Big Data Analytics – Social Media Data Analysis Framework Using A Big Data Analytic Ecosystem

Big data analytics are at the center of modern science and business. Our social media networks, mobile devices and enterprise systems generate enormous volumes of it on a daily basis. This wide range of availability provides many organizations in every field opportunities to discover valuable intelligence for critical decision-making. However, traditional analytic architectures are insufficient to handle unprecedentedly big volume of data and complexity of data processing.

This talk presents an analytic framework to handle unprecedented scale of big data that performs data analysis effectively in a batch mode and real time. The work presents data processing techniques and data analytic methodologies in a Social Media Big Data Sentiment Analytics Service System. The architecture of the big data analytic framework including Apache Spark stream data processing framework, coupled with a NoSQL Hive big data ecosystem is also presented in this talk. The work in this talk demonstrates that topic and aspect based sentiment analysis models using machine learning classifiers coupled with a NoSQL big data ecosystem in the Cloudera virtual machine.

Dr. Chung received her Ph.D. in Computer Science from Case Western Reserve University and worked as a postdoctoral fellow in Information Retrieval System at Case. Before joining Cleveland State University as a faculty at 2012, she worked as Research Associate at NCR (now a part of IBM) and Teradata (formerly AT&T) a leading Big Data Industry in Silicon Valley, California from 2006.

Dr. Chung’s research interests include Data Analytics, Big Data Processing in Massively Parallel Processing Systems, Cloud Computing, Integration of Big Data Processing Systems, and Cyber Security in Database on Cloud. Her research has resulted in numerous publications in prestigious conferences and Journals and 5 research projects implemented into a commercial Tera Data Enterprise Parallel Data Warehouse Systems. She has also served as an ad-hoc reviewer for international conferences. She is a member of Data Scientists Professionals and she is currently serving in establishing a Center of Expertise in Data Analytics, Cloud Computing, and Cyber Security at Cleveland State University.

EECS Dept in Engineering College

Cleveland State University

Fenn Hall Room 103 (Compton Lounge)

1960 East 24th Street

Cleveland, Ohio 44115

5:00 or 6:00 arrival, registration, and refreshments

6:00 to 7:30pm lecture

East Garage, CG21, South Garage, Lot 22 under SC, or WG lot under BU

• East Garage is right next to Recreation Center(gym) at E24th and Chester and closest to Fenn Hall 103.
• CG 21 (Central Garage) is next to SC (Student Center) at E21st between Euclid and Chester.
• South Garage can be accessed from Prospect.
• Visitor’s parking lot 22 under SC (Student Center) at E21st
• WG lot under BU (Business College) at E17th.