Sharan Kumar Ravindran - Mastering Social Media Mining with R

Sharan Kumar Ravindran is a data scientist with over five years of experience. He is currently working for a leading e-commerce company in India. His primary interests lie in statistics and machine learning, and he has worked with customers from Europe and the U.S. in the e-commerce and IoT domains.

He holds an MBA degree with specialization in marketing and business analysis. He conducts workshops for Anna University to train their staff, research scholars, and volunteers in analytics.

In addition to coauthoring Social Media Mining with R , he has also reviewed R Data Visualization Cookbook . He maintains a website, www.rsharankumar.com, with links to his social profiles and blog.

I would like to thank the R community for their generous contributions.

I am grateful to Mr. Derick Jose for the inspiration and opportunities given to me.

I would like to thank all my friends, colleagues, and family members, without whom I wouldn't have learned as much.

I would like to thank my dad and brother-in-law for all their support and also helping me in proofreading and testing.

I would like to thank my wife, Aishwarya, and my sister, Saranya, for the constant motivation, and also my son, Rithik, and niece, Shravani, who make every day of mine joyful and fulfilling.

Most of all, I would like to thank my mother for always believing in me.

Vikram Garg (@vikram_garg) is a senior analytical engineer at a Big Data organization. He is passionate about applying machine learning approaches to any given domain and creating technology to amplify human intelligence. He completed his graduation in computer science and electrical engineering from IIT, Delhi. When he is not solving hard problems, he can be found playing tennis or in a swimming pool.

I would like to dedicate all my books to my parents and my brother. Without whom I am no one.

Richard Iannone is an R enthusiast and a very simple person. Those who know him (and know him well) know that this is indeed true. He has authored many R packages that have achieved great success. Those who have reviewed the code know that it possesses a je ne sais quoi essence to it. In any case, the code coverage is quite adequate (thanks to the many "test parties" he held), and he often offers builds that pass muster according to Travis CI.

Although he has a tendency toward modesty, others have remarked that he's just a straight shooter with upper management written all over him. You know what, we couldn't agree more. We bet you'll hear a lot more about him in the near future.

Hasan Kurban is a PhD candidate from the School of Informatics and Computing at Indiana University, Bloomington. He is majoring in Computer Science and minoring in Statistics. His main fields of interest are Data Mining, Machine Learning, Data Science, and Statistics. He also received his master's degree in Computer Science from Indiana University, Bloomington, in 2012. You can contact him at <>.

Mahbubul Majumder is an assistant professor of statistics in the Department of Mathematics, the University of Nebraska at Omaha (UNO). He earned his PhD in statistics with specialization in data visualization and visual statistical inference from Iowa State University. He had the opportunity to work with some industries dealing with data and creating data products. His research interests include exploratory data analysis, data visualization, and statistical modeling. He teaches data science and he is currently developing a data science program for UNO.

Haichuan Wang holds a PhD degree in computer science from the University of Illinois at Urbana-Champaign. He has worked extensively in the field of programming languages and on runtime systems, and he worked in the R language and GNU-R system for a few years. He has also worked in the machine learning and pattern recognition fields. He is passionate about bringing R into parallel and distributed computing domains to handle massive data processing.

I'd like to thank Bo for always loving and supporting me.

I'd also like to thank my PhD advisors, Prof. Padua and Dr. Wu, and my MS advisor, Prof. Zhang, who triggered my interest in this field and guided me throughout this journey.