Showing posts from May, 2021

2021-05-10: Chronicling the life-cycle of top new stories with StoryGraphBot

Fig. 1: Fig. 1 (Click on image to expand): Story Attention Dynamics chart illustrating the life-cycle of two top news stories from May 18, 2018 -- May 19, 2018. Each line (red or blue) represents a top news story. The x-axis represents time while the y-axis represents the average degree of Connected Components (representation of story). Within our window of observation, the  Santa Fe High School Shooting   story received peak attention on Friday May 18, 2018 at 4:40PM, this attention waned with the lowest point coinciding with the rise of a new story, the  Royal Wedding of Prince Harry and Meghan Markle . News stories are born expected or unexpected, big or small, compete for attention with sibling stories or enjoy the spotlight alone, live short or long lives, and exit through death or hibernation.  Since August 2017, every 10-minutes, StoryGraph has been quantifying the attention given to news stories. In the past three years, we have seen threats of war , hurricanes Harvey / Irma /

2021-05-03: Automated Filtering of Eye Movements Using Dynamic Areas of Interest in Different Granularity Levels

Fig. 1: The Workflow of Object Detection and Segmentation for Dynamic AOI Filtering and Eye Movement Processing. Most of the eye-tracking experiments involve areas of interests (AOIs) for the analysis of eye gaze data. It is because people only attend to a few areas in a given stimulus and an analysis of eye movements within them can provide important clues to the underlying physiological functions supporting the allocation of visual attention resources. For instance, in user interface interaction, the number of fixations within a user interface component indicates the efficiency of finding that component among others. Analysis of eye movements is mostly done within static AOIs though analysis of eye movements using dynamic AOIs, such as in videos, has recently gained traction. One such example is visual and statistical analysis of viewers’ experience using eye movement data on video feeds. One potential application of dynamic AOIs is dynamically controlled magnification around the cen