Graph Algorithms: Make Election Data Great Again
Blog post from Neo4j
The presentation by John Swain of Right Relevance and Microsoft Azure analyzes Twitter conversations around Brexit and the 2016 US Presidential election using graph algorithms. The analysis reveals that social media influencers, rather than a small group of special individuals, play a crucial role in spreading information. The "Law of Quite a Few" debunks the common Internet trope of "the Law of the Few," which suggests that only a few influential people can spread information through networks. Instead, ordinary influencers with certain skills are responsible for spreading information. The analysis also highlights the importance of community detection algorithms to identify groups of people sharing similar values and interests. By using graph algorithms, such as PageRank and betweenness centrality, the team was able to analyze the Twitter data and identify key influencers and topics in the conversation. The presentation demonstrates how Neo4j's user-defined APOC procedures can be used to process large datasets and run graph algorithms natively, improving performance and scalability.
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