ant-participant-identification

To identify actors in Actor-Network Theory, you extract human participants like individuals and organizations, alongside non-human entities such as technologies and artifacts, to build a comprehensive actor inventory from your text.

Yes, you can analyze socio-technical networks for technology adoption by computing basic graph metrics using NetworkX, inferring relationship types with context and confidence from co-occurrence and action cues.

The best way to build an actor inventory from policy implementation text is to process the content to extract individual, collective, and technological entities, categorizing them into human and non-human participants.

Yes, participant identification works for telemedicine deployment scenarios by detecting technologies, documents, and human actors to model who acts and with what relational significance in the network.

You infer relationship types between actors in a socio-technical network by analyzing co-occurrence and action cues in the text, generating connections with contextual data and confidence scores.

To extract non-human actors, you need to provide raw text or a JSON object containing a text or content field, which the system processes to detect technologies, documents, concepts, and contextual entities.