Analyzing Interactions in a Slack Communication Network

During a company-wide hackathon, Memgraph developed a Slack bot designed to analyze interactions within a Slack communication network using streaming data from Kafka and Memgraph's graph analytics capabilities. The bot gathers data from channels it is part of and creates a graph model with nodes representing users, messages, words, and channels, and edges for reactions, posts, and word count. This real-time application architecture leverages Slack's API and a Kafka cluster to feed data into Memgraph, where it updates a knowledge graph, allowing users to interact with the bot via Slack commands to gain insights into their messaging habits and interactions. The project highlights the integration of knowledge graphs and streaming data, demonstrating its potential through visualization in Memgraph Lab and analysis of network connectivity using NetworkX algorithms. The development and internal testing of Slack Influencer showcased the effectiveness of combining knowledge graphs with real-time streaming data, emphasizing its fun and experimental nature during the hackathon.