Abstract: In one embodiment, a predictive contextual transaction scoring system receives transaction review data associated with person-to-person transactions from a marketplace, the transaction review data including feedback information relating to the person-to-person transaction. The system identifies contextual characteristics of the person-to-person transactions by analyzing the feedback information related to the person-to-person transactions. The system pairs a first party requesting a service to a second party providing the requested service by matching a contextual characteristic of the first party to a contextual characteristic of the second party. The system also predicts a transaction score for a new person-to-person transaction involving the first party and the second party, and provides the predicted transaction score to the marketplace to facilitate pairing of the first party requesting the service.

Abstract: In one embodiment, a predictive contextual transaction scoring system receives transaction review data associated with person-to-person transactions from a marketplace, the transaction review data including feedback information relating to the person-to-person transaction. The system identifies contextual characteristics of the person-to-person transactions by analyzing the feedback information related to the person-to-person transactions. The system pairs a first party requesting a service to a second party providing the requested service by matching a contextual characteristic of the first party to a contextual characteristic of the second party. The system also predicts a transaction score for a new person-to-person transaction involving the first party and the second party, and provides the predicted transaction score to the marketplace to facilitate pairing of the first party requesting the service.

Abstract: In one embodiment, a predictive contextual transaction scoring system receives transaction review data associated with person-to-person transactions from a marketplace, the transaction review data including feedback information relating to the person-to-person transaction. The system identifies contextual characteristics of the person-to-person transactions by analyzing the feedback information related to the person-to-person transactions. The system pairs a first party requesting a service to a second party providing the requested service by matching a contextual characteristic of the first party to a contextual characteristic of the second party. The system also predicts a transaction score for a new person-to-person transaction involving the first party and the second party, and provides the predicted transaction score to the marketplace to facilitate pairing of the first party requesting the service.

Abstract: In one embodiment, a predictive contextual transaction scoring system receives transaction review data associated with person-to-person transactions from a marketplace, the transaction review data including feedback information relating to the person-to-person transaction. The system identifies contextual characteristics of the person-to-person transactions by analyzing the feedback information related to the person-to-person transactions. The system pairs a first party requesting a service to a second party providing the requested service by matching a contextual characteristic of the first party to a contextual characteristic of the second party. The system also predicts a transaction score for a new person-to-person transaction involving the first party and the second party, and provides the predicted transaction score to the marketplace to facilitate pairing of the first party requesting the service.

Abstract: A trust platform receives transaction review values from a plurality of marketplace providers, each transaction review value associated with a person-to-person transaction. The platform weighs each transaction review value to generate a weighted transaction review value based on a characteristic of the transaction. A baseline individual trust score is generated based on an aggregation of the weighted transaction review values which reflects a “trust” attributable to a user. The trust platform is also configured to adjust new transaction review values based on the baseline individual trust score to render such review more accurate.

Abstract: In one embodiment, a predictive contextual transaction scoring system receives transaction review data associated with person-to-person transactions from a marketplace, the transaction review data including feedback information relating to the person-to-person transaction. The system identifies contextual characteristics of the person-to-person transactions by analyzing the feedback information related to the person-to-person transactions. The system pairs a first party requesting a service to a second party providing the requested service by matching a contextual characteristic of the first party to a contextual characteristic of the second party. The system also predicts a transaction score for a new person-to-person transaction involving the first party and the second party, and provides the predicted transaction score to the marketplace to facilitate pairing of the first party requesting the service.

Abstract: A trust platform receives transaction review values from a plurality of marketplace providers, each transaction review value associated with a person-to-person transaction. The platform weighs each transaction review value to generate a weighted transaction review value based on a characteristic of the transaction. A baseline individual trust score is generated based on an aggregation of the weighted transaction review values which reflects a “trust” attributable to a user. The trust platform is also configured to adjust new transaction review values based on the baseline individual trust score to render such review more accurate.

Abstract: A trust platform receives transaction review values from a plurality of marketplace providers, each transaction review value associated with a person-to-person transaction. The platform weighs each transaction review value to generate a weighted transaction review value based on a characteristic of the transaction. A baseline individual trust score is generated based on an aggregation of the weighted transaction review values which reflects a “trust” attributable to a user. The trust platform is also configured to adjust new transaction review values based on the baseline individual trust score to render such review more accurate.