This document outlines steps for analyzing social media text data using semantic network analysis and visualization techniques: 1) Collecting Twitter data using Crimson Hexagon and cleaning the text by removing stop words and punctuation. 2) Performing analyses like frequency analysis, entity detection, topic modeling and sentiment analysis using packages like ConText. 3) Creating semantic networks to show word co-occurrence and visualize relationships between concepts, topics and sentiments.