Crowdsourcing Service Node Selection Algorithm Based on Social Network Ability Discovery

To solve the problem of inaccurate crowdsourcing service node selection caused by the unsuccessful information update of the unregistered potential workers or the registered workers in the social network crowdsourcing system, a network crowdsourcing service node selection algorithm is proposed based on social relationship ability discovery. The social relationship cognition is introduced, and the crowdsourcing task publishers or recipients are supposed to be the tasks release centers. Following the relevant theories of social networks, the themes of crowdsourcing tasks and the corresponding keywords are refined, and the key words in the interaction information among friends are analyzed. The number of key words, combined with the number of occurrences of the corresponding keywords in their friends circles, is comprehensively and weightedly calculated to quantify the size of a friend ability to generate a friend ability matrix, thus their social relationships are reconstructed. When a crowdsourcing task is generated or arrives, considering the quality factor of the task completion, the honesty index of the node, the matching degree, the task is selectively forwarded to the friend who meets the ability requirement. Simulation experiment of WeChat interaction shows that the proposed algorithm can better perform ability discovery, select appropriate task receiver, and save about 64.5% of time than random distribution to achieve fast and accurate task publishing and data collection. © 2019, Editorial Office of Journal of Xi'an Jiaotong University. All right reserved.