社交网络用户影响力的模糊综合评价

社交网络平台信息传播迅速，为了有效地进行舆情预警，定量地评估用户在消息传播网络中重要性，将模糊综合评价方法引入用户影响力建模问题中. 通过对用户在社交平台上的行为分析，构造了包含用户活跃粉丝数以及平均转发数等五项指标在内的评价体系. 并针对传统的模糊综合评价算法在应用于计算评价指标权重方面的缺陷与不足，提出改进模糊合成算子的方法构建用户影响力评估模型. 利用新浪微博社交平台上的真实数据，结合对比实验和实际评估，改进的模糊合成算子能根据需求调整权重对评价结果的影响，同时该方法能较准确地反应社交网络中用户的实际影响力.

Fuzzy Comprehensive Evaluation of Social Network User's Influence

Information spreads quickly on social networking platform. In order to effectively carry out public opinion early warning and quantitatively evaluate the importance of users in social network, the fuzzy comprehensive evaluation method is introduced into the user influence modeling problem. Based on the analysis of the behavioral analysis of the user''s behavior on the social platform, the evaluation system including five indicators, such as user active number of fans and average forwarding number is constructed. A new fuzzy synthesis operator is proposed to construct the user influence evaluation model based on the shortcomings of the traditional fuzzy comprehensive evaluation algorithm in calculating the weight of the evaluation index. This operator can adjust the weight of the impact on the evaluation results according to the demand. Using the real data of Sina microblogging social platform, combined with comparative experiments and practical assessment, the method can more accurately reflect the actual impact of the user in the social network.