Abstract: The present disclosure relates to a system, method, computer program and electronic device for managing end user data takeout. A data takeout message is communicated to one or more target subscriber entities to instruct the one or more target subscriber entities to enact a data takeout request relating to an end user. User data relating to the end user is then uploaded to a data collection database from at least some of the one or more target subscriber entities, which is then aggregated and made available for download by the end user.

Abstract: The present disclosure relates to systems, methods and computer programs for managing end user data deletion by communicating a prepare for deletion message to one or more two-step deletion subscriber entities to instruct them to prepare to enact a data deletion request, and communicate a deletion message to the one or more two-step target subscriber entities only after a ready for deletion message is received from each of the one or more two-step deletion subscriber entities.

Abstract: The present disclosure relates to the management of end user privacy controls using a privacy broker system, method, computer program and electronic device for managing end user privacy controls of a plurality of end users across a plurality of end user services. The system is configured to receive from a publisher entity a privacy event relating to an end user of the plurality of end users, determine one or more target subscriber entities and communicate the privacy event to the one or more target subscriber entities.

Abstract: The present disclosure relates to a system, method, computer program and electronic device for managing end user data takeout. A data takeout message is communicated to one or more target subscriber entities to instruct the one or more target subscriber entities to enact a data takeout request relating to an end user. User data relating to the end user is then uploaded to a data collection database from at least some of the one or more target subscriber entities, which is then aggregated and made available for download by the end user.

Abstract: The present disclosure relates to systems, methods and computer programs for managing end user data deletion by communicating a prepare for deletion message to one or more two-step deletion subscriber entities to instruct them to prepare to enact a data deletion request, and communicate a deletion message to the one or more two-step target subscriber entities only after a ready for deletion message is received from each of the one or more two-step deletion subscriber entities.

Abstract: The present disclosure relates to the management of end user privacy controls using a privacy broker system, method, computer program and electronic device for managing end user privacy controls of a plurality of end users across a plurality of end user services. The system is configured to receive from a publisher entity a privacy event relating to an end user of the plurality of end users, determine one or more target subscriber entities and communicate the privacy event to the one or more target subscriber entities.

Abstract: Surfacing relevant and predictively trending digital entities to a user in a content feed is provided. Aspects of a predictive trending system use one or more predictive models, such as neural networks or regression models, to generate predictive trending scores of digital entities (e.g., documents, people, electronic communications, meetings, locations, digital images, digital videos, digital audio, etc.) based on historical scores and context. By taking into account trends and context, the predictive trending system calculates future trending scores of digital entities, and determines which digital entities are both relevant to a given user and likely to be trending around the user and the people in the user's network in the future. The predictive trending system curates the digital entities determined to be relevant and predicted to be trending around the user, and presents the digital entities in a content feed.

Abstract: Surfacing relevant and predictively trending digital entities to a user in a content feed is provided. Aspects of a predictive trending system use one or more predictive models, such as neural networks or regression models, to generate predictive trending scores of digital entities (e.g., documents, people, electronic communications, meetings, locations, digital images, digital videos, digital audio, etc.) based on historical scores and context. By taking into account trends and context, the predictive trending system calculates future trending scores of digital entities, and determines which digital entities are both relevant to a given user and likely to be trending around the user and the people in the user's network in the future. The predictive trending system curates the digital entities determined to be relevant and predicted to be trending around the user, and presents the digital entities in a content feed.