This Python module defines keyword dictionaries used for incident classification of YouTube videos after retrieval. The keyword lists provide the terms used to identify different types of incidents and support automated classification.
The script organizes classification terms into separate keyword lists. Each list represents an incident category and contains words and phrases that may appear in video titles, descriptions, or related text.
The module defines keyword groups for the following categories:
The CATEGORY_MAP dictionary connects each incident category with its corresponding keyword list. This structure allows classification programs to loop through categories and apply consistent keyword matching.
The CATEGORY_WEIGHTS dictionary assigns importance scores to incident categories. These weights can be used by classification programs when multiple categories are identified or when prioritizing incident types.
This module is designed to be imported by other Python programs, such as YouTube API search and classification scripts. The importing program uses the keyword lists and category mappings to classify retrieved videos.
This script provides a reusable keyword-based classification framework. By separating keywords, category mappings, and weights into a dedicated module, the classification workflow becomes easier to maintain, expand, and apply to new datasets.