Semantically-Interlinked Online Communities (SIOC)¶
The SIOC (Semantically-Interlinked Online Communities) Ontology is a widely used ontology for describing the information and structure of online communities. It provides a standardized vocabulary for representing discussion forums, blogs, wikis, social networks, and other collaborative platforms. SIOC enables the modeling of users, posts, threads, topics, and relationships between community members and content. By providing a common framework, SIOC facilitates interoperability between social platforms, supports data integration, and enables advanced queries and analytics on social data. The ontology is used in social media mining, digital humanities, and knowledge graph construction to link and analyze user-generated content across platforms. SIOC is actively maintained and extended to support emerging social web technologies and applications.
Example Usage: Annotate a forum or blog platform with SIOC terms to describe users, posts, threads, and relationships, enabling semantic search and cross-platform analysis of online community interactions.
Metrics & Statistics¶
Total Nodes |
230 |
Total Edges |
551 |
Root Nodes |
0 |
Leaf Nodes |
123 |
Classes |
14 |
Individuals |
0 |
Properties |
91 |
Maximum Depth |
0 |
Minimum Depth |
0 |
Average Depth |
0.00 |
Depth Variance |
0.00 |
Maximum Breadth |
0 |
Minimum Breadth |
0 |
Average Breadth |
0.00 |
Breadth Variance |
0.00 |
Term Types |
0 |
Taxonomic Relations |
9 |
Non-taxonomic Relations |
31 |
Average Terms per Type |
0.00 |
Usage Example¶
Use the following code to import this ontology programmatically:
from ontolearner.ontology import SIOC
ontology = SIOC()
ontology.load("path/to/SIOC-ontology.rdf")
# Extract datasets
data = ontology.extract()
# Access specific relations
term_types = data.term_typings
taxonomic_relations = data.type_taxonomies
non_taxonomic_relations = data.type_non_taxonomic_relations