Despite the numerous ways already available to stalk people via the Internet, Sleepingtime.org came up with yet another method to creep your Twitter-using friends and celebrities.
Based on a Twitter user's tweet patterns and time zone, Sleepingtime.org generates a general time frame to determine their sleeping hours. This is based on their activity and lack of activity on the micro-blogging site.
According to Sleepingtime.org, Trendhunter has sleeping hours from 10pm - 6am. Do you think that's accurate?
Sleep Stalking
Sleepingtime.Org Provides Another Way To Twitter Stalk
Trend Themes
1. Sleep Tracking - Opportunity for disruptive innovation lies in developing advanced sleep tracking technologies that can accurately determine individuals' sleeping patterns based on their online activity and time zone.
2. Social Media Monitoring - Disruptive innovation can be achieved by creating tools and platforms that analyze social media activity to provide insights on individuals' behaviors and habits, such as Sleepingtime.org does for determining sleeping hours based on Twitter usage.
3. Personalized Analytics - There is an opportunity for disruptive innovation in the field of personalized analytics, where algorithms and machine learning can be used to gather data from various sources and provide customized insights, like determining individuals' sleep patterns based on their online activities.
Industry Implications
1. Sleep Technology - The sleep technology industry can embrace disruptive innovation by developing advanced devices and applications that accurately track and analyze individuals' sleep patterns based on their online activities.
2. Social Media Analytics - Disruptive innovation can be pursued in the social media analytics industry by creating tools and algorithms that monitor and analyze users' behaviors and habits to provide valuable insights for various purposes, including sleep pattern determination.
3. Data Analytics - The data analytics industry can explore disruptive innovation opportunities by leveraging data from multiple sources, including social media platforms, to create tailored algorithms that extract valuable information, such as individuals' sleep patterns based on their online activities.