Abstract: A popular highlight may be presented to a user who wishes to make the popular highlight a personal user highlight. Upon activation of a control, a personal user highlight is generated from the popular highlight. The user may then manipulate the resulting personal user highlight as they would any other user highlight.

Abstract: Digital items may be lent from one user to another. A lending system may facilitate matching users that have a digital item to lend with users that wish to borrow a digital item. Each user may have a reputation associated with his or her lending behavior that is represented as a lending metric. The lending metric may show whether a given user is primarily a lender or borrower of digital items. Heavy borrowers that do not engage in commensurate lending may be penalized. Multiple users that lend and borrow digital items from one another may be connected in a social network. The nature of a relationship in the social network may and the lending metrics of users are factors used to make lending decisions.

Abstract: While consuming digital content, a user may highlight a portion considered relevant or of interest. When this user highlight corresponds with an existing highlight created by other users in a community of users, a highlight match indicator is presented to the user. This indicator provides a positive reinforcement to the user that they have serendipitously highlighted a portion which others in the community of users found relevant.

Abstract: Communications from digital content consumers may be entered on reader devices as social media posts. Rather than specifying a particular recipient, a consumer may enter a reserved keyword, such as @author, as the recipient. Upon submission, this keyword is automatically replaced with the recipient identifier, such as with the user identifier of the actual author of the currently rendered content item.

Abstract: A popular highlight may be presented to a user who wishes to make the popular highlight a personal user highlight. Upon activation of a control, a personal user highlight is generated from the popular highlight. The user may then manipulate the resulting personal user highlight as they would any other user highlight.

Abstract: A popular highlight may be presented to a user who wishes to make the popular highlight a personal user highlight. Upon activation of a control, a personal user highlight is generated from the popular highlight. The user may then manipulate the resulting personal user highlight as they would any other user highlight.

Abstract: Digital items may be lent from one user to another. A lending system may facilitate matching users that have a digital item to lend with users that wish to borrow a digital item. Each user may have a reputation associated with his or her lending behavior that is represented as a lending metric. The lending metric may show whether a given user is primarily a lender or borrower of digital items. Heavy borrowers that do not engage in commensurate lending may be penalized. Multiple users that lend and borrow digital items from one another may be connected in a social network. The nature of a relationship in the social network may and the lending metrics of users are factors used to make lending decisions.

Abstract: Digital items may be lent from one user to another. A lending system may facilitate matching users that have a digital item to lend with users that wish to borrow a digital item. Each user may have a reputation associated with his or her lending behavior that is represented as a lending metric. The lending metric may show whether a given user is primarily a lender or borrower of digital items. Heavy borrowers that do not engage in commensurate lending may be penalized. Multiple users that lend and borrow digital items from one another may be connected in a social network. The nature of a relationship in the social network may and the lending metrics of users are factors used to make lending decisions.

Abstract: Digital items may be lent from one user to another. A lending system may facilitate matching users that have a digital item to lend with users that wish to borrow a digital item. Each user may have a reputation associated with his or her lending behavior that is represented as a lending metric. The lending metric may show whether a given user is primarily a lender or borrower of digital items. Heavy borrowers that do not engage in commensurate lending may be penalized. Multiple users that lend and borrow digital items from one another may be connected in a social network. The nature of a relationship in the social network may and the lending metrics of users are factors used to make lending decisions.

Abstract: Digital items may be lent from one user to another. A lending system may facilitate matching users that have a digital item to lend with users that wish to borrow a digital item. Each user may have a reputation associated with his or her lending behavior that is represented as a lending metric. The lending metric may show whether a given user is primarily a lender or borrower of digital items. Heavy borrowers that do not engage in commensurate lending may be penalized. Multiple users that lend and borrow digital items from one another may be connected in a social network. The nature of a relationship in the social network may and the lending metrics of users are factors used to make lending decisions.

Abstract: Digital items may be lent from one user to another. A lending system may facilitate matching users that have a digital item to lend with users that wish to borrow a digital item. Each user may have a reputation associated with his or her lending behavior that is represented as a lending metric. The lending metric may show whether a given user is primarily a lender or borrower of digital items. Heavy borrowers that do not engage in commensurate lending may be penalized. Multiple users that lend and borrow digital items from one another may be connected in a social network. The nature of a relationship in the social network may and the lending metrics of users are factors used to make lending decisions.