Convert actors and relationships into network graphs with computed properties.
npx skills add https://github.com/ptreezh/sscisubagent-skills --skill ant-subagent
Please help me install this Agent Skill. Skill: ant-subagent Source: https://github.com/ptreezh/sscisubagent-skills/tree/main/skills/ant-subagent Command: npx skills add https://github.com/ptreezh/sscisubagent-skills --skill ant-subagent
It helps you analyze complex social phenomena by turning actor networks (human and non-human) into structured graph data and interpretation-ready results based on Actor-Network Theory (ANT).
Example use case: You have qualitative and relational data describing how organizations, technologies, and stakeholders interact in a digital transformation process; you can generate a network map, identify central and bridging actors, and summarize community structures to support ANT-style interpretation.
Run ant-subagent with an input file containing actor and relationship data to produce a JSON network analysis summary with key nodes and communities.
High-intent search queries and answers about installing and using this skill.
Actor-network mapping for ANT converts human and non-human actors and their relationships into a structured graph. It computes network density, centrality, and community structures, outputting a JSON summary to support ANT translation interpretation.
Actor-Network Theory translation traces how human and non-human actors are enrolled and mobilized through network relationships. Graph analytics supports this by identifying central actors and community structures that drive the translation process.
Identifying key actors in a sociological network graph involves computing centrality measures across the network structure. The analysis detects key nodes based on centrality, highlighting central and bridging actors crucial to the network.
Community detection in a social network graph uses modularity-based clustering to identify structural groups, applying a fallback mechanism when needed. It outputs community structures and centrality patterns to support participant identification in sociology research.
Actor-network analysis applies to digital transformation studies by mapping interactions among organizations, technologies, and stakeholders into a graph. It identifies central and bridging actors and summarizes community structures for ANT-style interpretation.
Actor-network analysis requires a supported input schema containing structured actor and relationship data. This schema must define human and non-human actors and their relationships to generate the graph and produce computed network properties.
ptreezhIdentify actors, map networks, and trace translation phases in socio-technical systems.
ptreezhTransform social relationship data into networks and compute centrality and community detection results.
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sparq-orgAnalyze RDF graphs with PageRank, degree centrality, and label propagation.
