Abstract: An online system predicts whether a location will experience a threshold increase in traffic over the location's historical average amount of traffic. To predict a future deviation over historical traffic, the online system identifies events within a threshold distance of the location and determines an average number of indications that users will attend events within a threshold radius of the location during a prior time interval. The online system determines a total number of indications that users will attend future events within the threshold distance of the location, disregarding locations associated with less than a threshold number of future events and future events for which the online system received less than a threshold number of indications that users will attend, and determines a ratio of the total number of indications to the average number of indications that users will attend received for the prior events during the time interval.

Abstract: According to examples, a system for coordinating and managing potential volunteers (i.e., volunteer blood donors) is disclosed. The system may include may include a processor and a memory storing instructions. The processor, when executing the instructions, may cause the system to receive partner data from one or more of a local partner and a global partner and determine a donation need based on the partner data. The processor may also cause the system to identify a pool of volunteer donors based on the donation need, build an online campaign to increase the pool of volunteer donors, and coordinate the pool of volunteer donors with the local or global partners based at least in part on a machine learning (ML) technique.

Abstract: Information associated with a content provider within an online system can be acquired. The information can include data about interactions performed by the content provider. A machine learning model can be applied to the information. A metric indicating a predicted likelihood that the content provider will perform an action related to a content item when the content provider is presented with a coupon for the content item can be determined. It can be determined that the metric satisfies specified threshold criteria. An opportunity to present the coupon to the content provider can be detected. The coupon and a communication can be provided to the content provider at the opportunity. The communication can encourage the content provider to perform the action related to the content item. An instruction to execute the action can be acquired from the content provider. The content item can be provided to users of the online system.

Abstract: An online system predicts whether a location will experience a threshold increase in traffic over the location's historical average amount of traffic. To predict a future deviation over historical traffic, the online system identifies events within a threshold distance of the location and determines an average number of indications that users will attend events within a threshold radius of the location during a prior time interval. The online system determines a total number of indications that users will attend future events within the threshold distance of the location, disregarding locations associated with less than a threshold number of future events and future events for which the online system received less than a threshold number of indications that users will attend, and determines a ratio of the total number of indications to the average number of indications that users will attend received for the prior events during the time interval.

Abstract: Information associated with a content provider within an online system can be acquired. The information can include data about interactions performed by the content provider. A machine learning model can be applied to the information. A metric indicating a predicted likelihood that the content provider will perform an action related to a content item when the content provider is presented with a coupon for the content item can be determined. It can be determined that the metric satisfies specified threshold criteria. An opportunity to present the coupon to the content provider can be detected. The coupon and a communication can be provided to the content provider at the opportunity. The communication can encourage the content provider to perform the action related to the content item. An instruction to execute the action can be acquired from the content provider. The content item can be provided to users of the online system.