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Examining Users on News Provider Web Sites: A Review of Methodology

William Gibbs

Journal of Usability Studies, Volume 3, Issue 3, May 2008, pp. 129-148

Article Contents

Behavior identification and sequence analysis

The behavior identification method provided an in-depth level of analysis of user actions. It helped reveal that users engaged in a multitude of actions that may go undetected using more conventional collection methods. Compared to the other methods, it enabled observation of a more comprehensive set of actions (e.g., scrolling, visual scans, cursor scans) and when combined with sequential analysis provided estimates for forecasting behavioral sequences. The primary disadvantages of this method were (a) the amount of time needed to identify and code behaviors. It required a meticulous review of the Morae recordings, which may be prohibitive with larger user groups; (b) while two-event sequences were analyzed in this project and provided useful information about behavior (behavior A is followed by B), complexities of browsing may require analysis of multi-event sequences.

Table 8 presents the methods used including Web Behavior Graphs (WBG). The table identifies the (a) level of analysis afforded by the method, as used in the project; (b) type of user action (e.g., mouse clicks) for which the method facilitated observation; (c) degree of preparation needed to prepared data; (d) time required to analyze data; (e) potential of method to forecast behavior; and (f) extent to which method afforded data visualization. For the behavior identification and sequence analysis method, the time for data preparation will increase dramatically higher numbers of participants. In addition, approaches used to label search trails and tally recurrence rate will determine the amount of time needed for data preparation. To reduce preparation, the author created a program that compiled search trails and recurrences from exported Morae files. However, a significant amount of time was still needed to prepare the files.

Morae offered many useful features for collecting and analyzing observational data. As the level of analysis became more focused, however, additional measures were needed. Given the value of recurrence rate, information seek trails, and WBGs, it would be helpful for programs like Morae to provide researchers capabilities to extract these data in order to pursue deeper levels of analyses as well as to visualize browsing patterns.

Table 8. Characteristics of methods.
Method Level Action Data prep Time Forecast Visualization
Task performance (think aloud) Macro: General behavior Mouse & page events, time Little or none Low No No
Information seeking trails Micro: Browse pattern Page events & sequence Moderate or High High No Yes
Recurrence/URL frequency Macro: Browse pattern Page events Moderate or High Moderate No No
Behavior ID and Sequence analysis Micro: Specific behavior Mouse, scroll, scan, pages, time, etc. High High Yes No
WBG Micro: Browse pattern Page events and sequences High High No Yes

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