by Nicholas Archambault
Data Science Stack Exchange is a question and answer site for data scientists, machine learning professionals, and others interested in the field. This project will determine which content a data science company should create based on the site's most popular subjects.
Most questions on the site are practical, specific to data science, and relevant to other posts. The DSSE homepage divides into four main sections:
- Questions - a list of all questions asked
- Tags - a list of labels and keywords that classify questions
- Users - a list of users
- Unanswered - a list of unanswered questions
The tagging system utilized by the site provides a concrete way to quantify interest in particular topics in order to identify the trends that will inform a content recommendation.
- Understand the purpose and structure of Data Science Stack Exchange and take advantage of its organization to extract information on quantifiable trends.
- Gauge the popularity of various topics in the field through statistics on tags and views.
- Utilize data cleaning techniques and the Seaborn library to visualize the association between multiple tags.
- Conclude that topics in deep learning have the most potential for sustained engagement on the site.
A recommendation -- backed by analysis of trends over time -- for the specific type of deep learning content a company should create for maximal content engagement.