The Impact of User Demographics and Task Types on Cross-App Mobile Search
Recent developments in the mobile app industry have resulted in various types of mobile apps, each targeting a different need and a specific audience. Consequently, users access distinct apps to complete their information need tasks. This leads to the use of various apps not only separately, but also collaboratively in the same session to achieve a single goal. Recent work has argued the need for a unified mobile search system that would act as metasearch on users' mobile devices. The system would identify the target apps for the user's query, submit the query to the apps, and present the results to the user in a unified way. In this work, we aim to deepen our understanding of user behavior while accessing information on their mobile phones by conducting an extensive analysis of various aspects related to the search process. In particular, we study the effect of task type and user demographics on their behavior in interacting with mobile apps. Our findings reveal trends and patterns that can inform the design of a more effective mobile information access environment.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Cookie Consent Has Disparate Impact on Estimation Accuracy
Cookies are designed to enable more accurate identification and tracking of user behavior, in turn allowing for more personalized ads and better performing ad campaigns. Given the additional information that is recorded,…
Towards Algorithmic Fidelity: Mental Health Representation across Demographics in Synthetic vs. Human-generated Data
Synthetic data generation has the potential to impact applications and domains with scarce data. However, before such data is used for sensitive tasks such as mental health, we need an understanding of how different demo…
Synthetic Data GenerationIntelligent Tutors Beyond K-12: An Observational Study of Adult Learner Engagement and Academic Impact
Intelligent tutors have proven to be effective in K-12 education, though their impact on adult learners -- especially as a supplementary resource -- remains underexplored. Understanding how adults voluntarily engage with…
Aligning Language Models to User Opinions
An important aspect of developing LLMs that interact with humans is to align models' behavior to their users. It is possible to prompt an LLM into behaving as a certain persona, especially a user group or ideological per…
Open-Ended Question AnsweringAnalyzing the Effects of Annotator Gender across NLP Tasks
Recent studies have shown that for subjective annotation tasks, the demographics, lived experiences, and identity of annotators can have a large impact on how items are labeled. We expand on this work, hypothesizing that…
Natural Language Inference