A method of importing and visualizing microblog user forwarding relationship based on graph database
A database and microblog technology, which is applied in the analysis field of microblog public opinion big data, can solve problems such as difficult to obtain forwarding order, random forwarding relationship, discontinuity, etc., and achieve the effect of high data import efficiency, easy modification, and broad application prospects
Active Publication Date: 2022-02-15
JIANGSU POLICE INST
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Problems solved by technology
When collecting social platform forwarding relationship data, in order to improve crawler performance, multi-threaded crawler technology needs to be used. However, the forwarding relationships crawled by multi-threaded crawlers are random, chaotic, and discontinuous. There is a problem when Weibo forwards the relationship network
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[0031] The code of the present invention realizes the node creation and modification functions facing the mutual connection of nodes. The code divides the nodes into the following situations according to the contents of the content attribute of the nodes: original nodes, one-layer forwarding nodes and multi-layer forwarding nodes, that is, nodes with more than one layer of forwarding layers.
[0032] First of all, limited by the crawler algorithm, the imported nodes have several prerequisites:
[0033] 1. Since the crawler is multi-threaded crawling, the order of crawling nodes is unknown. For example, the nodes of the advanced database are most likely to be forwarded late, and the nodes of the late database are most likely to be forwarded first, except for the first original node.
[0034] 2. Due to the limitation of the function of the search node program, only one attribute can be passed. Here we choose the user name as the index of the search node.
[0035] We use a list...
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The invention relates to a graph database-based microblog user forwarding relationship import and visualization method, using multi-threaded crawlers to obtain source microblogs and all multi-layered forwarding messages, constructing a real forwarding relationship network and displaying it in the graph database . The present invention solves the problem that the sequence of nodes crawled by multi-threaded crawlers is random, chaotic, and discontinuous when constructing a forwarding relationship network, and can construct an overall forwarding relationship network when only part of the forwarding nodes are known, and follow-up The number of crawlers fetching nodes increases and is continuously improved. Functions such as node addition, node deduplication, node content and forwarding relationship update between nodes are realized; and when the crawler system is uninterrupted for 24 hours, the node and its forwarding relationship can be imported into the graph database in real time when there is a new forwarding message. It has the advantages of high import efficiency and good scalability, and can run on different platforms, so it has broad application prospects.
Description
technical field [0001] The invention relates to the analysis field of microblog public opinion big data, in particular to a method for importing and visualizing microblog user forwarding relationships based on a Neo4j graph database. Background technique [0002] With the advent of the self-media era, social networking services (Social Networking Service, SNS) have been integrated into the daily life of the public. Individuals upload their own information to various social media platforms such as Weibo, forums, blogs, online communities, WeChat, QQ and other instant messaging software, social networking sites (Facebook, Twitter), etc., and manage themselves through social platforms. social circle, resulting in a large amount of personal information being disclosed on the Internet. These information contain a lot of useful information, providing countless valuable information for public security intelligence information work. The focus of public security intelligence work i...
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IPC IPC(8): G06F16/901G06F16/904
Inventor 王群夏玲玲张亮印杰梁广俊胡春涛
Owner JIANGSU POLICE INST