Abstract:
An online system receives tracking requests from client devices interacting with a website to analyze user interactions with the website. The website provides instructions with web pages sent to a client device that cause the client device to send tracking instructions to the online system. The online system sends requests for web pages to the website, receives a plurality of web pages from the website, and determines a count of distinct web pages provided by the website. The online system determines a score for the website indicating a quality of tracking instructions of the website based on various factors, including an aggregate value based on the distinct webpages of the website that include tracking instructions and the count of distinct web pages provided by the website. Based on this score, the online system generates a report describing a quality of the tracking instructions of the website.
Abstract:
An online system matches a user across multiple online systems based on image data for the user (e.g., profile photo) regardless whether the image data is from the online system, a different but related online system or a third party system. For example, to match the user across a social networking system and INSTAGRAM™ system, the online system compares the similarity between images of the user from both systems in addition to similarity of textual information in the user profiles on both systems. The similarity of image data and the similarity of textual information associated with the user are used by the online system as indicators of matched user accounts belonging to the same user across both systems. The online system applies models trained using deep learning techniques to match a user across multiple online systems based on the image data and textual information associated with the user.
Abstract:
A method is disclosed for attributing conversions among multiple members of a socially connected influence group, such as a household. Data from advertising impressions, including views and clicks, is maintained by an online system. When a conversion is made, the social network of the user creating the conversion event is analyzed. An influence group, defined as a group comprising the users and group of socially connected users whom influence the purchasing decisions of the first user, is created. Conversion data is analyzed for the first user and the other members of the influence group. This data is weighted to determine the propensities of successful conversions among all members of the influence group.
Abstract:
An online system associates a user with a characteristic attribute of a geographic area in response to the user visiting the geographic area. The geographic area is identified based on visits by users of the online system, and attributes of entities associated with locations within the geographic area. A characteristic attribute is identified from the obtained attributes. A visit to the geographic area by a first user not associated with the characteristic attribute is identified. In response to identifying that the first user has visited the geographic area, the first user is associated with the characteristic profile attribute. Based at least in part on the association between the characteristic profile attribute and the first user, a content item is sent to a client device for presentation to the first user.
Abstract:
An online system tracks identities of users that interact with the online system. The online system sends a browser identifier for storing on a client device that interacts with the online system. The browser identifier uniquely identifies a browser of the client device used for interacting with the online system. A content provider system receives the browser identifier from the client device and uses the browser identifier for logging user actions associated with content provided by the content provider system. The content provider system sends user action logs to the online system and the online system determines users that used the client device at a timestamp associated with the user action log. The online system provides the user identifiers to the content provider system. The content provider system uses the user identifiers to generate reports.
Abstract:
In one embodiment, a method includes initiating a communication session with a second client system associated with a second user via a communication network, wherein the communication session is initiated in a first modality, receiving a ping to the first client system from the communication network to evaluate available bandwidth on the communication network, estimating, by the first client system, an amount of bandwidth available on the communication network for use by the first client system, determining, by the first client system, the amount of bandwidth available on the communication network for use by the first client system is insufficient for the first modality, and switching the communication session with the second client system to a second modality by the first client system, wherein the second modality uses less bandwidth than the first modality.
Abstract:
An online system receives tracking requests from client devices interacting with a website. The online system analyzes user interactions with websites using the tracking requests. The online system identifies missing parameters in the tracking requests and predicts values of the missing parameters. The online system may also identify parameters that are populated incorrectly and predicts their correct values. The online system uses the predicted parameter values for generating reports describing user interactions with the website. The online system predicts the values of the missing parameters based on metadata extracted from previous tracking requests received from client devices and also via web crawling of websites. The online system generates accurate reports based on the predicted parameters values.
Abstract:
Online system users interact with one or more third party systems, with the online system maintaining an account for each of its users and each third party system maintaining a third party account for each of its users. The online system compares information in a user's account to accessible information in third party accounts and establishes connections between the user's account and third party accounts based on the comparisons, a connection including a confidence level indicating a likelihood of a third party account being associated with the user of the online system corresponding to the user's account. Similarly, the online system compares information in different third party accounts and establishes connections between different third party accounts based on the comparisons including includes a confidence level indicating a likelihood of a third party account and an additional third party account being associated with the same user.
Abstract:
Different online systems, such as an ad system or a social networking system, maintain different identifiers. An ad system identifies an association between an unsynced cookie maintained by an ad system and a user of the online system. The ad system identifies an overlap IP sequence including multiple occurrences of a user's user id and multiple occurrences of an unsynced cookie id in communications associated with an IP address over a given time period. The ad system determines an overlap score based on the identified overlap IP sequence. The overlap score determines how closely the unsynced cookie is associated with the user of the online system. The ad system determines whether the unsynced cookie id and the user id are associated with one another based on the overlap score. The ad system stores an association between the unsynced cookie and the user of the online system thereby generating a synced cookie.
Abstract:
Disclosed is a method for identifying an action performed by a user in a third party system. Information associated with a form is received by an online system. For instance, hashed values of a plurality of form fields provided by a user and a description of the plurality of form fields are received by an online system. A form is identified based on the received information. Additionally, a determination whether one or more of the received hashed values correspond to stored values by the online system is made. If the received hashed values correspond to stored values in the online system, a user of the online system is identified based on the stored values corresponding to the one or more received hashed values. An identification of an action associated with the identified form and performed by the user in the third party system is stored.