Text Network Analysis

The 121 revised full papers and 52 short papers presented together with the abstracts of 3 invited papers and those of the keynote speeches were carefully reviewed and selected from a total of 467 submissions. The papers cover a wide range of topics, including e-learning platforms and tools, learning resource management, practice and experience sharing, e-learning standards, mobile learning, education and remote classrooms, effectiveness of VR for education, life long learning, collaborative environments, remote group simulations, collaborative learning, virtual reality in education, game design and development, game engine development, game AI and artificial life, game physics, game rendering, virtual characters/agents, online/mobile game/video game, storytelling and game narrative, affective interaction in games, digital museum, digital heritage, animation techniques, augmented reality, and mixed reality.

Until recently, most network design techniques employed a bottom-up approach with lower protocol layer mechanisms affecting the development of higher ones. This approach, however, has not yielded fascinating results in the case of wireless distributed networks.

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R
About This Book
A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data
Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms.
Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering.

Master NetworkX, Social Network Analysis & Shortest Path Algorithms - Build 4 Professional Projects with Graph Theory

Master TensorFlow and Deep learning — from basic neural networks to advanced models and real world AI applications.

Unlock the power of data and insights in shaping the future of politics and society through real-world applications

by Taylor Arnold (Author), Lauren Tilton (Author)
Provides a user-friendly beginners guide to the key concepts in the digital humanities by focusing on four major types of humanities data structures: networks, text corpora, geospatial data, and images
Assumes no prior programming experience
Suitable for a one-semester course at the university level for undergraduate, graduate and professional students, or as half or full-day tutorial or seminar