A computer-implemented method, computer program product, and computer system for selecting strangers for information spreading on a social network. For the strangers who are users of the social network and not related to each other, information spreading probabilities based on features, information reach, and information spreading probabilities based on a wait time are computed. Fitness scores of the strangers are computed; the fitness scores are a function of the information spreading probabilities, the information reach, and the information spreading probabilities. The strangers are ranked, based on the fitness scores, in a sorted set. One or more of the strangers for the information spreading are selected from the sorted set. The one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, and the interval satisfies an optimization objective of maximizing unit information reach per stranger.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for selecting strangers for information spreading on a social network, the method comprising: training statistical models with history data of the information spreading of strangers on the social network, the strangers on the social network being not known to a requester who requests the strangers on the social network to conduct the information spreading; computing information spreading probabilities based on features of the strangers on the social network; computing information reach of the strangers on the social network; computing information spreading probabilities based on a wait time of the strangers on the social network, the wait time being a period of time for the strangers on the social network to initiate information spreading in response to being requested by the requester; computing fitness scores of the strangers on the social network, the fitness scores being a function of: the information spreading probabilities based on features, the information reach, and the information spreading probabilities based on the wait time; ranking the strangers on the social network in a sorted set, based on the fitness scores; selecting one or more of the strangers for the information spreading from the sorted set; and wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing unit information reach per stranger, the unit information reach per stranger is a sum of followers of strangers conducting the information spreading normalized by a number of strangers being asked to conduct the information spreading. 2. The method of claim 1, wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing an information spreading rate, the information spreading rate is a ratio of a number of strangers conducting the information spreading to a number of strangers being asked to conduct the information spreading. 3. The method of claim 1, wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of minimizing time for the information spreading within a confidence probability. 4. The method of claim 1, wherein the one or more of the strangers for the information spreading are selected by choosing strangers with highest fitness scores. 5. The method of claim 1, the method further comprising: determining a first set for subset selection, the first set including a portion of the strangers on the social network; ranking the first set based on the fitness scores; computing a value of an optimization objective function for each of intervals in the first set; determining an interval in the first set, the interval in the first set having an optimal value of the optimization objective function; determining a second set for selecting the one or more of the strangers for the information spreading; ranking the second set based on the fitness score; and determining an interval in the second set, the interval in the second set being defined by the interval in the first set, based on percentiles. 6. The method of claim 1, wherein the features are selected from the group consisting of profile features, social network features, personality features, activity features, past information spreading features, and readiness features, wherein the profile features are extracted form profiles of the strangers on the social network, the social network features indicate socialness the strangers on the social network, the personal features include information drawn from analyzing personality of the strangers on the social network, the activity features indicate how active the strangers on the social network are, the past information spreading features indicate quantity and rate of information spreading done by the strangers on the social network, and wherein the readiness features include information spreading likelihood in a day, information spreading likelihood in a hour, information spreading steadiness, and information spreading inactivity. 7. A computer program product for selecting strangers for information spreading on a social network, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a processor to: train statistical models with history data of the information spreading of strangers on the social network, the strangers on the social network being not known to a requester who requests the strangers on the social network to conduct the information spreading; compute information spreading probabilities based on features of the strangers on the social network; compute information reach of the strangers on the social network; compute information spreading probabilities based on a wait time of the strangers on the social network, the wait time being a period of time for the strangers on the social network to initiate information spreading in response to being requested by the requester; compute fitness scores of the strangers on the social network, the fitness scores being a function of the information spreading probabilities based on features, the information reach, and the information spreading probabilities based on the wait time; rank the strangers on the social network in a sorted set, based on the fitness scores; select one or more of the strangers for the information spreading from the sorted set; and wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing unit information reach per stranger, the unit information reach per stranger is a sum of followers of strangers conducting the information spreading normalized by a number of strangers being asked to conduct the information spreading. 8. The computer program product of claim 7, wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing an information spreading rate, the information spreading rate is a ratio of a number of strangers conducting the information spreading to a number of strangers being asked to conduct the information spreading. 9. The computer program product of claim 7, wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of minimizing time for the information spreading within a confidence probability. 10. The computer program product of claim 7, wherein the one or more of the strangers for the information spreading are selected by choosing strangers with highest fitness scores. 11. The computer program product of claim 7, the computer program product further comprising the program code executable by the processor to: determine a first set for subset selection, the first set including a portion of the strangers on the social network; rank the first set based on the fitness scores; compute a value of an optimization objective function for each of intervals in the first set; determine an interval in the first set, the interval in the first set having an optimal value of the optimization objective function; determine a second set for selecting the one or more of the strangers for the information spreading; rank the second set based on the fitness score; and program instructions to determine an interval in the second set, the interval in the second set being defined by the interval in the first set, based on percentiles. 12. The computer program product of claim 7, wherein the features are selected from the group consisting of profile features, social network features, personality features, activity features, past information spreading features, and readiness features, wherein the profile features are extracted form profiles of the strangers on the social network, the social network features indicate socialness the strangers on the social network, the personal features include information drawn from analyzing personality of the strangers on the social network, the activity features indicate how active the strangers on the social network are, the past information spreading features indicate quantity and rate of information spreading done by the strangers on the social network, and wherein the readiness features include information spreading likelihood in a day, information spreading likelihood in a hour, information spreading steadiness, and information spreading inactivity. 13. A computer system for selecting strangers for information spreading on a social network, the computer system comprising: one or more processors, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more computer-readable tangible storage devices for execution by at least one of the one or more processors, the program instructions executable to: train statistical models with history data of the information spreading of strangers on the social network, the strangers on the social network being not known to a requester who requests the strangers on the social network to conduct the information spreading; compute information spreading probabilities based on features of the strangers on the social network; compute information reach of the strangers on the social network; compute information spreading probabilities based on a wait time of the strangers on the social network, the wait time being a period of time for the strangers on the social network to initiate information spreading in response to being requested by the requester; compute fitness scores of the strangers on the social network, the fitness scores being a function of the information spreading probabilities based on features, the information reach, and the information spreading probabilities based on the wait time; rank the strangers on the social network in a sorted set, based on the fitness scores; select one or more of the strangers for the information spreading from the sorted set; and wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing unit information reach per stranger, the unit information reach per stranger is a sum of followers of strangers conducting the information spreading normalized by a number of strangers being asked to conduct the information spreading. 14. The computer system of claim 13, wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of maximizing an information spreading rate, the information spreading rate is a ratio of a number of strangers conducting the information spreading to a number of strangers being asked to conduct the information spreading. 15. The computer system of claim 13, wherein the one or more of the strangers for the information spreading are selected by determining an interval in the sorted set, the interval satisfies an optimization objective of minimizing time for the information spreading within a confidence probability. 16. The computer system of claim 13, wherein the one or more of the strangers for the information spreading are selected by choosing strangers with highest fitness scores. 17. The computer system of claim 13, further comprising program instructions executable to: determine a first set for subset selection, the first set including a portion of the strangers on the social network; rank the first set based on the fitness scores; compute a value of an optimization objective function for each of intervals in the first set; determine an interval in the first set, the interval in the first set having an optimal value of the optimization objective function; determine a second set for selecting the one or more of the strangers for the information spreading; rank the second set based on the fitness score; and determine an interval in the second set, the interval in the second set being defined by the interval in the first set, based on percentiles. 18. The computer system of claim 13, wherein the features are selected from the group consisting of profile features, social network features, personality features, activity features, past information spreading features, and readiness features, wherein the profile features are extracted form profiles of the strangers on the social network, the social network features indicate socialness the strangers on the social network, the personal features include information drawn from analyzing personality of the strangers on the social network, the activity features indicate how active the strangers on the social network are, the past information spreading features indicate quantity and rate of information spreading done by the strangers on the social network, and wherein the readiness features include information spreading likelihood in a day, information spreading likelihood in a hour, information spreading steadiness, and information spreading inactivity.