Social Media Big Data (No Coding Required)

Assume you work for a client XYZ. Client wants to leverage big social media data to learn more information online and help make better decisions. Task is to work on one idea and make a concrete plan (no actual coding required) Idea: Detect events from social media using big data techniques. Messages posted on Twitter (tweets) have been reporting everything from daily life stories to the latest local and global news and events. Monitoring and analyzing this rich and continuous user-generated content can yield unprecedentedly valuable information, enabling users and organizations to acquire actionable knowledge. While making plan, you need to know his requirement. Here’s requirements: 1) In real-time detection on Twitter 2) Able to tell which event is interesting and trending, e.g., a lot of people talking about it 3) Able to receive pushed events information on various devices, including phones, tablets, and desktop computers. Client provides a set of keywords to guide you when planning a big data pipeline for him: Real-time Twitter streams, event detection, clustering, Spark, Kafka Client also provides a list of references, and suggests to use his keywords to search online to get more resources [login to view URL] [login to view URL]~gravano/Papers/2011/[login to view URL] [login to view URL]~gravano/Papers/2010/[login to view URL] [login to view URL] (read section 4 carefully) [login to view URL] Make an actionable plan (3-4 Pages Report) -What is the initial input -What is the final output -What are the software/algorithm components in the plan -What are the Input/Output of each component -What do each component do -Why pick this component (e.g., why using spark here, why do sentiment analysis) -What does this component do (e.g., how is the sentiment score computed, what are the steps) -Advantages and disadvantages of the plan