Week 3: 9/13/2016 - 9/20/2016

This week I wrapped up my evaluation of the study on the research paper, Synthesizing Image Representations of Linguistic and Topological Features for Predicting Areas of Attention. The conclusions we reached were that there seemed to be a more accurate area prediction when a subject was given more time to read the document or if the subject was presented with objectives/tasks before reading. We found that there was very little accurate information gathered on important features for comprehension during the tasks where subjects were given only seconds to read the the text and gather whatever information they could. Jenna also provided us with some information about what iTrace can provide in respect to Stack Overflow, which will be beneficial to our study. She found that pieces of the page are broken up into a certain number of parts, i.e. chunks of text, the title, the code excerpt, comments, votes, etc. iTrace will then return, based on these parts, what part of the page was focused on. So we can use these existing features when implementing our own study. We are also currently evaluating data from a competition that was held in the past on kaggle that we feel is relevant to our study. The competition was to predict the tags on across stack exchange sites (so the dataset includes technical and non-technical questions) only given the text and title of a posting.