Time-space varying visual analysis of micro-blog sentiment

Abstract

Micro-blog sentiment analysis attracts much attention by companies, governments and other organizations. It could help companies to estimate the extent of product acceptance and to determine marketing strategies, governments to monitor online public perception and to improve government-public relation, etc. Researchers mainly focused on time-varying analysis or space varying analysis. This paper combines time-varying analysis and space varying analysis and proposes an Electron Cloud Model (ECM) based on the Schrodinger equation and Niels Bohr atomic theory to conduct time-varying visual analysis of micro-blog sentiments. In the ECM, an attempt to map a score of sentiment to the electron stability is made. Kernel density estimation and edge bundling are used to conduct space-varying visual analysis of sentiments. The former visualizes sentiment changes in different levels of detail naturally while the latter can reduce visual clutter of edge crossing and reveal high-level edge pattern.