Text Network Analysis

This text will be of interest to policy-makers, industry consultants and students of industrial economics and management alike who feel attracted and pay attention to strategic and structural elements of network economies.

A comprehensive package for the analysis of social network data as well as other 1-mode and 2-mode data. Can read and write a multitude of differently formatted text files, as well as Excel files. Can handle a maximum of 32,767 nodes (with some exceptions) although practically speaking many procedures get too slow around 5,000 - 10,000 nodes. social network analysis methods include centrality measures, subgroup identification, role analysis, elementary graph theory, and permutation-based statistical analysis. In addition, the package has strong matrix analysis routines, such as matrix algebra and multivariate statistics.

A comprehensive package for the analysis of social network data as well as other 1-mode and 2-mode data. Can read and write a multitude of differently formatted text files, as well as Excel files. Can handle a maximum of 32,767 nodes (with some exceptions) although practically speaking many procedures get too slow around 5,000 - 10,000 nodes. social network analysis methods include centrality measures, subgroup identification, role analysis, elementary graph theory, and permutation-based statistical analysis. In addition, the package has strong matrix analysis routines, such as matrix algebra and multivariate statistics.

Network Notepad Professional Edition is a software tool that was built in order to help you design network diagrams and save them for further analysis and safekeeping.

Network Notepad Professional Edition is a software tool that was built in order to help you design network diagrams and save them for further analysis and safekeeping.

Network Notepad Professional Edition is a software tool that was built in order to help you design network diagrams and save them for further analysis and safekeeping.

Data Science & Machine Learning - Boost your Machine Learning, statistics skills with real heart attack analysis project

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning.