processing-network-data

Converting raw survey data into an edge list involves extracting entities and coded relationships from questionnaire responses, then cleaning inconsistencies to output structured node and edge lists. This standardizes raw relationship data for network analysis frameworks.

Building an adjacency matrix from interview and observation logs requires identifying interacting entities and encoding their relationship frequencies or strengths. The process constructs a validated matrix representing undirected, weighted, or multi-attribute network patterns.

Yes, you can use questionnaire exports to generate a node list with integrated attributes. The process extracts unique entities from raw relationship descriptions, merges their specific node attributes, and handles time-related relationship information into a structured format.

Network data validation detects missing values, inconsistencies, and anomalies within raw relationship datasets through deterministic script-based transformations. It outputs structured results alongside a data quality assessment record to ensure clean network inputs.

Data sources suitable for extracting relationship data include surveys, interviews, observation coding, and digital interaction logs. The process identifies relationships and optional weights from these sources to construct node sets and adjacency matrices.

Limitations when processing digital interaction logs involve relying on deterministic script-based transformations and strict format requirements. The process requires well-structured raw inputs to correctly extract edges and produce validated network analysis artifacts.