Method for sensing network sudden hotspots based on perception maximization
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A hotspot and network technology, applied in the field of sudden hotspot perception in social networks, can solve problems such as no sensor
Active Publication Date: 2018-06-12
北京东方科诺科技发展有限公司
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However, there is currently no method for emergency perception from the perspective of perception, and there is no standard definition to evaluate the pros and cons of perceptrons, and how to better select perceptrons
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Embodiment 1
[0045] This embodiment provides a social network burst hotspot sensing method based on social perception maximization. The present invention defines this sensing process based on special perceptrons as social perception maximization, and applies the social perception maximization calculation to burst hot spot perception.
[0046] Specific perceptual processes such as figure 1 Shown:
[0047] Step 1. Collect microblogs related to emergencies that have occurred in social networks in history. Events are defined in the form of keywords. Search the entire network to record the publishers, release times, and microblogs of the searched microblogs. mid, microblog type, source microblog mid (root_mid), number of fans, especially for the retrieved original microblog, crawl all subsequent reposted microblogs together;
[0048] Step 2. Define the concept of emergency perception and evaluation index system. All participants in an event are regarded as aware of the emergency. For each eve...
Embodiment 2
[0067] This embodiment provides a method for sensing sudden hotspots in the network based on perception maximization, and the specific steps are as follows:
[0068] S1: Collect historical emergencies and corresponding release information in the network, define the occurrence time of a historical emergency as the earliest time of all information releases under this historical emergency, and use it as the benchmark time,
[0069] S2: Define the time when the user participated in the historical emergency event as the difference between the time when the user releases information and the reference time, and define the evaluation index for perceptually released information according to the perception maximization;
[0070] S3: Use the information released by all users who participated in the historical emergency to train a set of perceptrons, which is recorded as a set of perceptrons;
[0071] S4: Obtain the published information in the perceptron set in real time, construct a cla...
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Abstract
The invention provides a method for sensing network sudden hotspots based on perception maximization. The method comprises the following steps: collecting historical sudden events in a network and corresponding post messages at first, defining reference time and difference between time of post messages of participates and the reference time, defining evaluation indexes for sensing the post messages according to perception maximization, and training a perceptron set; aggregating the post messages acquired in real time in the perceptron set into different clusters on the basis of a text similarity detecting method, wherein each cluster is regarded as a potential hotspot; and detecting every potential hotspot, and when the observation amount of the post messages corresponding to a certain potential hotspot at a certain time is not smaller than a threshold value, regarding that the potential hotspots burst out. All user nodes in a social network are regarded as the perceptron according tocommunication characteristics of information in the social network, all information which circulates in the social network is regarded as perceptual information, and the information which circulates in the social network, namely social perception, is sensed through the perceptron which monitors the social network.
Description
technical field [0001] The invention relates to the technical field of machine learning, in particular to a social network sudden hotspot sensing method based on social sensing maximization. Background technique [0002] In recent years, with the extensive penetration and innovative development of Internet technology, social media represented by Weibo has been widely and deeply integrated into every aspect of people's lives. Social media has become an important platform for people to find information, express opinions and communicate. Research based on Twitter shows that the properties of social media are closer to event networks. Early perception of sudden hot spots and timely targeted measures can gain huge social and economic value, such as politically sensitive event monitoring, news hotspot discovery, business public opinion analysis, stock market public opinion fluctuations, etc. However, due to the diversity of information sources in social networks, the suddenness ...
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