the user satisfying the targeting criteria and presents a description to the user identifying the selected one or more characteristics satisfying the targeting criteria. The online system may apply one or more rules based on user perception of characteristics when selecting the one or more characteristics included in the description. An option for the user to prevent use of the selected one or more characteristics when the online system subsequently selects advertisement content for the user is also presented with the description.

Abstract: An online system identifies seed users with a high value score to a third party system. The online system identifies features of each of the seed users. A weight for each of the identified features is identified. The identified features are divided into a plurality of buckets, each bucket indicating a property associated with one or more of the identified features. Each bucket is ranked according to the weights of the identified features in each bucket. The online system identifies an additional user that has a threshold measure of similarity the seed users. The online system transmits a content item to the additional user for presentation. Additionally, the online system transmits one or more third party-presentable factors based on the bucket having the highest rank to the third party system, the third party-presentable factors indicating a reason as to why the additional user was presented with the content item.

Abstract: Content presented to a user of an online system is presented along with an option allowing the user to view one or more reasons for presentation of the advertisement content to the user and one or more characteristics of the user satisfying targeting criteria associated with the content. For example, a description identifying one or more selected characteristics of the user satisfying the targeting criteria is presented along with the content. The online system selects the one or more characteristics presented along with the content by applying one or more rules to characteristics of the user satisfying targeting criteria included in the content. The rules may account for accuracy of models used to determine whether the user has characteristics, revenue received by the online system from presenting content associated with targeting criteria identifying various characteristics, or prevalence of characteristics among users or targeting criteria of content.

Abstract: An online system propagates settings from a user's client device to the online system itself for the user. If multiple users of the online system use the client device, the online system propagates settings of a primary user of the client device to the online system, but does not propagate settings of other users of the client device to the online system. The online system logs accesses to the online system each day from the client device of each user. A user having a maximum number of logged days accessing the system and accessing the online system for at least 50% of the logged days is determined to be the primary user by the online system. The online system may use determination that a user is a primary user of the client device for associating actions with the user, selecting content for the user, and identifying the user.

Abstract: An online system identifies seed users with a high value score to a third party system. The online system identifies features of each of the seed users. A weight for each of the identified features is identified. The identified features are divided into a plurality of buckets, each bucket indicating a property associated with one or more of the identified features. Each bucket is ranked according to the weights of the identified features in each bucket. The online system identifies an additional user that has a threshold measure of similarity the seed users. The online system transmits a content item to the additional user for presentation. Additionally, the online system transmits one or more third party-presentable factors based on the bucket having the highest rank to the third party system, the third party-presentable factors indicating a reason as to why the additional user was presented with the content item.

Abstract: An online system propagates settings from a user's client device to the online system itself for the user. If multiple users of the online system use the client device, the online system propagates settings of a primary user of the client device to the online system, but does not propagate settings of other users of the client device to the online system. The online system logs accesses to the online system each day from the client device of each user. A user having a maximum number of logged days accessing the system and accessing the online system for at least 50% of the logged days is determined to be the primary user by the online system. The online system may use determination that a user is a primary user of the client device for associating actions with the user, selecting content for the user, and identifying the user.

Abstract: An online system receives a content item from content providers and a target audience criterion and for targeting the received content item. The online system determines recommendations of modifications of the target audience criteria such that users of the modified target audience criteria have a higher likelihood of interacting with the content item compared to the received target audience criteria. The online system stores measures of interest of subsets of users for different topics. The online system determines topics associated with the content item and determines measures of interest of subsets of users in the content item based on topics associated with the content item. The online system provides recommendations for modifying the target audience criteria based on the determined measures of interests of users.

Abstract: An online system identifies a threshold score dividing seed users into low value seed users and high value seed users based on the initial score of each seed user. The online system identifies, as additional high value users, additional users of the online system having a measure of similarity to one or more of the high value seed users. The online system identifies, as additional engaged users, additional users of the online system having a measure of similarity to one or more of the identified seed users. The online system determines a value score for each of the additional high value users. The online system determines an engagement score for each of the additional engaged users. The online system determines one or more intersections between the value tiers of users containing the additional high value users and the engagement tiers of the additional engaged users based on the scores.

Abstract: Content presented to a user of an online system is presented along with an option allowing the user to view one or more reasons for presentation of the advertisement content to the user and one or more characteristics of the user satisfying targeting criteria associated with the content. For example, a description identifying one or more selected characteristics of the user satisfying the targeting criteria is presented along with the content. The online system selects the one or more characteristics presented along with the content by applying one or more rules to characteristics of the user satisfying targeting criteria included in the content. The rules may account for accuracy of models used to determine whether the user has characteristics, revenue received by the online system from presenting content associated with targeting criteria identifying various characteristics, or prevalence of characteristics among users or targeting criteria of content.

Abstract: An online system receives a content item from content providers and a target audience criterion and for targeting the received content item. The online system determines recommendations of modifications of the target audience criteria such that users of the modified target audience criteria have a higher likelihood of interacting with the content item compared to the received target audience criteria. The online system stores measures of interest of subsets of users for different topics. The online system determines topics associated with the content item and determines measures of interest of subsets of users in the content item based on topics associated with the content item. The online system provides recommendations for modifying the target audience criteria based on the determined measures of interests of users.

Abstract: A user makes a request to restrict targeted advertising through third party services accessed on a client device. A publishing system obtains information indicating that the user requested to restrict targeted advertising. The publishing system updates a profile associated with an account of the user to indicate that the user has requested to restrict targeted advertising.

Abstract: A social networking system receives a sponsored story request identifying a story describing an action performed by a social networking system user and generates a sponsored story accordingly. The sponsored story request may also include a bid amount and other information for generating a sponsored story from the sponsored story request. When an action is included in a sponsored story presented to a social networking system user, the social networking system notifies the user associated with the action and provides one or more settings regulating inclusion of actions associated with the user in sponsored story requests. For example, settings allow a user to prevent generation of sponsored stories including a specified type of action, a specific action, or multiple actions associated with the user. Hence, the settings allow a user to limit or prevent generation of sponsored stories describing actions associated with the user.

Abstract: When two or more devices are near each other, they are likely to hear the same ambient sounds. To detect such proximity, each device captures a short digital audio signal from its microphone and uploads it to a proximity-detecting service along with a timestamp that indicates when the clip was captured. The proximity-detecting service maintains a history of sound clips for its clients and analyzes recently received sound clips that have similar time stamps. The devices can then be grouped according to the similarities of their sound clips. Devices that are grouped together in this way are deemed to be near each other.

Abstract: Advertisement content presented to a user of an online system is presented along with an option allowing the user to view one or more reasons for presentation of the advertisement content to the user. If the user selects the option, based on targeting criteria associated with the advertisement content and characteristics associated with the user, the online system selects one or more characteristics of the user satisfying the targeting criteria and presents a description to the user identifying the selected one or more characteristics satisfying the targeting criteria. The online system may apply one or more rules based on user perception of characteristics when selecting the one or more characteristics included in the description. An option for the user to prevent use of the selected one or more characteristics when the online system subsequently selects advertisement content for the user is also presented with the description.

Abstract: A social networking system receives a sponsored story request identifying a story describing an action performed by a social networking system user and generates a sponsored story accordingly. The sponsored story request may also include a bid amount and other information for generating a sponsored story from the sponsored story request. When an action is included in a sponsored story presented to a social networking system user, the social networking system notifies the user associated with the action and provides one or more settings regulating inclusion of actions associated with the user in sponsored story requests. For example, settings allow a user to prevent generation of sponsored stories including a specified type of action, a specific action, or multiple actions associated with the user. Hence, the settings allow a user to limit or prevent generation of sponsored stories describing actions associated with the user.

Abstract: Generally, this disclosure describes a scalable cluster router that includes a plurality of server-class computers interconnected together to form a router. Each server may be configured to independently schedule switching of packets to reduce the switch speed requirements on a per server basis. Each server may include a scheduler that independently load balances packet flows across servers of the cluster. Router capacity may be incrementally scaled by adding more servers, and router capacity may be increased by load balancing techniques within individual servers.

Abstract: When two or more devices are near each other, they are likely to hear the same ambient sounds. To detect such proximity, each device captures a short digital audio signal from its microphone and uploads it to a proximity-detecting service along with a timestamp that indicates when the clip was captured. The proximity-detecting service maintains a history of sound clips for its clients and analyzes recently received sound clips that have similar time stamps. The devices can then be grouped according to the similarities of their sound clips. Devices that are grouped together in this way are deemed to be near each other.

Abstract: The invention relates to a system and method for generating realistic network traffic by replaying captured network traffic using parallelized streams of subtraces. In accordance with one method of the invention, a captured trace of network traffic from a network link is provided. The captured trace is split into a number of subtraces. The subtraces are replayed and then recombined into a recombined trace, wherein the timing of packets in the recombined trace approximates the timing of packets in the captured trace.

Abstract: Generally, this disclosure describes a scalable cluster router that includes a plurality of server-class computers interconnected together to form a router. Each server may be configured to independently schedule switching of packets to reduce the switch speed requirements on a per server basis. Each server may include a scheduler that independently load balances packet flows across servers of the cluster. Router capacity may be incrementally scaled by adding more servers, and router capacity may be increased by load balancing techniques within individual servers.