Richard Zhang¹ and Ang Li², ¹USA, ²California State Polytechnic University, USA

Oftentimes we lose track of the time we take to skim over a website or article online or we are simply curious about the time it might take for us to read over some text. We might also be curious about our attention span based on the length or difficulty of an article. This paper details the development process of an intelligent google chrome extension capable of gathering data from specific articles and processing the data to estimate the amount of time needed to read over an article based on the time it took to read similar or dissimilar articles [10]. This application takes into account the length, readability, average word size, and comparisons to other reading times in order to return the most accurate time predictions. The benefit of this application is improved time management as an accurate prediction of time will be provided.

Chrome-extension, Time management, Machine learning, Web scraping