## 1 Introduction  
Electrification has replaced the internal combustion engine, given power to non-powered products, introduced personal means of transportation, and is bringing about a variety of changes in our lives. In various forms, personal mobility devices (PMDs) are being developed for conventional vehicles (e.g., cars, bikes, or kick scooters) or novel vehicles (e.g., self-balancing boards, one-wheels, or hoverboards) [1; 2; 3]. Among these, products such as electric kick scooters enmeshed in the Internet of things (IoT) are rapidly distributed as shared services [4]. Although PMDs have been increasingly distributed due to their advantages of reducing transportation costs and providing convenient means to use information and communication technology (ICT), PMD-related traffic accidents and those caused by product failures are also rapidly on the rise [3; 5; 6; 7]. In the emergency departments of two downtown hospitals in Indiana, 92 patients reported injuries from electric kick scooters in 61 days in 2018, while no injuries from electric kickboards were reported in the same period in 2017 [4]. At a hospital in South Korea, which had more than 100,000 patients annually, the number of PMD-related accidents tripled from 14 in 2016 to 51 in 2017 [6]. Due to the increasing number of accidents, efforts are needed to ensure the safety of PMDs in terms of research, industry, and society. However, existing studies on PMD mainly focus on functional areasor only report the status of PMD-related accidents. [PERSON] and [PERSON] [8] studied the center-of-gravity shifting ability and the patterns of stand-lining-type self-balancing PMD users, and [PERSON] et al. [9] studied how to design PMDs to rotate naturally by analyzing patterns of rotation like how a person walks. [PERSON] et al. [10] studied electric bicycle use in Europe and analyzed risk events to identify the differences between conventional bicycles and electric bicycles, and [PERSON] et al. [11] investigated the risk cases related to PMDs such as electric bicycles and electric scooters, but both studies could be seen as reporting on the phenomenon rather than revealing the cause of the risk and suggesting improvements. However, although many recent studies have been conducted on electric kickboards, most only report accident sites or give medical descriptions of accident situations [1; 4; 6; 7]. Moreover, PMD-related accidents occur even when a product is being charged or carried [12], but most studies address accidents in driving situations. While the proportion of electric kick scooters among PMD products worldwide is considerable, and accidents related to electric kick scooters are increasing, insufficient studies analyzed the users' actual cases of electric kick scooter-related risks. To understand the safety issues and find solutions accordingly, research from a user-centered perspective is needed to explore the factors that hinder safety. Although studies that analyzed actual user behavior in the studies mentioned above, there are lacking studies that comprehensively reflect the environmental factors of PMD use and the product factors of PMDs. Further, to understand users' risk episodes, it is practical to analyze the participants' textual responses describing the risk episodes. However, because electric kickboard users experience various categories of risk episodes, the manual work of reading and analyzing many responses directly had limited success [13; 14; 15; 16; 17]. Therefore, this study collected the actual cases experienced by users to conduct research from the user's perspective, to understand and analyze the context related to the safety of electric kick scooters. We provided an online form for participants to respond to comfortably and then applied text mining to systematically analyze a large number of responses.