EP-4742138-A2 - LOCATION PRIVACY MANAGEMENT ON MAP-BASED SOCIAL MEDIA PLATFORMS

EP4742138A2EP 4742138 A2EP4742138 A2EP 4742138A2EP-4742138-A2

Abstract

A map-based graphical user interface for a social media application displays to special social media activity information based on submission of geo-tagged social media items to the platform. For users and or submitted items that need predefined location fuzzing criteria, such activity is represented in the graphical user interface at an intentionally inaccurate position.

Inventors

GARCIA, Timothy Jordan
YUNG, MARCEL M
AMITAY, Daniel
SPIEGEL, Evan
LIN, ANDREW
LIN, WALTON
BRODY, Jonathan
GORKIN, Leonid
RAUSSER, John
SHAHNAWAZ, AMER

Assignees

Snap Inc.

Dates

Publication Date: 20260513
Application Date: 20180427

Claims (15)

A system comprising: one or more computer processor devices; and memory having stored therein instructions that configure the system, when the instructions are executed by the one or more computer processor devices, to perform operations comprising: determining one or more attributes of social media activity in a geographical area in an automated process comprising, for each of multiple social media postings forming part of the social media activity, representing the posting as having a density distribution in two-dimensional space; and causing display as part of a graphical user interface, GUI, (612) for a social media platform of one or more user interface elements that are determined based at least in part on the one or more attributes of the social media activity.
The system of claim 1, wherein the density distribution for each posting is centered on a posting location associated with the posting, density of the distribution decreasing radially from the posting location.
The system of claim 1 or 2, wherein representing each posting as having a density distribution comprises an automated kernel smoothing procedure.
The system of any one of claims 1 to 3, wherein the instructions further configure the system to calculate a geographical distribution of posting density in the geographical area by summing, at each of multiple positions within the geographical area, respective density contributions of each posting whose density distribution at least partially overlaps the respective position.
The system of claim 4, wherein the calculating of the geographical distribution of posting density comprises: dividing (1603) the geographical area into a grid of cells; and for each cell, summing the density contribution of each posting whose density distribution at least partially overlaps the respective cell.
The system of any one of claims 1 to 5, wherein the instructions further configure the system to perform operations comprising: representing each posting as additionally having a density distribution in time; and generating respective geographic density distribution models for each of a plurality of time windows, the density distribution of each posting being centered on a time window corresponding with a timestamp of the posting, and the density of the distribution decreasing in other time windows with an increase in time difference between the timestamp and the respective time window.
The system of claim 6, wherein representing each posting as having a density distribution in time comprises applying a kernel smoothing procedure in time space.
The system of any one of claims 1 to 7, wherein the instructions further configure the system to perform operations comprising: accessing social media activity data indicating a set of social media postings within the geographical area; and filtering the set of social media postings by imposing a maximum number of postings per unique user, thereby deriving a filtered data set, wherein the determining of the one or more attributes of social media activity in the geographical area is performed using the filtered data set.
The system of any one of claims 1 to 8, wherein: the one or more attributes of the social media activity includes a geographical distribution of unusualness of posting activity within the geographical area; and the instructions further configure the system to: apply the representation of each posting as having a density distribution to historical social media activity data to derive a historical model of social media activity in the geographical area; calculate a geographical distribution of current social media activity based on a set of social media postings within a predefined preceding time period, the calculating being based at least in part on representing each posting in the set as having a respective density distribution; and calculate the geographical distribution of unusualness of posting activity within the geographical area based on automated comparison of the historical model and the calculated geographical distribution of the current social media activity.
A method comprising: determining one or more attributes of social media activity in a geographical area in an automated process performed by one or more computer processor devices, the automated process comprising, for each of multiple social media postings forming part of the social media activity, representing the posting as having a density distribution in two-dimensional space; and causing display as part of a graphical user interface, GUI, (602) for a social media platform of one or more user interface elements that are determined based at least in part on the one or more attributes of the social media activity.
The method of claim 10, wherein the density distribution for each posting is centered on a posting location associated with the posting, density of the distribution decreasing radially from the posting location, and wherein representing each posting as having a density distribution comprises an automated kernel smoothing procedure, preferably based on an Epanechnikov kernel.
The method of claim 10 or 11, further comprising calculating a geographical distribution of posting density in the geographical area by: dividing the geographical area into a grid of cells; and for each cell, summing the density contribution of each posting whose density distribution at least partially overlaps the respective cell.
The method of any one of claims 10 to 12, further comprising: representing each posting as additionally having a density distribution in time; and generating respective geographic density distribution models for each of a plurality of time windows, the density distribution of each posting being centered on a time window corresponding with a timestamp of the posting, and the density of the distribution decreasing in other time windows with an increase in time difference between the timestamp and the respective time window.
The method of any one of claims 10 to 13, further comprising: accessing social media activity data indicating a set of social media postings within the geographical area; and filtering the set of social media postings by imposing a maximum number of postings per unique user, thereby deriving a filtered data set, wherein the determining of the one or more attributes of social media activity in the geographical area is performed using the filtered data set.
The method of any one of claims 10 to 14, wherein the one or more attributes of the social media activity includes a geographical distribution of unusualness of posting activity within the geographical area, and wherein the method further comprises: applying the representation of each posting as having a density distribution to historical social media activity data to derive a historical model of social media activity in the geographical area; calculating a geographical distribution of current social media activity based on a set of social media postings within a predefined preceding time period, the calculating being based at least in part on representing each posting in the set as having a respective density distribution; and calculating the geographical distribution of unusualness of posting activity within the geographical area based on automated comparison of the historical model and the calculated geographical distribution of the current social media activity.

Description

PRIORITY APPLICATIONS This application is a non-provisional application which claims the benefit of priority to U.S. Provisional Application Serial No. 62/556,134, filed September 8, 2017; U.S. Provisional Application Serial No. 62/552,958, filed August 31, 2017; and U.S. Provisional Application Serial No. 62/491,115, filed April 27, 2017, the contents of which are incorporated herein by reference in their entireties. BACKGROUND Social media applications implement computer-mediated technologies allowing for the creating and sharing of content that communicates information, ideas, career interests, and other forms of expression via virtual communities and networks. Social media platforms use web-based technologies, desktop computers, and mobile technologies (e.g., smart phones and tablet computers) to create highly interactive platforms through which individuals, communities, and organizations can share, co-create, discuss, and modify user-generated content or pre-made content posted online. Mobile electronic devices on which end-user social media applications can be executed typically provide geolocation services that determinc the geographic location of the mobile electronic device, by extension indicating the geographic location of the associated user. Social media content posted by users is often geo-tagged based on the geolocation of a mobile electronic device (such as a mobile phone) by use of which the social media content is captured and/or posted to the social media platform. In other embodiments, social media content may explicitly be geo-tagged by a user using a computer device that does not have activated geolocation services and/or that is not a mobile device (such as a desktop PC). In many social media platforms, the total number of individual social media items that are available for viewing by any particular user can be very large. Search mechanisms that enable users to locate social media content that may be of interest to them can consume significant server side resources and often provide less than satisfactory search results. BRIEF DESCRIPTION OF THE DRAWINGS Some aspects of the disclosure are illustrated in the appended drawings. Note that the appended drawings illustrate example embodiments of the present disclosure and cannot be considered as limiting the scope of the disclosure. FIG. 1 is a block diagram showing an example social media platform system for exchanging, posting, and consuming social media data (e.g., messages and associated content) over a network.FIG. 2 is a block diagram illustrating further details regarding a social media platform system, according to example embodiments.FIG. 3 is a schematic diagram illustrating data which may be stored in a database of the social media platform system, according to certain example embodiments.FIG. 4 is a schematic diagram illustrating a structure of a message, according to some embodiments, generated by a social media client application according to example embodiments.FIG. 5 is a schematic diagram illustrating an example access-limiting process, in terms of which access to content (e.g., an ephemeral message, and associated multimedia payload of data) or a content collection (e.g., an ephemeral message gallery or story) may be time-limited (e.g., made ephemeral).FIGS. 6A and 6B are respective schematic views of a client device providing a map-based graphical user interface for a social media application, according to different respective example embodiments.FIGS. 7A-7C are respective schematic views of a client device providing a destination selection interface forming part of a map-based graphical user interface for a social media application, according to some example embodiments.FIGS. 8A-8C are respective screenshots of a map-based graphical user interface, providing features relating to display of user icons in a map forming part of the interface, according to an example embodiment.FIGS. 9A and 9B are respective screenshots of the functionalities of a map-based graphical user interface that provides access to a chat interface and to friend content via a friend icon displayed as part of the map, according to an example embodiment.FIG. 10A-10D are a series of screenshots of search interfaces provided as part of a map-based graphical user interface, according to respective example embodiments.FIGS. 11A-11B are a series of schematic screenshots illustrating a location-based search mechanism provided by a map-based graphical user interface, according to one example embodiment.FIG. 12 is a schematic view of a social media platform system for providing a map-based graphical user interface for a social media application, according to one example embodiment.FIGS. 13A-13B show respective flow charts illustrating an example embodiment of a method of providing a map-based graphical user interface for a social media application that includes an activity heat map, according to an example embodiment.FIG. 14 shows a flowchart illustrating a m