Social media graph representation model-based social risk event extraction method

A technology for social media and event extraction, used in special data processing applications, instruments, unstructured text data retrieval, etc.

Inactive Publication Date: 2016-09-21
杭州量知数据科技有限公司
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

The above-mentioned characteristics have brought many new challenges to the extraction of social risk events based on social media.

Method used

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  • Social media graph representation model-based social risk event extraction method
  • Social media graph representation model-based social risk event extraction method
  • Social media graph representation model-based social risk event extraction method

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Embodiment

[0074] Since there is no standard measure in the field of incident detection on social media platforms. The experiment adopts the real data on the Sina Weibo platform to detect the method of the present invention. When crawling microblogs, use a keyword-based search method to input disaster center keywords into the microblog big data, and select the latest published microblogs from the returned data. Using "Ebola" as the central word of the disaster, a total of 13,538 microblogs were obtained through the Sina API, and their release dates were between January 1, 2014 and January 30, 2014. After cleaning the microblog data, a total of 10452 microblogs are left. These Weibo messages are those that have attracted more attention under the topic of Ebola. 2) The system firstly performs pre-cleaning work such as original forwarding judgment, noise judgment, etc. on Weibo. For original microblogs, the criterion for noise judgment is that when the number of original words is less th...

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Abstract

The invention discloses a social media graph representation model-based social risk event extraction method. The method comprises the following steps of 1) modeling an event by adopting an HCCG model, defining an entity relationship generation rule, describing event attributes, and performing multi-granularity extraction on the event by utilizing word-level and stream-level contexts; 2) performing similarity calculation by utilizing an information quantity ratio of a maximum common subgraph and a minimum common hypergraph according to an HCCG graph of the extracted event; 3) performing incremental clustering on HCCG through context information of social media, and gradually highlighting event elements of news in a clustering process; and 4) performing event judgment through an HCCG model-based clustering result, and judging whether the clustering result is a true event or not. According to the method, dispersed social media information can be effectively collected; intermediate and final event detection results are expressed in a multi-granularity manner visually by using an entity relationship model; and compared with a conventional social media event extraction method, the social media graph representation model-based social risk event extraction method has better generalization application capability and higher accuracy.

Description

technical field [0001] The invention relates to the field of information query and retrieval, in particular to a method for extracting social risk events based on a social media graph representation model. Background technique [0002] With the rapid increase in the speed of news dissemination in the information society, the influence of public opinion on social risk events has become increasingly prominent, and there are more and more extensive application requirements for real-time monitoring and social analysis of social risk events. In the network environment, the real world and the virtual world have the convenience of mapping each other, and users continue to gather in large numbers on social networking platforms. The real-time data of social media reflects the development trend of events in the real world from the side, which is of great value for the extraction and analysis of social risk events. [0003] The existing research on event perception technology based on...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/35
Inventor 凌立刚朱海鹏
Owner 杭州量知数据科技有限公司
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