Directions and Speeds of Mouse Movements on a Website and Reading Patterns: A Web Usage Mining Case Study
30 Jun 2020-pp 129-138
TL;DR: In this paper, the authors focused on mouse movement directions and speeds, and what they indicate, rather than on the mouse cursor position, and found that most mouse movements in the examined usage data are either approximately horizontal or approximately vertical, horizontal mouse movements are more frequent than vertical mouse movements, and horizontal movements to the left and to the right are not equivalent in terms of moving time and speed.
Abstract: Mouse activity is known as an important indicator of user attention and interest on a web page. Many modern commercial web analytics services record and report mouse activity of users on websites. The position of the mouse cursor on the screen is the main source of information, as studies show a correlation between the cursor position during mouse activity and the user's eye gaze. This study focuses on mouse movement directions and speeds, and what they indicate, rather than on the mouse cursor position. Statistical analysis of mouse movements on a technical-educational website, which was selected for this study, sheds light on several interesting patterns. For example, most mouse movements in the examined usage data are either approximately horizontal or approximately vertical, horizontal mouse movements are more frequent than vertical mouse movements, and horizontal movements to the left and to the right are not equivalent in terms of moving time and speed. As this study shows, these statistical findings are related to the reading patterns and behaviors of web users. Associating mouse movements with text reading may potentially highlight content that most users tend to skip, and therefore, might not interest the website audience, and content that many readers read more than once or slowly, meaning it is possibly unclear. This could be useful in locating issues in textual content, in websites in general, and especially in online learning and educational technology applications.
Citations
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30 Jun 2020
TL;DR: This paper discusses the potential and challenges of sub-page web analytics and defines a framework for calculatingSub-page metrics from accumulated in-page user activity data, such as mouse and keyboard events, and proposes potential KPIs that may be effective in highlighting the strengths and weaknesses of individual page parts,such as paragraphs.
Abstract: Web analytics Key Performance Indicators (KPIs) are important metrics used to evaluate websites and web pages against objectives. The power of KPIs is in their simplicity. Every web page can be assessed by numeric KPI values, which can be easily calculated, compared, and tracked over time. KPIs highlight the strengths and weaknesses of individual web pages and significantly help in maintaining, improving, and optimizing websites. Current web analytics metrics and KPIs, in academic studies as well as in commercial tools, relate to entire websites and web pages. This paper advocates extending KPIs use to sub-page elements, such as paragraphs, as an effective way to refine knowledge and leverage web analytics capabilities. We discuss the potential and challenges of sub-page web analytics and define a framework for calculating sub-page metrics from accumulated in-page user activity data, such as mouse and keyboard events. Then we propose potential KPIs that may be effective in highlighting the strengths and weaknesses of individual page parts, such as paragraphs. We use web usage data from a sample website to demonstrate these ideas. This study is the first step towards sub-page web analytics metrics and KPIs. Further work is required in order to gain more knowledge about potential KPIs that are introduced in this work, as well as to explore new methods, metrics, and KPIs.
13 citations
Cites background from "Directions and Speeds of Mouse Move..."
...For example, a high value of Mouse-RL may indicate frequent reading activity [20], which is a good signal that may indicate user interest in the page content [22]....
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19 Jul 2020
TL;DR: In this article, the authors explored pointer assisted reading (PAR), a reading behavior consisting of moving the mouse cursor (also known as the pointer) along sentences to mark the reading position, similarly to finger-pointing when reading a book.
Abstract: This paper explores Pointer Assisted Reading (PAR), a reading behavior consisting of moving the mouse cursor (also known as the pointer) along sentences to mark the reading position, similarly to finger-pointing when reading a book. The study shows that PAR is an uncommon reading technique and examines methods to extract and visualize the PAR activity of web users. An analysis shows that PAR data of real users reveal reading properties, such as speed, and reading patterns, such as skipping and rereading. Eye-tracking is usually used to analyze user reading behaviors. This paper advocates for considering PAR-tracking as a feasible alternative to eye-tracking on websites, as tracking the eye gaze of ordinary web users is usually impractical. PAR data might help in spotting quality issues in the textual content of a website, such as unclear text or content that might not interest the website users, based on analyzing reading properties and patterns (e.g. reading speed, skipping, and rereading). Accordingly, PAR-tracking may have various practical applications in a wide range of fields, and particularly in educational technology, e-learning, and web analytics.
9 citations
25 Oct 2020
TL;DR: A new type of web page heatmap, the Word Attention Heatmap (WAH), is introduced, which visualizes user attention to text words based on mouse movements, which may help in identifying complex words and challenging sentences as part of a process of improving and simplifying textual web content.
Abstract: User attention on web pages is commonly visualized using heatmaps. Substantial mouse activity in an area of a web page may indicate substantial user attention. Accordingly, areas of web pages are painted with hot and cold colors based on the frequency of mouse clicks and movements in these areas. This paper introduces a new type of web page heatmap, the Word Attention Heatmap (WAH), which visualizes user attention to text words based on mouse movements. Naturally, complex words and unclear text may draw more attention and increase reading time, and therefore, may be painted in hotter colors. Consequently, WAHs may help in identifying complex words and challenging sentences as part of a process of improving and simplifying textual web content.
8 citations
Cites background from "Directions and Speeds of Mouse Move..."
...This is expected, as Pointer Assisted Reading (reading with the aid of the mouse) is occasional [16, 18]....
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...The motivation is to focus on mouse movements that may be related to Pointer Assisted Reading, which is reading text with the aid of the mouse (as defined in [16, 18]), i....
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19 Jul 2020
TL;DR: In this paper, a particular pattern of mouse movements, Horizontal Mouse Movements (HMMs), consisting of series of mouse move events in the same horizontal direction, as indicators of users' current interest was investigated.
Abstract: Mouse events are widely used as implicit indicators of user attention on web pages. In this study, we investigated a particular pattern of mouse movements, Horizontal Mouse Movements (HMMs), consisting of series of mouse move events in the same horizontal direction, as indicators of users’ current interest. We formally defined HMMs and analyzed HMM activity on a sample website in English. We distinguished between LTR (Left to Right) HMMs and RTL (Right to Left) HMMs. LTR HMMs (in the reading direction of the sample website) were found to be more frequent than RTL HMMs (in the opposite direction). Then we investigated leaving web pages immediately after HMMs and found that they are much more frequent after an RTL HMM than after an LTR HMM. The difference can be explained by recent studies, which show that mouse movements in the reading direction are related to reading. Because reading indicates current interest in the web page content, the probability of leaving a web page immediately after LTR HMMs is lower. Accordingly, HMMs in the reading direction may serve as user interest indicators in educational technology, online learning, web analytics, and adaptive websites.
5 citations
TL;DR: In this article , a statistical analysis of mouse movements on an online learning website, which was selected for this study, sheds light on several interesting patterns, such as: most mouse movements in the examined usage data are either approximately horizontal or approximately vertical and horizontal mouse movements are more frequent than vertical mouse movements.
1 citations
References
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01 Jan 2001
TL;DR: It was found that the time spent on a pages, the amount of scrolling on a page and the combination of time and scrolling had a strong correlation with explicit interest, while individual scrolling methods and mouse-clicks were ineffective in predicting explicit interest.
Abstract: Recommender systems provide personalized suggestions about items that users will find interesting. Typically, recommender systems require a user interface that can ``intelligently'' determine the interest of a user and use this information to make suggestions. The common solution, ``explicit ratings'', where users tell the system what they think about a piece of information, is well-understood and fairly precise. However, having to stop to enter explicit ratings can alter normal patterns of browsing and reading. A more ``intelligent'' method is to useimplicit ratings, where a rating is obtained by a method other than obtaining it directly from the user. These implicit interest indicators have obvious advantages, including removing the cost of the user rating, and that every user interaction with the system can contribute to an implicit rating.Current recommender systems mostly do not use implicit ratings, nor is the ability of implicit ratings to predict actual user interest well-understood. This research studies the correlation between various implicit ratings and the explicit rating for a single Web page. A Web browser was developed to record the user's actions (implicit ratings) and the explicit rating of a page. Actions included mouse clicks, mouse movement, scrolling and elapsed time. This browser was used by over 80 people that browsed more than 2500 Web pages.Using the data collected by the browser, the individual implicit ratings and some combinations of implicit ratings were analyzed and compared with the explicit rating. We found that the time spent on a page, the amount of scrolling on a page and the combination of time and scrolling had a strong correlation with explicit interest, while individual scrolling methods and mouse-clicks were ineffective in predicting explicit interest.
768 citations
"Directions and Speeds of Mouse Move..." refers background in this paper
...Therefore, many studies have examined analyzing user actions that can be tracked in modern browsers using JavaScript, such as page scrolling and mouse activity, as alternative implicit indicators of user attention [4, 12, 24]....
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31 Mar 2001
TL;DR: It is argued that a mouse could provide us more information than just the x, y position where a user is pointing, which implies that an inexpensive and extremely popular tool can be used as an alternative of eye-tracking systems, especially in web usability evaluation.
Abstract: In this paper, we describe a study on the relationship between gaze position and cursor position on a computer screen during web browsing. Users were asked to browse several web sites while their eye/mouse movements were recorded. The data suggest that there is a strong relationship between gaze position and cursor position. The data also show that there are regular patterns of eye/mouse movements. Based on these findings, we argue that a mouse could provide us more information than just the x, y position where a user is pointing. This implies that we can use an inexpensive and extremely popular tool as an alternative of eye-tracking systems, especially in web usability evaluation. Moreover, by understanding the intent of every mouse movement, we may be able to achieve a better interface for human computer interaction.
339 citations
"Directions and Speeds of Mouse Move..." refers background in this paper
...when a user clicks or moves the mouse [3, 20]....
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05 May 2012
TL;DR: A search study is conducted to determine when gaze and cursor are aligned, and thus when the cursor position is a good proxy for gaze position, and improves the state-of-the-art technique for approximating visual attention with the cursor.
Abstract: Past studies of user behavior in Web search have correlated eye-gaze and mouse cursor positions, and other lines of research have found cursor interactions to be useful in determining user intent and relevant parts of Web pages. However, cursor interactions are not all the same; different types of cursor behavior patterns exist, such as reading, hesitating, scrolling and clicking, each of which has a different meaning. We conduct a search study with 36 subjects and 32 search tasks to determine when gaze and cursor are aligned, and thus when the cursor position is a good proxy for gaze position. We study the effect of time, behavior patterns, user, and search task on the gaze-cursor alignment, findings which lead us to question the maxim that "gaze is well approximated by cursor." These lessons inform an experiment in which we predict the gaze position with better accuracy than simply using the cursor position, improving the state-of-the-art technique for approximating visual attention with the cursor. Our new technique can help make better use of large-scale cursor data in identifying how users examine Web search pages.
196 citations
"Directions and Speeds of Mouse Move..." refers background in this paper
...Previous work has shown a correlation between eye gaze and mouse cursor positions on a screen [7], and the correlation is higher during mouse activity, i....
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...As discussed in section 2, previous work has shown a correlation between eye gaze and mouse cursor positions on a screen [7], and the correlation is higher during mouse activity, i....
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...Accordingly, mouse cursor position information was found to be useful in providing implicit relevance feedback on web search [6, 7, 19, 20], and in evaluating user attention in various other...
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TL;DR: The results suggest that animation in banner ads does not necessarily increase user attention, but that even if a user does not consciously notice a banner ad, the user's attitude toward the brand is influenced.
Abstract: As with all forms of advertising, exposure is a necessary prerequisite for Internet banner ad effectiveness. However, exposure does not guarantee a user's attention, an issue especially relevant to the Internet, where ad avoidance occurs most frequently. And if an ad is noticed, the message may or may not remain in the consumer's memory after cognitive processing. However, even if the advertising message is not consciously remembered, the exposure can be unconsciously processed and subsequently change the user's affective state. To investigate how attention levels influence users, this study uses eye tracking to measure the level of attention that results from an advertisement exposure and explores how different levels of attention influence users in conscious and unconscious ways. Also, we examine the effect of animation-one of the most popular attention-grabbing tools-on attention and how it moderates cognitive processing.
By measuring and analyzing users' actual eye-movement data, we found that animation in banner ads not only attracts less attention than static ads but also reduces the positive effect of attention on memory. In addition, although more than half of the participants could not recognize the advertised brand, the animated banner ad was unconsciously processed and did influence attitudes toward the brand. The results suggest that animation in banner ads does not necessarily increase user attention, but that even if a user does not consciously notice a banner ad, the user's attitude toward the brand is influenced.
166 citations
"Directions and Speeds of Mouse Move..." refers background in this paper
...This ability has been demonstrated in various applications, including in evaluating user attention to ads [15], identifying issues in a user interface [8], assessing web user interest on mobile devices [16], verifying that users pay attention when they authorize permissions [9], detecting user stress [23], and evaluating user enjoyment from online videos [18]....
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TL;DR: This article found that the average silent reading rate for adults in English is 238 words per minute (wpm) for non-fiction and 260 wpm for fiction, and that the difference can be predicted by taking into account the length of the words, with longer words in nonfiction than in fiction.
135 citations
"Directions and Speeds of Mouse Move..." refers background in this paper
...A recent review that examined 190 different studies (17,887 participants) evaluated that most adults read non-fiction English at a rate of 175–300 wpm, with an average of 238 wpm [1]....
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