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Title: Objective predictors of subjective aesthetic ratings of web pages
Author: Williams, Nicola Kim
ISNI:       0000 0004 5989 8521
Awarding Body: Keele University
Current Institution: Keele University
Date of Award: 2015
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This research is concerned with the effect of visual stimulus on decision-­‐making and opinions, what visual aspects of a page affect very early impressions of web sites, and how this relates to computational methods of prediction and evaluation of web pages. The aim of this study was to discover whether there are identifiable visual attributes of web pages that can be used to predict subjective opinions. This was explored through three separate studies. These consisted of two correlational studies and a categorisation task. Participants were gained through convenience and snowball sampling, and the materials reviewed were two distinct sets of web pages. Cards sorts, laddering and an online data collection tool were used to gather the information. Both qualitative and quantitative analysis was used to explore the information. The visual attributes found to correlate with subjective opinions were inconsistent across the two correlational studies. Study One had a number of limitations that may have contributed to this inconsistency. Concrete findings were that levels of encouragement and discouragement influenced by web pages are on two distinct scales, as, although there is a negative correlation between them, a large number of pages were rated poorly on both scales. The similarity between the card sort and questionnaire results had consistent findings for predictors of low-­‐rated web pages. The findings from the cards sorts also show that users are able to make preference judgements of web pages without being able to understand the content. An application of the findings regarding prediction of low-­‐rated pages would be to create web design optimisation system, enabling web pages to be reviewed computationally. Although this should never replace user testing, it may provide an economical alternative during the early stages of design.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QA75 Electronic computers. Computer science