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CN-121979934-A - Propagation influence dynamic visualization method supporting multidimensional drill-down and real-time interaction

CN121979934ACN 121979934 ACN121979934 ACN 121979934ACN-121979934-A

Abstract

The invention discloses a transmission influence dynamic visualization method supporting multidimensional drill-down and real-time interaction, which comprises the following steps of S1, accessing multi-source original transmission event data through a transmission influence data adapter and converting the multi-source original transmission event data into structured data carrying multidimensional labels, S2, responding to user visual view interaction operation, analyzing context information by an interaction intention analyzer to generate a drill-down instruction containing a target dimension identifier, S3, dynamically generating a data query statement and a visual configuration option required by next-level analysis by a drill-down path manager according to the instruction and a predefined metadata rule, and S4, submitting the configuration option to an Echarts-based visual instance, and realizing view difference comparison and local update by utilizing a virtual option tree Diff algorithm of the configuration option to realize seamless drill-down rendering. The method can automatically analyze the user interaction intention and generate a drill-down path, improves analysis flexibility and depth, optimizes an Echarts rendering mechanism, can efficiently process massive real-time data update and complex view linkage, and ensures response speed and fluency.

Inventors

  • QIN XUAN
  • WEI LU
  • JIANG YANBING
  • ZHENG DEJUN

Assignees

  • 浙江传媒学院

Dates

Publication Date
20260505
Application Date
20260126

Claims (8)

  1. 1. The method for dynamically visualizing the propagation influence supporting multidimensional drill-down and real-time interaction is characterized by comprising the following steps of: S1, accessing original propagation event data from a multi-source data stream through a propagation influence data adapter, and converting the original propagation event data into structured data carrying a multi-dimensional tag; S2, responding to interactive operation of a user on a visual view, and dynamically analyzing the context information of the interactive operation through an interactive intention analyzer to generate a drill-down instruction containing a target dimension identifier; s3, dynamically generating data query sentences and visual configuration options required by the analysis view of the next level through a drill-down path manager according to the drill-down instruction and a predefined metadata rule; And S4, submitting the visual configuration options to a visual instance based on Echarts, and performing difference comparison and local updating on the views by using a virtual option tree Diff algorithm of the Echarts to realize seamless drill-down rendering.
  2. 2. The method for dynamically visualizing propagation influence in support of multidimensional drill-down and real-time interaction according to claim 1, wherein in step S1, the propagation influence data adapter is provided with a built-in hierarchical data model for organizing unstructured data into an Echarts standard dataset format, and the multidimensional label comprises at least one of a geographic hierarchy, a timestamp, a media type and an emotion polarity.
  3. 3. The method for dynamically visualizing propagation influence in support of multidimensional drill-down and real-time interactions according to claim 1, wherein in step S2, said interaction intention analyzer analyzes a target dimension identifier according to a user operation context and a global screening condition, and transmits the target dimension identifier to a drill-down path manager.
  4. 4. The method for dynamically visualizing propagation influence in support of multi-dimensional drill-down and real-time interactions of claim 1, wherein the interactive operation comprises clicking on a map area, selecting a time range, or swiping a data point in a trend graph, and wherein the context information comprises a dimension value associated with a current interactive object and a global filtering condition.
  5. 5. The method for dynamically visualizing propagation impact in support of multidimensional drill-down and real-time interactions of claim 1, wherein the drill-down path manager dynamically combines to generate new echorts configuration options according to predefined drill-down rules and triggers view update by a char. Setoption () method.
  6. 6. The method for dynamically visualizing propagation influence in support of multidimensional drill-down and real-time interaction according to claim 1, wherein the visual view comprises at least one geographical hierarchy drill-down map constructed based on the echartis custom series, and the graphic elements of the geographical hierarchy drill-down map are determined by dimension identifiers Fu Jiangbang in the data model.
  7. 7. The method for dynamically visualizing propagation influence in support of multi-dimensional drill-down and real-time interactions of claim 1, further comprising the step of constructing a high-performance rendering pipeline: The method comprises the steps that raw data are aggregated and preprocessed through a real-time computing engine; Pushing the processed data to the corresponding Echarts instance according to the current state of the visual component as required; Monitoring data volume and interaction complexity, and dynamically selecting an enabling large mode for different Echarts examples to sample data or selecting an SVG rendering mode.
  8. 8. The method for dynamically visualizing propagation influence in support of multi-dimensional drill-down and real-time interactions of claim 1, further comprising a system-level linkage step of: establishing a visual event bus by expanding the connect function of Echarts; The interaction of any visual view is normalized to the event being published on the event bus; After other visual views subscribing related events receive the events, the data views of the events are automatically updated, and multi-view complex linkage is realized.

Description

Propagation influence dynamic visualization method supporting multidimensional drill-down and real-time interaction Technical Field The invention relates to the technical field of data visualization and urban data analysis, in particular to a propagation influence dynamic visualization method supporting multidimensional drill-down and real-time interaction. Background In the field of urban international transmission influence analysis, dynamic visualization is a key tool for assisting decision makers in understanding global public opinion and evaluating transmission effects. Currently, the construction of an analysis platform based on an open source visualization library (e.g., echorts) is a common solution in the industry. Echarts provides a good basis for general chart display by virtue of the design concept of data-driven and efficient rendering. The method adopts a hierarchical architecture design, separates data, logic and view, realizes high-efficiency update through a virtual option tree and a Diff algorithm, and effectively improves rendering performance. However, when standard echorts is applied to a specific vertical scenario of urban international transmission influence, the general design thereof exposes several key technical drawbacks. First, there is insufficient support in multidimensional data analysis. Urban propagation analysis involves multiple data dimensions of geographic hierarchy (e.g., country-city-county), time dimension, media platform, impact index, etc. The associations between dimensions of standard echartists charts are typically static and predefined, and it is difficult to support dynamic, flexible drill-down exploration by users based on real-time analysis intent. For example, when drilling from a "global city influence ranking" view to "public opinion trend of a particular city on social media platform X", it is often necessary to interrupt the current analysis flow, manually switch or reconfigure multiple charts, resulting in fragmentation of the analysis flow, inefficiency. Secondly, when facing mass real-time propagation data, the interactive performance has a bottleneck. The urban level transmission event data size is huge and the update is frequent, and when the general optimization strategy of the standard Echarts is used for coping with multi-view complex linkage (such as multi-interaction simultaneous triggering of map region selection, time axis filtration, trend graph brushing and selection and the like), the real-time performance and fluency of the system are still difficult to ensure, rendering delay and blocking are easy to occur, and the user experience and decision efficiency are seriously affected. Finally, the complexity of deep integration of Echarts with specialized city propagation influence data models and real-time computing engines is high. The standard configuration and event mechanism of echarties lacks a high-level abstraction for this scenario, resulting in tightly coupled system architecture, large custom development workload, and challenging maintainability and extensibility. Disclosure of Invention The invention aims to provide a propagation influence dynamic visualization method supporting multidimensional drill-down and real-time interaction. The method and the system can analyze the user interaction intention and automatically generate the drill-down path, improve analysis flexibility and depth, and simultaneously can efficiently process massive real-time data update and complex view linkage by optimizing the rendering mechanism of Echarts, so as to ensure response speed and fluency. The technical scheme of the invention is that the method for dynamically visualizing the propagation influence supporting multidimensional drill-down and real-time interaction comprises the following steps: S1, accessing original propagation event data from a multi-source data stream through a propagation influence data adapter, and converting the original propagation event data into structured data carrying a multi-dimensional tag; S2, responding to interactive operation of a user on a visual view, and dynamically analyzing the context information of the interactive operation through an interactive intention analyzer to generate a drill-down instruction containing a target dimension identifier; s3, dynamically generating data query sentences and visual configuration options required by the analysis view of the next level through a drill-down path manager according to the drill-down instruction and a predefined metadata rule; And S4, submitting the visual configuration options to a visual instance based on Echarts, and performing difference comparison and local updating on the views by using a virtual option tree Diff algorithm of the Echarts to realize seamless drill-down rendering. In the method for dynamically visualizing the propagation influence supporting multidimensional drill-down and real-time interaction, in step S1, the propagation influence data adap