Papers 16: Understanding Online Behaviors and Experiences
What prompts users to click on news headlines? A clickstream data analysis of the effects of news recency and popularity
1School of Information Management, Wuhan University, China; 2Center for Studies of Information Resources, Wuhan University, China
A new headline nowadays has to compete for readers’ attention and some-times it needs to entice readers to click and read the news article. The peripheral indicators of news headlines would provide visual suggestions for user to decide on which news to read and which to ignore. This study focused on the recency and popularity indicators of online news. For the purpose of revealing the relationships between news recency/popularity and users’ clicking behavior, a 2-month server log file containing 39,990,200 click-stream records from an institutional news site was analyzed in combination with the news recency and popularity information crawled from its homepage. It was found that more recent or more popular news headlines received more clicks. The results have important implications for news providers in creating effective news headlines and in publishing and disseminating news more responsibly. The introduction of unobtrusive clickstream data to user behavior analysis is a major methodological contribution.
Effects of the User-Need State for Online Shopping: Analyzing Search Patterns
National Taiwan Normal University, Taiwan
With the fast growth of e-commerce and the emerging trend of “New Re-tail”—that is, online and offline integration—the important research issues are how to know the best ways to collect and analyze users’ search behaviors online for a streamlined shopping process, and how to set marketing strategies. Accordingly, we proposed a search pattern analytical method to analyze users’ search behavior in the entire shopping process on the target website from the perspective of the users’ need states. We have focused on the recommendation functions (RFs) and the search functions on Taobao.com to evaluate the effectiveness of each RF to support the online shopping process in different user-need states, namely in a goal-oriented or an exploratory-based approach to online shopping. We first adopted zero-order state transition matrices and then used lag sequential analysis (LSA) to derive the significant repeating search patterns. The results show that the goal-oriented shoppers tend to search directly, whereas exploratory shoppers tend to explore the categories of products as their initial RFs. In addition, goal-oriented users have much more simple search paths compared to the exploratory-based users when engaged in online shopping. Furthermore, based on the results of the LSA, there are two typical search patterns for goal-oriented users and one search pattern for the exploratory ones. Interestingly, the results reveal that exploratory-based users are easily stimulated by context even if they have moved to specific stores. The aim of this research is to summarize users’ search paths and patterns with different need states on the website.
How Users Gaze and Experience on Digital Humanities Platform?: A Model of Usability Evaluation
Wuhan University, China, People's Republic of
Digital humanities platform has been developing rapidly. Using eye-tracking in usability evaluation can make a difference in user experience. In this pa-per we propose a gaze-experience model for usability evaluation on digital humanities platform, and select the “Digital Dunhuang” platform as the case study. A user experiment was carried out to verify the application value of the model through a large amount of eye-tracking and user experience data collection and analysis. We found that the features of eye-tracking (such as fixation and saccade) and those of user experience (such as satisfaction, effi-ciency and effectiveness) had correlations. Implications were also put for-ward to improve the usability of digital humanities platform and can be ex-tended to similar platforms.