Driving the Last Mile: Characterizing and Understanding Distracted Driving Posts on Social Networks

Abstract

In 2015, 391,000 people were injured due to distracted driving in the US. One of the major reasons behind distracted driving is the use of cell-phones, accounting for 14% of fatal crashes. Social media applications have enabled users to stay connected, however, the use of such applications while driving could have serious repercussions - often leading the user to be distracted from the road and ending up in an accident. In the context of impression management, it has been discovered that individuals often take a risk (such as teens smoking cigarettes, indulging in narcotics, and participating in unsafe sex) to improve their social standing. Therefore, viewing the phenomena of posting distracted driving posts under the lens of self-presentation, it can be hypothesized that users often indulge in risk-taking behavior on social media to improve their impression among their peers. In this paper, we first try to understand the severity of such social-media-based distractions by analyzing the content posted on a popular social media site where the user is driving and is also simultaneously creating content. To this end, we build a deep learning classifier to identify publicly posted content on social media that involves the user driving. Furthermore, a framework proposed to understand factors behind voluntary risk-taking activity observes that younger individuals are more willing to perform such activities, and men (as opposed to women) are more inclined to take risks. Grounding our observations in this framework, we test these hypotheses on 173 cities across the world. We conduct spatial and temporal analysis on a city-level and understand how distracted driving content posting behavior changes due to varied demographics. We discover that the factors put forth by the framework are significant in estimating the extent of such behavior.

Effect of Feedback on Drug Consumption Disclosures on Social Media

“…An increasing number of users are getting involved in dangerous social media challenges like the KiKi Challenge (Baghel et al 2018), the Salt and Ice Challenge (Roussel and Bell 2016), the Cinnamon Challenge (Grant-Alfieri, Schaechter, and Lipshultz 2013), Tide Pod Challenge (Murphy 2019), and the Fire Challenge (Ahern, Sauer, and Thacker 2015). (Lamba et al 2020) analyzed public Snapchat data from 173 cities around the world, revealing 23.5% of total 6.4 Million samples were examples of distracted driving. They performed demographic analysis to reveal that young males from the Middle Eastern and Indian subcontinent are more likely to produce distracted driving content.…”

How Gender Affects Motor Vehicle Crashes: A Case Study from San Antonio, Texas

“…Males are more likely to send text messages, use a navigation system, and use a cellphone compared to females, who are more likely to interact with children on the back seat or perform personal grooming while driving [39]. Moreover, male drivers were found to post more distracted driving-related contents of their driving on social media than females [40]. Some studies suggest that the perception of male and female drivers towards distracted driving legislation might differ.…”