HCApr 16, 2020

Quantifying Low-Battery Anxiety of Mobile Users and Its Impacts on Video Watching Behavior

arXiv:2004.07662v13 citations
AI Analysis

This work addresses the need to understand LBA for improving mobile user Quality of Experience, but it is incremental as it builds on prior awareness without introducing new paradigms.

The study tackled the problem of low-battery anxiety (LBA) in mobile users by investigating over 2000 users to quantify anxiety during battery drain and found that it impacts video-watching behavior, quantifying the likelihood of abandoning videos based on battery status.

People nowadays are increasingly dependent on mobile phones for daily communication, study, and business. Along with this it incurs the low-battery anxiety (LBA). Although having been unveiled for a while, LBA has not been thoroughly investigated yet. Without a better understanding of LBA, it would be difficult to precisely validate energy saving and management techniques in terms of alleviating LBA and enhancing Quality of Experience (QoE) of mobile users. To fill the gap, we conduct an investigation over 2000+ mobile users, look into their feelings and reactions towards LBA, and quantify their anxiety degree during the draining of battery power. As a case study, we also investigate the impact of LBA on user's behavior at video watching, and with the massive collected answers we are able to quantify user's abandoning likelihood of attractive videos versus the battery status of mobile phone. The empirical findings and quantitative models obtained in this work not only disclose the characteristics of LBA among modern mobile users, but also provide valuable references for the design, evaluation, and improvement of QoE-aware mobile applications and services.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes