Episode 5: Blaise Pascal’s Pensées
This fifth episode analyzes another passage from Blaise Pascal’s Pensées. The selected text concerns justice, force, and the conditions for social peace.
Without doubt, the equality of goods is just; but, unable to make it force to obey justice, we have made it just to obey force; unable to strengthen justice, force was justified, so that the just and the strong might be together, and peace might be, which is the sovereign good.
Workflow for Creating a Network of Keywords
Start by generating a new node named “Blaise Pascal - Pensées”. This node will hold the text that you plan to analyze.
Add the selected excerpt into the comment section of the “Blaise Pascal - Pensées” node.
Run the Dimension Elicitor, set the General Context to “Philosophy”, and input “Keywords” as the keyword for the analysis of the node comment.
Evaluate the keywords or dimensions identified by Hellixia and eliminate any that are redundant or irrelevant.
Use the Embedding Generator for all remaining nodes. This tool will distill the semantics of the names and comments of each node into a quantifiable form.
Set “Blaise Pascal - Pensées” as the Target Node.
Run the Naive Learning algorithm.
Change the style of all nodes to “Badges”. This style will display the comment embedded within each node.
Switch to Validation Mode F5.
Perform an Arc Force analysis.
While within the Arc Force analysis tool, run the Radial Layout. This will arrange the nodes in a clockwise pattern in relation to their connection strength with the target node.
Provide information about the strength of the relationships between nodes.
Workflow for Creating the Semantic Network
Make a copy of the node named “Blaise Pascal - Pensées”.
Open a new graph and paste the copied “Blaise Pascal - Pensées” node.
Use the following keywords to guide the Dimension Elicitor in its analysis of the node: Arguments, Contents, Ideas, Matters, Milestones, Motifs, Rules, Themes, Theses, Topics, and the General Context set to “Philosophy”.
Inspect the dimensions suggested by Hellixia. Any dimensions that are irrelevant or redundant should be removed from the analysis.
Exclude the “Blaise Pascal - Pensées” node.
Use the Embedding Generator on all remaining nodes.
Run the Maximum Weight Spanning Tree algorithm to create a semantic network based on the text analysis.
Change the style of all nodes to “Badges”. This will display the comment within each node.
Run the Dynamic Grid Layout to organize the nodes on the graph. This algorithm’s output is not deterministic; it may favor vertical, horizontal, or mixed orientations. Execute this layout multiple times until you find the most suitable arrangement.
Switch to Validation Mode F5.
As the graph does not represent causal relationships, opt for the Skeleton View. This will remove all arc directions, leaving only the node connections without any specified direction.
Workflow for Node Force Analysis
Switch back to Modeling Mode F4.
Change all node styles to Discs.
Use the Symmetric Layout to organize the nodes in the graph.
Go to Validation Mode F5.
Conduct a Node Force analysis to evaluate the strength of associations in the graph.
Workflow for Creating the Hierarchical Semantic Network
This operation will categorize analogous variables based on their semantic relationships.
Open the Class Editor.
Use this function to generate descriptive names for your identified factors. This helps to make the output more understandable and interpretable.
Save these descriptions by using the Export Descriptions function.
Switch back to Modeling Mode F4.
Run Multiple Clustering.
Use this structural learning algorithm to learn a hierarchical network. Make sure to enable the Delete Unfixed Arcs option to remove unnecessary connections and streamline the model.
Use the descriptions you exported earlier as a dictionary to rename the latent variables you’ve just created. This helps in making the model more understandable and keeps the nodes’ names consistent with their semantic meaning.
Switch to Validation Mode F5.
Apply Node Force.