Implemented Text Clustering and Semantic Mapping

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Implemented Text Clustering and Semantic Mapping

  • Day: 2026-02-23
  • Time: 21:15 to 21:30
  • Project: Dev
  • Workspace: WP 1: Strategic / Growth & Development
  • Status: In Progress
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Text Clustering, Semantic Map, Python, Political Analysis, Wiki Design

Description

Session Goal

The session aimed to implement text clustering techniques and create a semantic map for political and institutional topics.

Key Activities

  • Importing and Sorting Markdown Files: Utilized Python to import necessary libraries and retrieve a sorted list of markdown summary files, focusing on political tags.
  • File Reading and Content Extraction: Defined a function to read file content and store it in a dictionary, focusing on files with specific naming patterns.
  • Sample Content Extraction: Extracted and printed a sample of markdown content related to politics.
  • Event Parsing: Developed a Python function to parse events from markdown text, extracting titles and descriptions.
  • Text Clustering with TF-IDF and KMeans: Implemented text clustering using TF-IDF vectorization and KMeans clustering, selecting documents based on user input.
  • DataFrame Creation: Constructed a DataFrame from selected events, capturing file names, titles, and descriptions.
  • K-Means Clustering: Detailed the process of clustering text data and extracting top terms for each cluster.
  • Hierarchical Semantic Map: Created a structured semantic table of contents for political leadership and institutional management themes.
  • Political and Social Thought Analysis: Examined political and social thought, focusing on institutional redesign and operational excellence.
  • Strategic Wiki Design: Outlined a framework for a strategic wiki for FCEN UBA, emphasizing structure and ontology.

Achievements

  • Successfully implemented text clustering techniques with TF-IDF and KMeans.
  • Created a semantic map for organizing political and institutional topics.

Pending Tasks

  • Further refine the semantic map to include additional political themes and insights.
  • Expand the strategic wiki framework to cover more institutional design aspects.

Evidence

  • source_file=2026-02-23.sessions.jsonl, line_number=4, event_count=0, session_id=1b0aeb345338825bb89e1954ecaa192249160e99dfef1cea77b6ba92644923c2
  • event_ids: []

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