Upasna Bhandari

Serendipitous Recommendation for Mobile Apps Using Item-Item Similarity Graph

Recommender systems can provide users with relevant items based on each user’s preferences. However, in the domain of mobile applications (apps), existing recommender systems merely recommend apps that users have experienced (rated, commented, or downloaded) since this type of information indicates each user’s preference for the apps. Unfortunately, this prunes the apps which are releavnt but are not featured in the recommendation lists since users have never experienced them. Motivated by this phenomenon, our work proposes a method for recommending serendipitous apps using graph-based techniques. Our approach can recommend apps even if users do not specify their preferences. In addition, our approach can discover apps that are highly diverse. Experimental results show that our approach can recommend highly novel apps and reduce over-personalization in a recommendation list.

Understanding Visual Appeal and Quality Perceptions of Mobile Apps: An Emotional Perspective

In this study we look at user judgments like perceived quality and also visual appeal from an emotional perspective. This is important to examine since unlike existing studies that focus on the cognitive mechanism of first impression judgments, we use aesthetics framework forwarded by Lavie and Tractinsky, and Russells’ circumplex model of emotions to examine the phenomenon. We also try to answer whether aesthetics lead to significant affective responses from users, which then trickle into quality perceptions and visual appeal, which are otherwise considered higher order judgments. Measurement of emotions has mostly been done through subjective evaluation e.g. self-report or survey. We use objective data (electro-dermal activity for arousal and facial electromyography for valence) in addition to subjective data to measure emotions. We design custom mobile app interfaces which users get exposed to achieve effective aesthetic manipulation.

Mobile App Preferences: What Role Does Aesthetics and Emotions Play?

This research-in-progress reports on the development of a NeuroIS measurement model for studying the role of emotions in non-instrumental preferences. We aim at exploring the effects of emotions and aesthetics on users’ preferences for mobile application. The context of mobile apps is interesting because the phenomenon of high initial adoption but very low retention is still unexplained. For this, we aesthetically manipulated mobile apps, and measured subjects’ affective responses. Our approach builds on galvanic skin response (GSR) and surface electromyography of the face.

Getting Interrupted? Design Support Strategies for Learning Success in M-Learning Applications

This study explores how interruption support from a design standpoint can impact learning and resumption success with mobile applications. Building upon memory for goals theory, we propose that metacognitive support and interactive immediacy are two interruption support features that can increase user’s learning and resumption success. We also propose that these effects are moderated by the task complexity that user is achieving with the app. We aim to find a fit between task and feature that will guide developers and designers to support users during interruptions. The proposed hypothesis will be tested with laboratory experiments.

Cognitive Load and Attention for Mobile Applications: A Design Perspective

Aesthetics has been the success factor of Apple products. Despite of knowing aesthetics as a success factor, researchers and practitioners have limited aesthetics to purely defining it without any factors of practicability being instilled to it. Two factors of practicability could be design balance and complexity. To fill the gap of the need for practicability factors to be instilled into the understanding of aesthetics, this studies draws upon the Gestalt theory to examine how design balance and complexity could be applied on mobile app design. As a research in progress, we plan to validate the effects of design balance and complexity empirically.