This Week in Neo4j: Bluesky, Process Tempo, GraphGPT, D3.js, Pathfinding, and More

This week's newsletter highlights a tutorial by Michael Hunger on model creation with JSON data from social media platform Bluesky using graph algorithms such as Louvain for clusters and PageRank for size/importance. The code is available on GitHub. The NODES 2023 Call for Papers remains open until June 30, and the first speaker has been announced. Featured Node Speaker Joe Cobbs presents a generalizable graph model for nesting teams within leagues across multiple seasons. Additionally, Daria Chadwick introduces Process Tempo, a graph application platform that creates powerful data applications built on Neo4j with features like no-code approach, advanced automation, and efficient data modeling tools. Various upcoming events, including Graphversation Ep, Neo4j Live, Jump into Graph, MeetUp, and APAC Training Series, are highlighted as well as a tweet from Javier Cha about his participation in the virtual symposium organized by Zhaojin Zeng.