Social network site false fan detection method achieved on basis of network crawler by means of machine learning

Abstract

The invention provides a social network site false fan detection method achieved on the basis of a network crawler by means of machine learning. The method comprises the steps that data of microblog or other social network users is automatically acquired through the web crawler, and a simulation login function is achieved; characteristic fields are selected from the data extracted by the web crawler, and a training sample and a test sample are obtained; a classical SVM algorithm classifier is adopted, multiple groups of data are extracted from the training sample randomly and guided into the classifier, and the classifier conducts machine learning to form a training classification model; the classification model is tested through the test sample, and the optimal cross validation precision is achieved by continuously adjusting setting parameters of the classification model; the microblog or other social network users are detected through the optimal classification model. Accordingly, the false fan detection precision is greatly improved, the computing amount is low, the processing speed is high, the data is not likely to be interfered in the computing process, and the method is particularly suitable for mass data processing.

Description

technical field [0001] The invention relates to a method for detecting false fans, in particular to a method for detecting false fans of social networking sites based on web crawlers and machine learning, and belongs to the technical field of data processing. Background technique [0002] People all over the world now rely on online social networks (OSNs) to share knowledge, opinions and experiences, seek information and resources, and expand personal connections, but in social networking sites, users' actions are not necessarily true. Due to the large number of users using online social networks, social networking sites have also become platforms that are exploited and profited in various forms while providing value to ordinary users. For example: a large amount of user information on social networking sites is what advertisers and fraudsters hope to obtain; some people who want to increase the social participation of their accounts will use robots to like or repost; Popul...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that there are a large number of false fans in the existing microblog or other social networks. The existing detection and identification methods have poor accuracy, large amount of calculation, complex calculation, slow processing speed, and isolated distribution points Or record wrong data is sensitive, and the data is easily disturbed during the calculation process. Now we provide a small calculation, fast processing speed, data is not easy to be disturbed during the calculation process, and the detection accuracy of false fans. A high-level method for detecting fake followers on social networking sites based on web crawlers and machine learning

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