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Stay updated with the latest podcasting tips and trends.
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Create the best live podcast and engage your audience.
Tips on making the decision to monetize your podcast.
The best ways to get more eyes and ears on your podcast.
Everything you need to know about podcast advertising.
The ultimate guide to recording a podcast on your phone.
Steps to set up and use group recording in the Podbean app.
Reddit Sentiment Analysis with Apache Kafka-Based Microservices
How do you analyze Reddit sentiment with Apache Kafka® and microservices? Bringing the fresh perspective of someone who is both new to Kafka and the industry, Shufan Liu, nascent Developer Advocate at Confluent, discusses projects he has worked on during his summer internship—a Cluster Linking extension to a conceptual data pipeline project, and a microservice-based Reddit sentiment-analysis project. Shufan demonstrates that it’s possible to quickly get up to speed with the tools in the Kafka ecosystem and to start building something productive early on in your journey.
Shufan's Cluster Linking project extends a demo by Danica Fine (Senior Developer Advocate, Confluent) that uses a Kafka-based data pipeline to address the challenge of automatic houseplant watering. He discusses his contribution to the project and shares details in his blog—Data Enrichment in Existing Data Pipelines Using Confluent Cloud.
The second project Shufan presents is a sentiment analysis system that gathers data from a given subreddit, then assigns the data a sentiment score. He points out that its results would be hard to duplicate manually by simply reading through a subreddit—you really need the assistance of AI. The project consists of four microservices:
Interesting subreddits that Shufan has analyzed for sentiment include gaming forums before and after key releases; crypto and stock trading forums at various meaningful points in time; and sports-related forums both before the season and several games into it.
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2025-09-29
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