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This project collects social media data (from Twitter) and analyze it to retrieve any roadside traffic accident related information (like the location of incident, severity, type of injuries, etc) in realtime. Python, Spark, Apache Kafka.
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abhijajal/Social-Media-Data-Analysis-for-Accident-Reports
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Steps for runnning this Project: 1. Run "trainModels.py" to train the Models offline for the data stored in finalDataSet.txt. 2. After running this, two folders would be created for storing models. 3. Then open the terminal and run zookeeper, Kafka Server and create a topic named "twitter" 4. Run "twitter_producer.py" 5. Run "twitter_consumer.py" 6. Visualize the Data is Kibana at indexes twitternb and twitterlr Code for Running Kafka: Starting the zookeeper: bin/zookeeper-server-start.sh config/zookeeper.properties Starting the Kafka Server: bin/kafka-server-start.sh config/server.properties Creating a topic: bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic twitter List all the topics: bin/kafka-topics.sh --list --zookeeper localhost:2181 Running Producer: bin/kafka-console-producer.sh --broker-list localhost:9092 --topic twitter Running Consumer: bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic twitter --from-beginning
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This project collects social media data (from Twitter) and analyze it to retrieve any roadside traffic accident related information (like the location of incident, severity, type of injuries, etc) in realtime. Python, Spark, Apache Kafka.
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