Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts

Navalpakkam, Vidhya; Jentzsch, LaDawn; Sayres, Rory; Ravi, Srivatsan; Ahmed, Amr; Smola, Alex

doi:10.1145/2488388.2488471

Cited by 86 publications

(70 citation statements)

References 19 publications

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“…Further works showed that eye-mouse coordination [13] and gaze position [18] could be predicted to some extent by mouse movements, also in the context of non-linear layout SERPs [25]. Outside the search domain, [5] showed in a debugging task that mouse cursor behaviour was a significant indication of the level of difficulty and performance, and the observed cursor patterns were found comparable with the gaze patterns.…”

Section: Related Workmentioning

confidence: 98%

Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures

Arapakis

Lalmas

Valkanas

2014

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

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The availability of large volumes of interaction data and scalable data mining techniques have made possible to study the online behaviour for millions of Web users. Part of the efforts have focused on understanding how users interact and engage with web content. However, the measurement of within-content engagement remains a difficult and unsolved task. This is because of the lack of standardised, wellvalidated methods for measuring engagement, especially in an online context. To address this gap, we perform a controlled user study where we observe how users respond to online news in the presence or lack of interest. We collect mouse tracking data, which are known to correlate with visual attention, and examine how cursor behaviour can inform user engagement measures. The proposed method does not use any pre-determined concepts to characterise the cursor patterns. We, rather, follow an unsupervised approach and use a large set of features engineered from our data to extract the cursor patterns. Our findings support the connection between gaze and cursor behaviour but also, and more importantly, reveal other dependencies, such as the correlation between cursor activity and experienced affect. Finally, we demonstrate the value of our method by predicting the outcome of online news reading experiences.

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Section: Related Workmentioning

confidence: 98%

Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures

Arapakis

Lalmas

Valkanas

2014

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

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“…Such data collection se ings are similar to previous studies such as [36]. Meanwhile, we adopt SERP-level satisfaction rather than session-level satisfaction in this paper because most o ine metrics are designed to measure the quality of only one search result page.…”

Section: Figure 1: Data Collection Proceduresmentioning

confidence: 99%

Meta-evaluation of Online and Offline Web Search Evaluation Metrics

Chen

Zhou

Liu

et al. 2017

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

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As in most information retrieval (IR) studies, evaluation plays an essential part in Web search research. Both o ine and online evaluation metrics are adopted in measuring the performance of search engines. O ine metrics are usually based on relevance judgments of query-document pairs from assessors while online metrics exploit the user behavior data, such as clicks, collected from search engines to compare search algorithms. Although both types of IR evaluation metrics have achieved success, to what extent can they predict user satisfaction still remains under-investigated. To shed light on this research question, we meta-evaluate a series of existing online and o ine metrics to study how well they infer actual search user satisfaction in di erent search scenarios. We nd that both types of evaluation metrics signi cantly correlate with user satisfaction while they re ect satisfaction from di erent perspectives for di erent search tasks. O ine metrics be er align with user satisfaction in homogeneous search (i.e. ten blue links) whereas online metrics outperform when vertical results are federated. Finally, we also propose to incorporate mouse hover information into existing online evaluation metrics, and empirically show that they be er align with search user satisfaction than click-based online metrics.

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“…Core to their experience and success is the Search Engine Results Page (SERP), with its presentation and design over the years having been subject to much research. With more complex components now becoming commonplace in modern day Web search engines (such as the information card [5,36] or social annotations [35]), much work however still remains on examining how more traditional SERP components (such as result summaries) are designed and presented to end users.…”

Section: Introductionmentioning

confidence: 99%

A Study of Snippet Length and Informativeness

Maxwell

Azzopardi

Moshfeghi

2017

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

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e design and presentation of a Search Engine Results Page (SERP) has been subject to much research. With many contemporary aspects of the SERP now under scrutiny, work still remains in investigating more traditional SERP components, such as the result summary. Prior studies have examined a variety of di erent aspects of result summaries, but in this paper we investigate the in uence of result summary length on search behaviour, performance and user experience. To this end, we designed and conducted a withinsubjects experiment using the TREC AQUAINT news collection with 53 participants. Using Kullback-Leibler distance as a measure of information gain, we examined result summaries of di erent lengths and selected four conditions where the change in information gain was the greatest: (i) title only; (ii) title plus one snippet; (iii) title plus two snippets; and (iv) title plus four snippets. Findings show that participants broadly preferred longer result summaries, as they were perceived to be more informative. However, their performance in terms of correctly identifying relevant documents was similar across all four conditions. Furthermore, while the participants felt that longer summaries were more informative, empirical observations suggest otherwise; while participants were more likely to click on relevant items given longer summaries, they also were more likely to click on non-relevant items. is shows that longer is not necessarily be er, though participants perceived that to be the case -and second, they reveal a positive relationship between the length and informativeness of summaries and their a ractiveness (i.e. clickthrough rates). ese ndings show that there are tensions between perception and performance when designing result summaries that need to be taken into account.

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Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts

Cited by 86 publications

References 19 publications

Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures

Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures

Meta-evaluation of Online and Offline Web Search Evaluation Metrics

A Study of Snippet Length and Informativeness

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