Wazzabeee/pyspark-etl-twitter
Implementation of an ETL process for real-time sentiment analysis of tweets with Docker, Apache Kafka, Spark Streaming, MongoDB and Delta Lake
This project helps you monitor public opinion about topics or brands as it happens, by analyzing tweets in real time. It takes live Twitter data, processes it through a pre-built sentiment analysis model, and outputs whether the sentiment is positive, negative, or neutral. Social media strategists, brand managers, or marketing analysts can use this to quickly gauge public mood.
No commits in the last 6 months.
Use this if you need to track how people are feeling about a specific subject or your brand on Twitter right now, to inform rapid response or strategy adjustments.
Not ideal if you're looking for deep historical analysis of sentiment or want to analyze data from platforms other than Twitter.
Stars
19
Forks
5
Language
Python
License
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Category
Last pushed
May 06, 2023
Commits (30d)
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