  We propose the Echo-Chamber Effect assessment of an online forum. Sentiments
perceived by the forum readers are at the core of the analysis; a complete
message is the unit of the study. We build 14 models and apply those to
represent discussions gathered from an online medical forum. We use four
multi-class sentiment classification applications and two Machine Learning
algorithms to evaluate prowess of the assessment models.
