Visualizing e-Learner Emotion, Topic, and Group Structure in Chinese Interactive Texts

To help teachers know class/group members better in the case of large scale on-line textual interaction, this paper tried to display e-Learner's emotion combined with topics and group structure. For achieving this goal, a color palette of emotions based on Plutchik's color palette was presented, an extended cascaded PLSI algorithm using sliding window technique was proposed to detect and track topics in Chinese interactive texts, and multiple star-field variants were introduced to display the group structure.

I. Introduction

Textual interaction in e-learning applications, such as chat-room for courses, online Q&A and group discussion, serves as the most common ways to communicate between teachers and students or among students. How to display these emotional contents of interactive texts in a direct and artistic way becomes very important in the field of affective computing, which can help characterize e-Learners' negative emotions and be adopted by teachers to solve the problem of Emotional Illiteracy [1]–[3].