Predicting Real World Behaviors from Virtual World Data

CHF 92.75
Auf Lager
SKU
PK5JMD5O43U
Stock 1 Verfügbar
Geliefert zwischen Mi., 22.04.2026 und Do., 23.04.2026

Details

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.

Gathers insights from different disciplines like data mining, behavioral modeling, ethnography to connect the online with the offline world Features data-driven and theory-driven techniques for predicting people's behavior in the real world Provides a framework for doing predictive modeling from virtual worlds to the real world and the efficacy of such predictions Includes supplementary material: sn.pub/extras

Klappentext

This 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.

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.


Inhalt
Preface.- On The Problem of Predicting Real World Characteristics from Virtual Worlds.- The Use of Social Science Methods to Predict Player Characteristics from Avatar Observations.- Analyzing Effects of Public Communication onto Player Behavior in Massively Multiplayer Online Games.- Identifying User Demographic Traits through Virtual-World Language Use.- Predicting MMO Player Gender from In-Game Attributes using Machine Learning Models.- Predicting Links in Human Contact Networks using Online Social Proximity.- Identifying a Typology of Players Based on Longitudinal Game Data.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783319348490
    • Genre Information Technology
    • Auflage Softcover reprint of the original 1st ed. 2014
    • Editor Muhammad Aurangzeb Ahmad, Cuihua Shen, Jaideep Srivastava, Noshir Contractor
    • Lesemotiv Verstehen
    • Anzahl Seiten 118
    • Größe H7mm x B155mm x T235mm
    • Jahr 2016
    • EAN 9783319348490
    • Format Kartonierter Einband
    • ISBN 978-3-319-34849-0
    • Titel Predicting Real World Behaviors from Virtual World Data
    • Untertitel Springer Proceedings in Complexity
    • Gewicht 212g
    • Herausgeber Springer, Berlin
    • Sprache Englisch

Bewertungen

Schreiben Sie eine Bewertung
Nur registrierte Benutzer können Bewertungen schreiben. Bitte loggen Sie sich ein oder erstellen Sie ein Konto.
Made with ♥ in Switzerland | ©2025 Avento by Gametime AG
Gametime AG | Hohlstrasse 216 | 8004 Zürich | Schweiz | UID: CHE-112.967.470
Kundenservice: customerservice@avento.shop | Tel: +41 44 248 38 38