Items related to Social Media Mining with R

Social Media Mining with R - Softcover

Danneman, Nathan; Heimann, Richard

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9781783281770: Social Media Mining with R

Synopsis

A concise, hands-on guide with many practical examples and a detailed treatise on inference and social science research that will help you in mining data in the real world. Whether you are an undergraduate who wishes to get hands-on experience working with social data from the Web, a practitioner wishing to expand your competencies and learn unsupervised sentiment analysis, or you are simply interested in social data analysis, this book will prove to be an essential asset. No previous experience with R or statistics is required, though having knowledge of both will enrich your experience.

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About the Author

Mr. Richard Heimann has followed the big data turn closely and consults with government and industry on its implications. 

Mr. Heimann balances theory and practice within all fields of social science, but particularly within geography. He is a Data Scientist at L-3 Data Tactics and focuses on advanced analytics, data science, and cloud computing. He writes frequently on related topics including his recent book, Social Media Mining with R (ISBN : 1783281774). 


In addition to teaching Human Terrain Analysis (HTA) at George Mason University, Mr. Heimann is also adjunct faculty at The University of Maryland, Baltimore County where he stimulates and facilitates similar discussions built upon related principles. His investigation has been a near 15 year critique on current theory and methodology. 


Mr. Heimann has participated in Operation Iraqi Freedom and Operation Enduring Freedom - Afghanistan, most recently in 2012 where he worked directly with the 82nd Airborne Division in Kandahar. He has recently supported the Pentagon, Department of Homeland Security and the Defense Advanced Research Projects Agency.


Nathan Danneman has a background in the quantitative study of international and civil conflict. Recently, his research has included the analysis of textual and geospatial data and the study of multivariate outlier detection. Nathan is currently a Data Scientist at Data Tactics, and he supports programs at DARPA and the Department of Homeland Security.

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