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A Rumor Identification Method Based on Naive Bayesian Model

A Bayesian model and recognition method technology, applied in character and pattern recognition, data processing applications, unstructured text data retrieval, etc. The effect of reducing the likelihood

Active Publication Date: 2021-06-18
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

However, many studies considering the characteristics of rumor propagation simplifies rumor propagation into a single process, ignoring that different rumors may be created or reposted by the same group of users, which means that in different rumor forwarding networks, some players who participate in multiple processes at the same time can be found. active users who forwarded the rumor

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  • A Rumor Identification Method Based on Naive Bayesian Model
  • A Rumor Identification Method Based on Naive Bayesian Model
  • A Rumor Identification Method Based on Naive Bayesian Model

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Embodiment Construction

[0054] The present invention provides a method for identifying rumors based on a naive Bayesian model. In order to further clarify its technical means and effects, the technical method of the present invention will be described in detail below in conjunction with specific examples of rumor identification.

[0055] A rumor recognition method based on the naive Bayesian model of the present invention, such as figure 2 As shown, its specific implementation steps are as follows:

[0056] Step 1: Collect 1,863 rumors and 2,000 pieces of Sina Weibo data as training data according to the required information such as message content, creator ID number, creation time, forwarder ID number, forwarding time, and type label. At the same time, classify each message data collected, that is, mark it as fact or rumor.

[0057] The nodes in the network are defined as users participating in message forwarding, and the connection edge is defined as the forwarding relationship of the message, an...

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Abstract

The present invention provides a rumor recognition method based on Naive Bayesian, the steps are as follows: 1. Collect sample data and build a message forwarding network; 2. Statistically identify active users of the rumor forwarding network; 3. Determine the conditional probability calculation formula for rumor recognition Through the above steps, the present invention comprehensively considers the active user nodes participating in multiple rumor forwarding, based on the Naive Bayesian model, while reducing the storage space requirement, the recognition accuracy and calculation efficiency are improved, and the rumor recognition in the social network is solved. The problem has the value of popularization and application.

Description

technical field [0001] The invention proposes a rumor recognition method based on a naive Bayesian model, which assists in the identification of false news and false statements such as rumors according to the characteristics of active users spreading rumors in social networks, and belongs to the interdisciplinary field of machine learning and network science. Background technique [0002] With the rapid development of the Internet, the popularity of social network media such as Weibo and WeChat is also increasing. According to the 2018 Q1 quarterly financial report released by Sina Weibo, as of March 2018, the monthly active users of Weibo have exceeded 400 million; according to media reports, as of 2018, the total number of WeChat users worldwide exceeded 1 billion. When news spreads on the Internet, it is often mixed with various real news and false rumors. Because news has the characteristics of fast dissemination and wide influence on the Internet, rumors have more and ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06K9/62G06Q50/00
CPCG06Q50/01G06F18/24155
Inventor 李大庆钟季龙
Owner BEIHANG UNIV