The document discusses graphing Instagram activity using Neo4j and machine learning. It describes processing Instagram data through a pipeline to simulate and store data in Neo4j and HDFS for analysis. Machine learning is used to classify photos by levels of self-absorption. Problems encountered include API limitations, generating simulated data, and breaking the Neo4j database. Relational and graph databases are compared, with Neo4j being highlighted for its localized graph searches using linked node relationships.