| Predicting Real World Behaviors from Virtual World Data 2014 Edition Contributor(s): Ahmad, Muhammad Aurangzeb (Editor), Shen, Cuihua (Editor), Srivastava, Jaideep (Editor) |
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ISBN: 3319071416 ISBN-13: 9783319071411 Publisher: Springer OUR PRICE: $52.24 Product Type: Hardcover - Other Formats Published: August 2014 |
| Additional Information |
| BISAC Categories: - Computers | Data Processing - Science | System Theory - Social Science | Methodology |
| Dewey: 004 |
| Series: Springer Proceedings in Complexity |
| Physical Information: 0.38" H x 6.14" W x 9.21" (0.81 lbs) 118 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: There is a growing body of literature that focuses on the similarities and differences between how people behave in the offline world vs. how they behave in these virtual environments. Data mining has aided in discovering interesting insights with respect to how people behave in these virtual environments. The book addresses prediction, mining and analysis of offline characteristics and behaviors from online data and vice versa. Each chapter will focus on a different aspect of virtual worlds to real world prediction e.g., demographics, personality, location, etc. |