Big data technology and ethics considerations in customer behavior and customer feedback mining

Abstract

The rapidly increasing attention to customer behavior and satisfaction by department stores and commercial companies and development in social media as well as online systems has promoted production and research in user engagement pattern recognition, user network analysis, topic detection from customer feedback, text-based sentiment analysis, etc. With the development of Internet of Things and social media network, ethics consideration has also playing an important role in application of big data, especially customer behavior and feedback mining. Our proposed novel system, which extracts the important topics or issues from Skype customer feedback sources and measures the emotion associated with those topics using Vibe metric, can be a good example in this area. Unlike other previous research, which has focused on extracting the user sentiments either globally or in separate topics, our work focuses on tracking the correlated emotional trajectories across all the important issues from Skype customer feedback over time. Moreover, it also provides a platform for both studying customer emotions and tracking how the emotions regarding different important topics correlatively change over time by leveraging unstructured textual customer feedback data and structured user activity telemetry data.