Abstract: A social networking system receives information describing locations associated with a plurality of its users. Based on information identifying each user and a location associated with each user, the social networking system generates and stores hash values. For example, the social networking system maintains various geo-tiles that each identify geographic areas and generates a hash value based on a user identifier and an identifier of a geo-tile including the location associated with the user. Based on the hash values and locations associated with one or more users, the online system determines a number of unique users associated with locations included in a geographic region. When determining the number of unique users, the online system accounts for a rate at which the online system updates location information associated with various users.

Abstract: In one embodiment, a computing device selects a number of location updates from users which corresponds to a place. Each location update includes data indicating a geographic location that a user was at, and a time corresponding to when the user was at the geographic location. The computing device selects a first subset of the location updates which have geographic locations within a particular geographic area. For each location update in the first subset, the computing device determines a corresponding user and time. The computing device selects a second subset of location updates, each location update in the second subset corresponding to a user from the first subset, and a time within a threshold time of the time of the location update in the first subset. The computing device generates a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset.

Abstract: A social networking system receives information describing locations associated with a plurality of its users. Based on information identifying each user and a location associated with each user, the social networking system generates and stores hash values. For example, the social networking system maintains various geo-tiles that each identify geographic areas and generates a hash value based on a user identifier and an identifier of a geo-tile including the location associated with the user. Based on the hash values and locations associated with one or more users, the online system determines a number of unique users associated with locations included in a geographic region. When determining the number of unique users, the online system accounts for a rate at which the online system updates location information associated with various users.

Abstract: An online system estimates a lift in foot traffic at a store in response to an advertisement campaign at the online system. The online system identifies a physical location for the store and obtains location data for a base group of users and a lifted group of users, where the lifted group of users receives advertisements associated with the store and the base group of users does not. The online system computes a distance between the location of the store and the user's location to create a base distance array for the base group and a lifted distance array for the lifted group. The online system then determines an aggregate value that represents a measure of a number of users visiting the store for each of the base distance array and the lifted distance array, and estimates a lift in foot traffic by comparing the two aggregate values.

Abstract: In one embodiment, a computing device selects a number of location updates from users which corresponds to a place. Each location update includes data indicating a geographic location that a user was at, and a time corresponding to when the user was at the geographic location. The computing device selects a first subset of the location updates which have geographic locations within a particular geographic area. For each location update in the first subset, the computing device determines a corresponding user and time. The computing device selects a second subset of location updates, each location update in the second subset corresponding to a user from the first subset, and a time within a threshold time of the time of the location update in the first subset. The computing device generates a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset.

Abstract: In one embodiment, a computing device selects a number of location updates from users which corresponds to a place. Each location update includes data indicating a geographic location that a user was at, and a time corresponding to when the user was at the geographic location. The computing device selects a first subset of the location updates which have geographic locations within a particular geographic area. For each location update in the first subset, the computing device determines a corresponding user and time. The computing device selects a second subset of location updates, each location update in the second subset corresponding to a user from the first subset, and a time within a threshold time of the time of the location update in the first subset. The computing device generates a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset.

Abstract: An online system estimates a lift in foot traffic at a store in response to an advertisement campaign at the online system. The online system identifies a physical location for the store and obtains location data for a base group of users and a lifted group of users, where the lifted group of users receives advertisements associated with the store and the base group of users does not. The online system computes a distance between the location of the store and the user's location to create a base distance array for the base group and a lifted distance array for the lifted group. The online system then determines an aggregate value that represents a measure of a number of users visiting the store for each of the base distance array and the lifted distance array, and estimates a lift in foot traffic by comparing the two aggregate values.

Abstract: In one embodiment, a computing device selects a number of location updates from users which corresponds to a place. Each location update includes data indicating a geographic location that a user was at, and a time corresponding to when the user was at the geographic location. The computing device selects a first subset of the location updates which have geographic locations within a particular geographic area. For each location update in the first subset, the computing device determines a corresponding user and time. The computing device selects a second subset of location updates, each location update in the second subset corresponding to a user from the first subset, and a time within a threshold time of the time of the location update in the first subset. The computing device generates a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset.

Abstract: A social networking system receives information describing locations associated with a plurality of its users. Based on information identifying each user and a location associated with each user, the social networking system generates and stores hash values. For example, the social networking system maintains various geo-tiles that each identify geographic areas and generates a hash value based on a user identifier and an identifier of a geo-tile including the location associated with the user. Based on the hash values and locations associated with one or more users, the online system determines a number of unique users associated with locations included in a geographic region. When determining the number of unique users, the online system accounts for a rate at which the online system updates location information associated with various users.