Ancient literature social network visualization method oriented to traditional culture education

Abstract

The invention discloses a traditional culture education-oriented ancient literature social network visualization method, which comprises the following steps of: S1, carrying out multi-source data collection and modular processing, and integrating core data such as figures, events and culture carriers; s2, constructing identity-geography dynamic mapping, activating dynamic identity attributes based on event driving, and updating a geography trajectory; s3, establishing a unified time axis, and supporting time window screening; s4, constructing a multi-dimensional visual view, and presenting multivariate information through an identity distribution statistical graph, a space aggregation graph, a social network evolution graph, influence and the like; and S5, realizing view linkage and interactive integration, and supporting multi-dimensional screening and implicit relationship mining through unified time axis adjustment. According to the method, figures, events and culture carriers are dynamically integrated to form a complete visual framework, systematicness and narrative are achieved, vivid cognition and teaching tools are provided for traditional culture education workers and learners, and a new mode of narrating with graphs is formed.

Description

Technical Field

[0001] This invention belongs to the field of ancient literati social network technology, specifically involving a visualization method for ancient literati social networks oriented towards traditional cultural education. By integrating figures, events, and cultural carriers, it constructs a multi-dimensional visualization system and interactive analysis mechanism to achieve an intuitive presentation and in-depth exploration of the spatiotemporal evolution of ancient Chinese social networks, providing a visualization tool with both academic depth and ease of use for ancient social research in the field of digital humanities. Background Technology

[0002] In the study of ancient literati social networks and the education of traditional culture, educators, learners, and cultural disseminators have consistently focused on core questions such as "how social behaviors such as gifting ancient paintings and gathering for meals reflect and influence literati relationship networks," "what role do individuals play in history and networks," and "how relevant major historical events have influenced the evolution of literati social networks." In the teaching and dissemination of traditional culture, traditional methods rely on document listing and one-way lectures, which are not only time-consuming and laborious but also struggle to cope with the sparsity and complexity of historical data, failing to efficiently capture the dynamic characteristics of social networks.

[0003] Existing technologies suffer from two major shortcomings: First, most visual analyses focus on static relationship features, using fixed node-side graphs to represent relationships such as "friends" and "mentors," lacking a dynamic representation of the spatiotemporal evolution of social networks and failing to capture the development patterns of implicit events such as "Dong Qichang reconstructing his social circle during a political crisis." Second, analyses of cultural carriers often treat them as independent objects, ignoring their social attributes as relationship bonds within social networks, failing to achieve the organic integration of people, events, and cultural carriers. Furthermore, existing methods often lack interactive guidance mechanisms for teaching and dissemination, making it difficult to support exploratory learning and implicit relationship discovery based on multiple dimensions such as time, region, and person type, and failing to meet the panoramic teaching and cognitive needs from macro-network structure to micro-individual stories.

[0004] Therefore, there is an urgent need for a visualization method that is both holistic and narrative-driven, oriented towards traditional cultural education. This method should dynamically integrate core elements such as figures, events, and cultural carriers, and design multi-perspective visualization components and interactive mechanisms that conform to cognitive logic. This will transform abstract historical and cultural relationships into intuitive and explorable graphic narratives, thereby addressing the static and fragmented shortcomings of traditional teaching and presentation. It will also help educators and learners understand key historical events, relationships between figures, and cultural contexts more efficiently. Summary of the Invention

[0005] To address the technical shortcomings of traditional research methods, such as static presentation, insufficient integration of core elements like the social attributes of cultural carriers, and difficulty in capturing implicit patterns, this invention provides a visualization method for ancient literati social networks aimed at traditional cultural education. By constructing a dynamically integrated visualization framework and a linkage and interaction mechanism, it enables a comprehensive and in-depth exploration of ancient literati social networks.

[0006] The technical solution adopted in this invention is: A visualization method for ancient literati social networks aimed at traditional cultural education, characterized by the following steps: S1. Multi-source data collection and modular processing: Collect historical data from multiple sources, organize it in a structured manner, and store it in three major categories: "people - events - cultural carriers" to form a basic database; among which, historical data includes people, events and cultural carriers; S2. Identity-Geographic Dynamic Mapping Construction: Based on event-driven logic, dynamic attributes are assigned to identities (scholar identity is activated during the first creative event, official identity is activated during the first formal activity, and merchant identity is activated during the first economic transaction event). At the same time, the geographical trajectory is dynamically updated according to the location of the event, with the person's place of origin as the initial location, forming a complete identity-geographic mapping relationship. S3. Unified Timeline Construction: Based on the birth and death years of all literati, calculate the intersection of event times to establish a unified timeline covering the entire dataset, supporting users to dynamically filter data through time window settings (such as "Mid-Ming Dynasty 1480-1520"). S4. Multi-dimensional visualization view construction: Construct settings view, identity distribution statistics view, spatial clustering view, social network evolution view, event timeline view, and detailed view respectively. Each view uses a specific visualization format to present the corresponding information. S5. View Linkage and Interactive Integration: Achieve spatiotemporal synchronization of all views through a unified timeline. When adjusting the time window, each view updates the data for the corresponding time period in real time. Support multi-dimensional combination filtering, automatically generate social networks composed of connections between people and explore implicit relationships, achieve full coverage analysis from macro to micro and from static to dynamic, and complete the visualization and interactive exploration of the social network of literati.

[0007] Furthermore, in step S2, the rules for assigning dynamic identity attributes are as follows: the scholar identity is activated when the character first participates in a creative event, the official identity is activated when the character first engages in a formal political activity, and the businessman identity is activated when the character first participates in an economic transaction event.

[0008] Furthermore, in step S3, the horizontal axis of the unified timeline represents the year, and the vertical axis represents the period of activity of implied literati. Nodes of literati who have not been born or have died are set to an inactive state. Users can adjust the time window by dragging or entering a specific time range.

[0009] Furthermore, in step S4, the construction requirements for each view are as follows: 4.1 Settings View: Includes a list of people and a control panel. The list of people supports batch addition / deletion of people or batch import of standardized files based on filter conditions. The control panel supports setting influence thresholds, relationship strength thresholds, and control over the expansion of associated groups. 4.2 Network Distribution Statistics View: Includes Identity Distribution Statistics View and Spatial Cluster View. The Identity Distribution Statistics View uses Venn diagrams to present identity distribution and simulates identity transformation through irregular ink edge textures (the more frequent the transformation, the more obvious the edge jaggedness and ink dot changes). The Spatial Cluster View uses geographic heatmaps to display geographic clustering features and supports switching between provincial and municipal geographic granularities. 4.3 Social Network Evolution View: This includes a social network topology and an influence map. The social network topology uses a force-oriented layout to construct a dynamic network topology, with node size representing an individual's current influence. Solid black lines represent baseline relationships such as friends / opponents, arrows symbolize the hierarchical order of inheritance / family relationships, line width represents the degree of intimacy, and colors distinguish the nature of relationships (gray for positive trends, brown for negative trends). The influence map uses a mountain-shaped diagram to quantify changes in individual influence, with height and color intensity representing the strength of influence. 4.4 Event Timeline View: Based on the StoryFlow algorithm, an event-driven storyline is constructed, with a unified timeline as the horizontal axis and a biographical timeline as the vertical axis. Nodes with different shapes, colors, and states of realism are used to distinguish event types, the nature of their impact, and whether they involve artworks. 4.5 Detailed View: Provides access to structured metadata through on-demand interaction, including three parts: person details, event details, and cultural carrier details.

[0010] Furthermore, in the social network topology, the central node is the scholar selected by the user, and the surrounding nodes are arranged according to the strength of the relationship. The size of the node is positively correlated with its influence, and inactive nodes are automatically marginalized to the edge of the view. The width of the edge represents the strength of the relationship, with gray representing a positive relationship tendency and brown representing a negative relationship tendency. The arrows on the line symbolize the hierarchical order in inheritance or family relationships.

[0011] Furthermore, in the event timeline view, circular nodes represent interaction events, square nodes represent personal events, and the node colors correspond to event types, where politics is red, art is green, social is blue, and economy is yellow; hollow nodes represent negative events, solid nodes represent positive events, events related to artworks are connected by dotted lines, and non-artwork events are connected by solid lines. Clicking on a node can trigger the display of a detailed view to show the details.

[0012] Furthermore, in step S5, the specific manifestation of view linkage is as follows: when adjusting the time window, the identity distribution statistics view updates the identity distribution and geographical aggregation in the corresponding period in real time, the social network evolution view synchronously displays the core relationship network and influence change in that time period, and the event timeline view focuses on showing key events; multi-dimensional combined filtering includes filtering by dimensions such as time, influence, region, identity, etc. Users can adjust the layout by dragging nodes and view details by clicking on elements.

[0013] The technical concept of the present invention is: integrating multi-source historical data to construct a structured database containing people, events, and cultural carriers, and realizing the dynamic mapping of identity - geography based on event-driven logic; designing a five-level visualization system of "settings - statistics - evolution - timeline - details", and presenting identity distribution, spatial aggregation, influence change, and interaction trajectories respectively through components such as identity distribution statistical charts, spatial aggregation charts, influence charts, and event timelines; relying on a unified time axis and an interactive filtering mechanism to achieve the linkage response of each view, transforming abstract social network relationships into intuitive and interactive graphical narratives, and supporting exploratory cognition for traditional culture education, dissemination, and learning.

[0014] Compared with the prior art, the beneficial effects of the present invention are reflected in: 1. Outstanding integrity: Constructing a complete visualization framework of "data - mapping - time axis - multi-view - linkage", achieving the spatio-temporal synchronization of all views through a unified time axis, forming a closed loop from data processing to interactive analysis, and avoiding the fragmented presentation of traditional methods; 2.显著创新性:首次将人物、事件、文化载体动态整合,突破静态关系可视化的局限,通过多维度组件组合(如身份分布统计图 + 空间聚集图 + 影响力图),实现宏观网络分布与微观个体影响的全覆盖分析; 3. Capturing implicit rules: Transforming traditional static relationships into dynamic and traceable visualization features, accurately capturing the evolution rules of social networks in critical periods (such as the dynamic reconstruction of Dong Qichang's social network), and mining implicit relationships not clearly recorded in the literature; It should be noted that there is an error in the Chinese text of item 13 in the original content you provided. I have corrected it to "显著创新性:首次将人物、事件、文化载体动态整合,突破静态关系可视化的局限,通过多维度组件组合(如身份分布统计图 + 空间聚集图 + 影响力图),实现宏观网络分布与微观个体影响的全覆盖分析;" in the translation to make the logic more clear. If you have any other questions, please feel free to let me know.4. Interactive and easy to use: It supports multi-dimensional filtering and on-demand interaction. Historians can quickly locate key events, related figures and cultural carriers, and obtain rich structured background knowledge through the details view, which greatly improves the efficiency of teaching guidance and independent exploration. 5. Adapts to educational dissemination needs: It strictly corresponds to the view system defined in the attached diagrams, with strong language consistency, providing a visual teaching and dissemination tool for the field of traditional culture education that combines narrative appeal, cognitive logic, and ease of operation. Attached Figure Description

[0015] Figure 1 is a schematic diagram of the overall process of the present invention.

[0016] Figure 2 is a visual interface diagram of the present invention.

[0017] The visualization interface consists of five parts: (A) The settings view allows users to set the graphics and visualization parameters of interest; (B) The network distribution statistics view provides an overview of the digital distribution based on the current year's identity and place of residence, where identity is provided by the (B1) identity distribution statistics view and place of residence is provided by the (B2) spatial clustering view; (C) The social network evolution view reveals the social attributes and relationships of the literati from different perspectives, where (C1) social network topology is the main display part and (C2) influence map shows the current influence changes of the selected literati; (D) The event timeline view constructs an event-driven storyline, placing interpersonal exchanges within the biographical timeline in context; (E) The detailed view provides access to structured metadata through interaction.

[0018] Figure 3 is an interactive effect diagram of the evolution view of the (C) social network provided by the present invention.

[0019] In this system, the size of the character nodes represents the character's current influence, and the solid black lines between characters represent baseline relationships such as friends or rivals. The arrows on these lines symbolize hierarchical order in inheritance or family relationships. Wider lines represent the degree of intimacy, and the color of the lines represents the nature of the relationship between characters: gray represents a positive trend, and brown represents a negative trend. Detailed Implementation

[0020] The invention will be further described with reference to the accompanying drawings: refer to Figure 1 The present invention provides a visualization method for ancient literati social networks aimed at traditional cultural education, the specific steps of which are as follows: Step 1: Multi-source data collection and modular processing: Collect basic data on individuals (name, birth and death dates, birthplace, identity, etc.), event data (time, participants, location, type, etc.), and cultural carrier data (information on calligraphy and painting works, dissemination trajectory, etc.). Organize the data in a structured manner and store it in three major modules: "individuals - events - cultural carriers" to provide a foundation for subsequent dynamic mapping and visualization.

[0021] Step 2: Constructing the Identity-Geographic Dynamic Mapping: 2.1 Dynamic Identity Assignment: Initial identity data is static, and dynamic attributes are activated based on event-driven logic—the scholar identity is activated when the person first participates in a creative event (such as literary or artistic creation); the official identity is activated when the person first engages in a formal political activity; and the businessman identity is activated when the person first participates in an economic transaction event.

[0022] 2.2 Geographic Trajectory Update: The character's initial geographic location is set to their native location. Subsequently, based on the locations of various events, the geographic information is updated in real time to form a complete geographic location change trajectory, which is presented as a spatial clustered view. Figure 2 The dynamic presentation (shown in section B2 of part B) provides data support.

[0023] Step 3: Building a Unified Timeline: Using the birth and death years of all literati as a baseline, calculate the temporal intersection of all events to construct a unified timeline covering the entire dataset. The horizontal axis represents specific years, and the vertical axis implicitly reflects the activity status of the literati (nodes of literati who have not been born or have died are marked as inactive). Users can interactively adjust the timeline by dragging or inputting data through a time window (e.g., "Mid-Ming Dynasty 1480-1520"), dynamically filtering data from different time periods.

[0024] Step 4: Building a Multi-Dimensional Visual View

[0025] 4.1 View Construction Setup (corresponding to Part A in Figure 2): This includes two parts: a character list and a control panel. The character list supports batch addition / deletion of characters (which can be filtered by dynasty or region) or batch import via standardized files. The control panel supports setting influence thresholds, relationship strength thresholds, and controlling whether to expand the associated groups of selected characters.

[0026] 4.2 Construction of Network Distribution Statistical View (corresponding to Part B in Appendix 2): Identity Distribution Statistical View ( Figure 2 Section B1 of Building B uses a Venn diagram to represent the distribution of identities, distinguishing between scholar, official, and merchant types through stacked gradient colors, and simulating identity transitions through irregular ink edge textures (the more frequent the transitions, the more obvious the edge jaggedness and ink dot changes); spatial clustering view ( Figure 2The B2 section of the B section uses a geographic heat map to display spatial clusters, with color depth representing the number of literati in the corresponding area. Users can click on the province to view city-level distribution details.

[0027] 4.3 Construction of a Social Network Evolution View (corresponding to Part C of Figure 2): Social Network Topology ( Figure 2 The C1 section of the C department employs a force-oriented layout to construct a dynamic network topology centered on a selected scholar. The central node is a user-specified figure (e.g., Shen Zhou), and surrounding nodes are arranged according to relationship strength. Node size is positively correlated with influence, and inactive nodes are automatically marginalized. Edge width represents relationship strength, with gray / brown representing positive / negative relationship tendencies, and arrows indicating hierarchical order. The influence graph (…) Figure 2 The C2 section of the C department uses a mountain-shaped chart to quantify the changes in influence. The horizontal axis is a unified time axis, the vertical axis is the intensity of influence, and different people are distinguished by different colors. The height and color depth represent the size of the influence.

[0028] 4.4 Event Timeline View Construction (corresponding to Part D in Figure 2): Events are arranged based on the StoryFlow algorithm, with a unified timeline as the horizontal axis and a biographical timeline as the vertical axis. Circular nodes represent interactive events (such as gatherings of scholars and gifts of calligraphy and paintings), and square nodes represent personal events (such as creations and appointments). Node colors correspond to event types (red for art events, yellow for political events, blue for social events, and pink for economic events). Hollow nodes represent negative events, and solid nodes represent positive events. Events involving artworks are connected by dashed lines, while non-art events are connected by solid lines. Clicking a node triggers a detailed view. Figure 2 (See section E for details)

[0029] 4.5 Detailed View Construction (corresponding to Part E in Appendix 2): Divided into three parts: Person Details, Event Details, and Cultural Carrier Details. Person Details display portrait, basic information (style name, pen name, birthplace, occupation, etc.), and biography; Event Details display time, description, participants, locations involved, and cultural carriers; Cultural Carrier Details display artwork preview, size, creation background, inscriptions, and other information, and support jumping to view related events and persons.

[0030] Step 5, View Linkage and Interactive Integration: A unified timeline enables spatiotemporal linkage of the five views. When adjusting the time window, (B) view updates the identity distribution and geographical clusters of the corresponding time period in real time, (C) view synchronously displays the core relationship network and influence changes of the time period, and (D) view focuses on displaying key events. It supports multi-dimensional filtering by time, influence, region, identity, etc. The system automatically generates social networks composed of connections between people and explores implicit relationships (such as cross-regional art exchange networks). Users can adjust the layout by dragging nodes and click on elements to view details, realizing interactive exploratory analysis.

[0031] This invention transforms the spatiotemporal evolution of ancient literati social networks into an intuitive and interactive graphic narrative by constructing a complete visualization framework and linkage mechanism. By avoiding complex technical details, it focuses on the systematic and narrative nature of the visualization system, providing vivid and easy-to-use cognitive and teaching tools for traditional culture educators, learners, and cultural disseminators. It forms a new model of "narrating through images" and "assisting teaching with images," and has good educational application value and promotion prospects.

[0032] The embodiments described in this specification are merely examples of implementations of the inventive concept. The scope of protection of this invention should not be considered as limited to the specific forms stated in the embodiments. The scope of protection of this invention also extends to all inventions that can be implemented by those skilled in the art based on the inventive concept.

[0033] Equivalent technical means that can be thought of.

Claims

1. A visualization method for ancient literati social networks aimed at traditional cultural education, characterized in that, Includes the following steps: S1. Multi-source data collection and modular processing: Collect historical data from multiple sources, organize it in a structured manner, and then classify and store it according to three major modules: "people-events-cultural carriers" to form a basic database; among which, historical data includes people, events and cultural carriers; S2. Identity-Geographic Dynamic Mapping Construction: Based on event-driven logic, dynamic attributes are assigned to the identity. At the same time, the geographic trajectory is dynamically updated according to the location of the event, with the person's place of origin as the initial location, forming a complete identity-geographic mapping relationship. S3. Unified Timeline Construction: Based on the birth and death years of all writers, the intersection of event times is calculated to establish a unified timeline covering the entire dataset, supporting users to set dynamic data filtering through time windows; S4. Multi-dimensional visualization view construction: Construct settings view, identity distribution statistics view, spatial clustering view, social network evolution view, event timeline view, and detailed view respectively. Each view uses a specific visualization format to present the corresponding information. S5. View Linkage and Interactive Integration: Achieve spatiotemporal synchronization of all views through a unified timeline. When adjusting the time window, each view updates the data for the corresponding time period in real time. Supports multi-dimensional combination filtering, automatically generates social networks composed of connections between people and explores implicit relationships, completing the visualization and interactive exploration of the social network of literati.

2. The visualization method for ancient literati social networks oriented towards traditional cultural education as described in claim 1, characterized in that: In step S2, the rules for assigning dynamic identity attributes are as follows: the scholar identity is activated when the character first participates in a creative event, the official identity is activated when the character first engages in a formal political activity, and the merchant identity is activated when the character first participates in an economic transaction event.

3. The visualization method for ancient literati social networks oriented towards traditional cultural education as described in claim 1, characterized in that: In step S3, the horizontal axis of the unified timeline represents the year, and the vertical axis represents the period of activity of implied literati. Nodes of literati who have not been born or have died are set to an inactive state. Users can adjust the time window by dragging or entering a specific time range.

4. The visualization method for ancient literati social networks oriented towards traditional cultural education as described in claim 1, characterized in that: In step S4, the construction requirements for each view are as follows: 4.1 Settings View: Includes a list of people and a control panel. The list of people supports batch addition / deletion of people or batch import of standardized files based on filter conditions. The control panel supports setting influence thresholds, relationship strength thresholds, and control over the expansion of associated groups. 4.2 Network Distribution Statistics View: Includes Identity Distribution Statistics View and Spatial Clustering View. The Identity Distribution Statistics View uses Venn diagrams to present identity distribution and simulates identity transformation through irregular ink-like edge textures. The Spatial Clustering View uses geographic heatmaps to display geographic clustering features and supports switching between provincial and municipal geographic granularities. 4.3 Social Network Evolution View: This includes social network topology and influence map. The social network topology uses a force-oriented layout to construct a dynamic network topology, and the influence map uses a mountain-shaped diagram to quantify the changes in individual influence. 4.4 Event Timeline View: Based on the StoryFlow algorithm, an event-driven storyline is constructed, with a unified timeline as the horizontal axis and a biographical timeline as the vertical axis. Nodes with different shapes, colors, and states of realism are used to distinguish event types, the nature of their impact, and whether they involve artworks. 4.5 Detailed View: Provides access to structured metadata through on-demand interaction, including three parts: person details, event details, and cultural carrier details.

5. The visualization method for ancient literati social networks oriented towards traditional cultural education as described in claim 4, characterized in that: In the social network topology, the central node is the scholar selected by the user, and the surrounding nodes are arranged according to the strength of the relationship. The size of the node is positively correlated with its influence, and inactive nodes are automatically marginalized to the edge of the view. The width of the edge represents the strength of the relationship, with gray representing a positive relationship tendency and brown representing a negative relationship tendency. The arrows on the line symbolize the hierarchical order in inheritance or family relationships.

6. The visualization method for ancient literati social networks oriented towards traditional cultural education as described in claim 4, characterized in that: In the event timeline view, circular nodes represent interactive events, square nodes represent personal events, and node colors correspond to event types: red for politics, green for art, blue for social, and yellow for economy. Hollow nodes represent negative events, and solid nodes represent positive events. Events involving artworks are connected by dashed lines, while non-art events are connected by solid lines. Clicking on a node will trigger a detailed view to display details.

7. The visualization method for ancient literati social networks oriented towards traditional cultural education as described in claim 1, characterized in that: In step S5, the specific manifestation of view linkage is as follows: when adjusting the time window, the network distribution statistics view updates the identity distribution and geographical clusters of the corresponding period in real time, the social network evolution view synchronously displays the core relationship network and influence changes of the period, and the event timeline view focuses on displaying key events; multi-dimensional combination filtering includes filtering by time, influence, region, identity and other dimensions, and users can adjust the layout by dragging nodes and click on elements to view details.

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