Episode 6: Baruch Spinoza — The Ethics

Episode 6: Baruch Spinoza — The Ethics

Baruch Spinoza's "Ethics" (often referred to as "Ethica" from its Latin title "Ethica, ordine geometrico demonstrata", meaning "Ethics Demonstrated in Geometrical Order") is a philosophical treatise written in the mid-17th century. It is one of the most significant and controversial works of the Enlightenment, and it presents Spinoza's metaphysical, epistemological, moral, and political views.

The structure of "Ethics" is unique: it is laid out like a geometrical treatise, akin to Euclid's "Elements". Starting with definitions and axioms, Spinoza proceeds with propositions, proofs, corollaries, and scholia (notes), aiming to demonstrate his philosophy with mathematical precision.

In this particular semantic analysis, we explore one of the famous quotes from Ethics:

Desire is the very essence of man, insofar as it is conceived as determined to some action by any of its affections.

Workflow for Creating a Network of Keywords

  • Start by creating a new node. Label this node "Spinoza".
  • Input the chosen excerpt of text into the comment section of the "Spinoza" node.
  • Use the keyword "Keywords" to guide the Dimension Elicitor in analyzing the comment in the "Spinoza" node. Specify the General Context for your analysis as "Philosophy". By setting this context, you are providing direction for the Dimension Elicitor to understand the broader topic of your text. The Dimension Elicitor will then identify and extract relevant dimensions or keywords from the comment.
  • Examine the dimensions or keywords that Hellixia has identified. Any dimensions that appear irrelevant or redundant should be removed from your analysis.
  • Use the Embedding Generator on all remaining nodes. This tool will quantify the semantics associated with the names and comments of each node.
  • Set the "Spinoza" node as your Target Node.
  • Run the Naive Learning algorithm.
  • Update the visual style of all nodes to appear as "Badges". This will allow the comments within each node to be displayed.
  • Switch to Validation Mode F5.
  • Run an Arc Force analysis.
  • Use the Radial Layout while you are still within the Arc Force analysis tool. This will arrange the nodes in a clockwise fashion based on the strength of their relationships with the target node.
  • Show the Arc Comments to visualize information regarding the strength of the relationships between the nodes.

Workflow for creating the Semantic Network

  • Start by copying the node "Spinoza". Then, create a new graph and paste the node.
  • Utilize the Dimension Elicitor with the subsequent keywords: Ideas, Rules, Themes, Theses, Topics, and the General Context set to "Philosophy".
  • Inspect the dimensions returned by Hellixia and eliminate any that seem superfluous or unrelated to your analysis. Next, exclude the "Spinoza" 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 from the excerpt.
  • Change node styles to Badges to ensure each node's comment is visible. Then, apply the Dynamic Grid Layout to position the nodes on your graph; bear in mind that 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 your taste.
  • Switch over to Validation Mode F5 and select Skeleton View. Since your network doesn't represent causal relations, Skeleton View will maintain only node connections without indicating a direction.

Workflow for the Node Force analysis

Workflow for creating the Hierarchical Semantic Network

  • Execute Variable Clustering: This operation will categorize analogous variables based on their 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 apply Node Force.

For North America

Bayesia USA

4235 Hillsboro Pike
Suite 300-688
Nashville, TN 37215, USA

+1 888-386-8383

Head Office

Bayesia S.A.S.

Parc Ceres, Batiment N 21
rue Ferdinand Buisson
53810 Change, France

For Asia/Pacific

Bayesia Singapore

1 Fusionopolis Place
#03-20 Galaxis
Singapore 138522

Copyright © 2024 Bayesia S.A.S., Bayesia USA, LLC, and Bayesia Singapore Pte. Ltd. All Rights Reserved.