Research On The Selection Algorithm Of Event Organizers In Social Networks

In social networks,the classic problem of maximizing impact is to find a given positive integer number of seed users in the social network.By activating these seed users,the range of influences that maximize expectations can be obtained.The goal of influencing the event organizer to select the problem is to select a species set that not only has the skills or attributes that can organize an event,but also the most influential people to participate in the event.Although the traditional organizer selection problem(Search Influential Event Organizers)has been studied to a certain extent,the existing research has neglected many factors and problems,so the main research results of this paper are:1.In the traditional weighted cascade model(Weighted Cascade Model),the influence of attribute similarity on propagation probability is introduced.In the weight cascading model,the probability that a node is affected by any precursor node is the reciprocal of its indegree,which obviously cannot accurately describe the real The probability of influence.For example,the more the attributes of two adjacent nodes are repeated,the more dense the relationship between the two individuals,and the greater the probability of influence.In order to better measure the similarity of attributes,this paper introduces the Jaccard similarity formula to calculate the impact probability more accurately.2.Add the time factor to the traditional organizer selection problem.The event is performed within a specific time range.Therefore,the selected organizer’s activity time should include the time range of the event operation.After adding the time factor,the impact is maximized.The algorithm also has to make corresponding changes.Because,if the activity time of the node affected by the organizer cannot contain the time when the event occurred,the affected node cannot participate in the event even if it is successfully activated.3.Add multi-channel influencing factors to the organization selection problem.The traditional organizer selection problem is for the propagation of a single network.In real situations,information can be transmitted through multiple networks,considering that information can be used in multiple networks.In the middle of communication,this paper combines the previous studies on the maximization of multi-channel impact,and proposes the selection of organizers based on the multi-channel influence maximization,and gives two solutions.4.Min-Score algorithm is proposed based on the original scoring algorithm.The Min-Score algorithm is proved by theory and experiment with the other two scoring algorithms based on the scoring algorithm.Compared with the smaller time complexity,the experiment finally proves that the Min-Score algorithm outperforms the two algorithms in terms of time compared with the two derivative algorithms based on the pigeon cage principle,and the obtained species set has a larger influence range than the two.Equal to both.