Detecting Evolution of Concepts based on Cause-Effect Relationships in Online Reviews

Abstract

Analyzing how technology evolves is important for understanding technological progress and its impact on society. Although the concept of evolution has been explored in many domains (e.g., evolution of topics, events or terminology, evolution of species), little research has been done on automatically analyzing the evolution of products and technology in general. In this paper, we propose a novel approach for investigating the technology evolution based on collections of product reviews. We are particularly interested in understanding social impact of technology and in discovering how changes of product features influence changes in our social lives. We address this challenge by first distinguishing two kinds of product-related terms: physical product features and terms describing situations when products are used. We then detect changes in both types of terms over time by tracking fluctuations in their popularity and usage. Finally, we discover cases when changes of physical product features trigger the changes in product's use. We experimentally demonstrate the effectiveness of our approach on the Amazon Product Review Dataset that spans over 18 years.