@inproceedings{a92bf094a07b446b92641f044cc3bfe7,
title = "Assessing media relevance via eye tracking",
abstract = "To ease the problem of data overloading, it is crucial to understand the user behavior when s/he interacts with online contents, or more specifically, a web page containing several entries for further exploration. We devise to estimate the relevance of an entry to the user goal by observing eye movements as implicit feedback. Specifically, this study proposes a framework that assumes eye movement measures can be used to infer a user's cognition. A rating task was conducted in which subjects were required to judge whether an image was relevant to a word. Results showed that the total fixation duration and the fixation count can be used to discriminate between the relevant and irrelevant conditions; in contrast, the first fixation duration cannot. In addition, the subjective rating and relevancy manipulation interacted on the total fixation duration. Converging evidence verifies the assumption we have proposed.",
keywords = "Eye movement, Relevance feedback, Social media",
author = "Yang, {Cheng Ta} and Chang, {Wen Sheng} and Cheng, {Fan Ning} and Teng, {Wei Guang}",
year = "2011",
doi = "10.1109/ASONAM.2011.122",
language = "English",
isbn = "9780769543758",
series = "Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011",
pages = "722--727",
booktitle = "Proceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011",
note = "2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011 ; Conference date: 25-07-2011 Through 27-07-2011",
}