Text Network Analysis: Theory and Practice

Text network analysis belongs to the broader skill set of most text data-oriented analysts.

This article begins a journey to discover this wonderful area: from theory, data prep, and network construction to visualization and forecasting — this series covers the most fundamental concepts of text networks in Python.

Figure 1. Text network plot via Pyvis. Image by author

Developments since the late 20th century, such as…

• availability of data from social networks (e.g. Twitter),
• transcripts of politicians’ statements and central bankers’ meetings,
• publicly available APIs to text databases (Google Trends, RSS feeds, Wikipedia, Google Ngrams)
• general development of technologies to process big data

…and potentially many other factors have resulted in a vast amount of text data easily accessible to analysts, students, and researchers. Over time, scientists developed numerous complex methods to understand the relations in the text datasets, including text network analysis.

This first article on text network analysis in Python will briefly survey the underpinnings of text network analysis, real-world applications of text networks, and their implementation in major data science and business…