Twitter Analysis with Graph Databases
Neo4j and sentiment analysis for Stocks, Vaccination Centers, etc.
This is the first demo I developed with Neo4j. The objective of the demo is to open the discussion about graph databases, Neo4j, big data, analytics and IBM Power Systems with our global customers.
I decided to use Twitter as a data source so that the demo leverages public data (on Twitter) and could be customized by loading the database with tweets related to a specific customer. Now, there are a lot of things you can show from the tweets, but for my first iteration of the demonstration, I decided to keep it simple and try to answer the following questions: “When people talk about topic ‘X,’ what else do they talk about?”
Translated into the language of Twitter: “For people who use hashtag #X, what other hashtag(s) do they use?”
In order to visualize the result in an interesting way, why not try to figure out the location of those people in order to plot the results on a world map, leveraging the location information Twitter provides from consenting users.
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