Text Mining with Python; for Introduction to Project Management Maturity

Text mining has a long and rich history with variations of natural language processing methods for many different fields, from pharmaceutical to news sentiments. Likewise, project management has been a mature application domain since the 1960s and with many principles, assumptions, constraints, guidance, knowledge areas, methodologies and processes used for many years. Case studies are one of the fruits of project management, with an output that can expose the level of project management that it yields. This work is an attempt to scrutinize the output with the help of our knowledge and probe the practicality of theories. The libraries that were used include nearly all attributes that exist, from Gensim to Dirichlet, cosine similarity to VADER. Through a project management perspective, maturity models were examined and from a wide applicability perspective, KPM3 (Kerzner Project Management Maturity Model) was selected. The model originally has 5 Levels, from Common Languages to Continuous Improvement. Aiming to detect a duality between theory and practice, Level 1 was scrutinized in the light of PMBOK taxonomies. In one sentence, SMBs are more knowledgeable than we expect, but they apply less than we know.