A web browser responsive to the user interest level

Abstract

In this paper we present the design of a web browser that is responsive to the user's interest level. The user's interest level is measured via a wearable Neurosky EEG sensor that gives a value of the user's attention level in real time. The current scroll position is used to identify which part of the webpage the user is reading currently. Combining the scroll position and the user's real time attention level, we identify which parts of the webpage, or which website in a list of currently open websites, the user is most interested in. We then make the web browser responsive to the attention level by adding the current webpage to the favorites if the attention level exceeds a threshold, removing a current webpage from the favorites if the attention level goes below a second threshold, generate on-the-fly an automatic index of the portions of the webpage that the user is more interested in from among the currently open tabs and so on. Having a responsive web browser that responds to the user's level of interest or disinterest can increase the user engagement or satisfaction while browsing. It can also be used to display targeted ads within the interesting portions of the webpage or design better web pages by giving the user interest feedback to the web developer. We describe the methodology and web browser architecture, some tests of the approach on different websites and user interfaces for making the web browser more responsive.