Guy de Maupassant: The Horla (1887)
This example uses Hellixia to analyze Guy de Maupassant’s The Horla. The analysis is divided into two parts:
Identify plot events, character dynamics, and key relationships.
Examine broader themes, motifs, emotions, and interpretive dimensions.
Both workflows create semantic networks that can be inspected and refined in BayesiaLab.
Narrative Analysis
This narrative analysis focuses on plot events, character dynamics, and relationships in The Horla.
Workflow for Creating the Semantic Network
Create the node “The Horla, by Guy de Maupassant.”
Use the Dimension Elicitor, employing the keywords “Context, Developments, Entities, Events, Keywords, Locations, Milestones, Motifs, Progressions, and Relationships,” to conduct an exhaustive narrative analysis of the book.
Inspect the dimensions returned by Hellixia and eliminate any that seem superfluous or unrelated to the analysis. Next, disregard the “The Horla, by Guy de Maupassant” node and run the Embedding Generator on all remaining nodes to apprehend the semantic associations of their names and comments.
Use the Maximum Weight Spanning Tree algorithm to generate a semantic network.
Change node styles to Badges to ensure each node’s comment is visible. Then, apply the Dynamic Grid Layout to position the nodes on the graph; this algorithm is not deterministic, and its orientation—vertical, horizontal, or mixed—is random. You might need to execute this layout several times to obtain an arrangement that aligns with the intended presentation.
Switch over to Validation Mode F5 and select Skeleton View. Since the network does not represent causal relations, Skeleton View will maintain only node connections without indicating a direction.
Workflow for the Node Force Analysis
Return to Modeling Mode F4 and change the node styles to Discs.
Use the Symmetric Layout and switch to Validation Mode F5 to run a Node Force analysis.
Workflow for creating the Hierarchical Semantic Network
This operation will categorize analogous variables based on semantic relationships.
Open the Class Editor and run Class Description Generator to generate descriptive names for the factors in question. Use the Export Descriptions function, and save the newly created descriptions.
Return to Modeling Mode F4 and run Multiple Clustering to generate latent variables.
Run the structural learning algorithm Taboo. Ensure the “Delete Unfixed Arcs” option is enabled.
Use the descriptions you exported earlier as a Dictionary to rename the latent variables you’ve created.
Switch to Validation and run Node Force.
Given the size of this network, focus on the upper level of the hierarchical network. Below is the Node Force analysis on these factors only, i.e., excluding all manifest variables before the analysis.
Holistic Analysis
This holistic analysis shifts from plot structure to broader themes, emotions, and concepts in The Horla.
Follow the workflow outlined in the Narrative Analysis section, but use this set of keywords: Achievements, Characteristics, Components, Concepts, Considerations, Contributions, Domains, Elements, Emotions, Features, Feelings, Forces, Ideas, Impacts, Perspectives, Purposes, Sentiments, Subjects, Themes, Theses, and Values.
Semantic Network
Node Force Analysis
Hierarchical Semantic Network
