Kabam, Inc.

Zynga Inc.

Aftershock Services, Inc.

Electronic Arts Inc.

Sift Science, Inc.

Kevin A Lee

John Kim

Kevin Chanthasiriphan

David McNeill

Albert Wei

Daniel McCaffrey

Yan Zhang

Kenneth Rudin

Ananda Ghosh

Tomi Huttula

Wei-Ling Wu Deckinga

Christopher Chinwen Yu

Jay Jodway

Devin Nambiar

Wei Liu

Inyang Akpan

Wynne Chyou

Hui Wang

Rishabh Kothari

Helen Marushchenko

Aaron Port

Daniel Hoffman

Steven Andrew Martin

William Kim

William Christopher Parry

Participation by multiple users in an online game through client computing platforms associated with the users is facilitated. User accounts associated with the users indicate affiliations having a functional significance between users. Presentation of offers to sell virtual items are provided to users having a first affiliation and to users having a second affiliation. The virtual items associated with the offers are distributed to the users having a first affiliation upon an indication that a threshold number of users having the first affiliation have accepted the offer and are not distributed to users having a second affiliation upon an indication that a threshold number of users having the second affiliation have not accepted the offer.

System and method for providing virtual items to users of a virtual space

An online game is provided to users via client computing devices. Gameplay metrics are determined for users of the online game based on actions taken by the users in the online game. Secondary games are provided, where the potential awards provided by the secondary games are determined based on the gameplay metrics of the users.

System and method for providing awards to users of an online game

Systems and methods for detecting digital abuse or digital fraud that involves malicious account testing includes implementing a machine learning threat model that predicts malicious account testing using misappropriate accounts, wherein a subset of a plurality of learnable variables of an algorithmic structure of the machine learning threat model includes one or more learnable variables derived based on feature data indicative of malicious account testing; wherein implementing the machine learning threat model includes: (i) identifying event data from an online event that is suspected to involve digital fraud or digital abuse, (ii) extracting adverse feature data from the event data that map to the one or more learnable variables of the subset, and (iii) providing the adverse feature data as model input to the machine learning threat model; and computing, using the machine learning threat model, a threat prediction indicating a probability that the online event involves malicious account testing.

Systems and methods for configuring and implementing a malicious account testing machine learning model in a machine learning-based digital threat mitigation platform

Systems and methods for configuring and implementing a card testing machine learning model in a machine learning-based digital threat mitigation platform

An optimized friend recommendation system is described. An active social network (ASN) of a player of an online game is determined based on a frequency of reciprocated communications between the player and friends of the player. The ASN of the player has friends of the player with a minimum number of closed-loop communications with the player within a predetermined duration. The social network of non-ASN friends outside the ASN of the player is identified. One or more non-ASN friends identified and suggested to socially engage with the player in an online game based on the social network of non-ASN friends of the player outside the ASN of the player are.

Friend recommendation system

A system and method for facilitating chance-based in-game virtual item distribution in a video game. A mini-game interface presents a mini-game to a user that has committed to a battle. Prior to instigation of the battle the user participates in a chance-based mini-game that determines awards to be distributed to the user from a set of potential awards. Benefits associated with a determined award are applied to a game entity included in a battle which is to follow the mini-game.

Method and system for facilitating chance-based in-game virtual item distribution

System and method for providing cross-game virtual containers in online games are disclosed. Virtual items usable in multiple online games may be packaged in a cross-game virtual container. Instances of cross-game virtual container may be presented for purchase by user in a virtual store. The price of a given instance of cross-game virtual container may be set as a fraction of the total of the individual prices of the virtual items in the given instance of cross-game virtual container. After an activation of a purchased instance of cross-game virtual container by a user in one of the online games, virtual items in the purchased instance of cross-game virtual container may be made available for access to the user in respective online games. In some examples, a notification may be generated for informing the user of the availability of the virtual items in the activated instance of cross-game virtual container.

Providing virtual containers across online games

A system and method for facilitating a cross-game competitive event are disclosed. The cross-game competitive event may measure user performance in multiple online games during an event time period. For such measurement, the cross-game competitive event may be associated with an event metric. The event metric may correspond to gameplay metrics for users of the multiple online games. The value of the event metric may be determined for a given user based on aggregation of changes in the values of gameplay metrics in the multiple online games within the event time period. An award may be distributed to the given user based on the event metric value determined for the given user upon conclusion of the cross-game competitive event.

Facilitating an event across multiple online games

One aspect of the present disclosure relates to increasing an attribute of a virtual item type in a virtual space. Users, having virtual item instances of a virtual item, may be presented with an offer to increase a performance level of virtual item instances of the virtual item as a group in exchange for pooled consideration from the users as a group. The performance level of the virtual item instances of the virtual item may be increased as a group in exchange for the users, as a group, tendering the pooled consideration.

System and method for increasing attributes of a virtual item

Growing community of inventors

San Francisco, CA, United States of America

Kevin A Lee