Does Longer Phone Use Always Feel Worse? Examining How Intention and Duration Shape Evaluations of Time UsePrior work has examined how users judge their smartphone use, typically focusing on either usage duration or intention. How these two factors jointly shape such evaluations remains unclear. We conducted a two-week study with 104 participants, who reviewed their screenshots and provided labels of both usage intention and evaluation of time use. Across 73,000 sessions (6.1M screenshots), the relationship between duration and evaluation was initially linear but then bounded: positive evaluations declined and negative ones rose with longer phone use duration but both eventually stabilized, most often judged neutral. Trajectories varied by intention. Entertainment mirrored the overall trend; functional use continually lost positive evaluations, whereas information-seeking became increasingly positive during the first half hour before later declining; messaging-based connections slowly lost positive evaluations, while social media–based connections declined more quickly; finally, “no specific intention” unfolded in phases—from short positive use to regret-prone mid-length episodes to neutral long sessions.2026YTYi-Hua Tsai et al.National Yang Ming Chiao Tung UniversitySmartphone Addiction & Digital WellbeingBehavior Change & Reflection TechnologyData-Driven Personal Decision-MakingCHI
Verifying or Clarifying? User Preferences for Mobile Crowdsourcing in Response to Seemingly Inconsistent Sensor DataIn the realm of smart cities, sensor technologies play a pivotal role in monitoring urban facilities and environments, providing real-time, site-specific information to residents. However, discrepancies often arise in sensor data due to variances in granularity, abstraction, and scope, which can foster uncertainty regarding the actual conditions on-site. This study explores whether, under these circumstances, individuals prefer on-site mobile crowds for verification purposes or for the provision of supplementary contextual information to aid in decision-making. Conducting an online study with 100 participants from our home country, who engaged in a think-aloud process while utilizing smart city sensor data for decision-making, our findings indicate that participants more often (54%) preferred seeking verification over supplementary contextual information (46%). Both pre-existing expectations and the sense of task urgency affected participants' choices between verification and supplementary contextual information. However, we found that the driving factor for seeking supplementary contextual information was not sensor data deviating from pre-existing expectations, but rather the absence of such pre-existing expectations. Our qualitative data also uncovered five primary motivations and four factors influencing the choice of crowdsourced information. Overall, these findings contribute to our understanding of how people leverage on-site mobile crowds to supplement sensor data in the context of smart cities.2025YCYou-Hsuan Chiang et al.Crowdsourcing & Peer ProductionCSCW
From Overwhelmed to Overview: Understanding Smartphone Users' Preferences and Expectations in Relieving Notification Overload via Text SummarizationTo help users manage the overwhelming influx of smartphone notifications, this study explores how large language models (LLMs) can be leveraged to generate notification summaries. We developed an Android application that integrates ChatGPT to summarize notifications and conducted an in-the-wild deployment to examine how users guided the model. To further understand user expectations for LLM-generated summaries, we interviewed 20 participants following a week-long engagement with the app. Our findings reveal five main strategies that users employed in their prompts for generating summaries. Additionally, interviewees expected summaries to prioritize three types of notifications, preferred three levels of information disclosure influenced by content anticipation and perceived criticality, and used three different approaches to synthesizing notifications based on their interrelationships. Finally, interviewees envisioned notification summarization functioning like a virtual assistant, desiring capabilities beyond simple information condensation, including support for task and information management, revisiting archived content, and tracking activities for reflection.2025UCUei-Dar Chen et al.Human-LLM CollaborationNotification & Interruption ManagementMobileHCI
What Social Media Use Do People Regret? An Analysis of 34K Smartphone Screenshots with Multimodal LLMSmartphone users often regret aspects of their phone use, especially social media use. However, pinpointing specific ways in which the design of an interface contributes to regrettable use can be challenging due to the complexity of social media app features and user intentions. We conducted a one-week study with 17 Android users, using a novel method where we passively collected screenshots every five seconds, which we analyzed via a multimodal large language model to understand participants’ usage activity at a fine-grained level. Triangulating this data with data from experience sampling, surveys, and interviews, we found that regret varies based on user intention, with non-intentional and social media use being especially regrettable. Regret also varies by social media activity; participants were most likely to regret viewing algorithmically recommended content and comments. Additionally, participants frequently deviated to browsing social media when their intention was direct communication, which slightly increased their regret. Our findings provide guidance to designers and policy-makers seeking to improve users’ experience and autonomy.2025LGLongjie Guo et al.University of Washington, The Information SchoolExplainable AI (XAI)Social Platform Design & User BehaviorMisinformation & Fact-CheckingCHI
Pinning, Sorting, and Categorizing Notifications: A Mixed-methods Usage and Experience Study of Mobile Notification-management FeaturesLin 等人通过混合方法研究发现，移动通知的固定、排序和分类功能显著影响用户的信息处理效率和使用体验，为通知管理界面设计提供实证依据。2024YLYong-Han Lin et al.Notification & Interruption ManagementUbiComp
"I Want Lower Tone for Work-Related Notifications": Exploring the Effectiveness of User-Assigned Notification Alerts in Improving User Speculation of and Attendance to Mobile NotificationsResearch indicates that smartphone users often speculate about notifications upon sensing their arrival, aiding their decision to attend to them. This speculation, however, relies on the presence of sufficient clues to associate with the notification, which are not always available. To address this challenge, through an experience sampling study, we investigated the effectiveness of delivering user-assigned alerts in influencing users' speculation accuracy, attendance effectiveness, and perceived disturbance. Our findings suggest that while user-assigned alerts enhanced the accuracy of speculation and improved participants’ decisions to attend to notifications, the increased notification awareness sometimes led participants to view their decision to ignore notifications as less favorable. Moreover, we found that sporadic alert delivery disrupted the association between the alert and the notification, leading to no reduction in perceived disturbance nor improvement in speculation accuracy. In assigning alerts to notifications, participants considered five strategies: familiarity, distinctiveness, disturbance, emotional resonance, and dimension representation.2024TCTang-Jie Chang et al.Notification & Interruption ManagementWorkplace Wellbeing & Work StressMobileHCI
Investigating User-perceived Impacts of Contextual Factors on Opportune MomentsIn this exploratory experience sampling method (ESM) research, we examined the perceptions of 74 smartphone users regarding the opportuneness of moments for proceeding through a four-stage notification-response process: the phone generating an alert (Alert), the user roughly glancing at the notification (Glance), engaging with it (Engage), and acting on it (Act). We investigated how the moments perceived as opportune for each of the four stages related to users’ self-reported values of 20 contextual factors, and how these factors influenced users’ perceived opportuneness of the moments for each stage. Our results reveal that Alert and Glance stages were perceived as more distinct, with Alert being influenced by social-environmental related factors and Glance characterized by a lower threshold for what constitutes an opportune moment. The final two stages – Engage and Act – were the most similar to each other. The findings also indicated how the influence of contextual factors on perceived opportuneness of the moments varied across factors, notification types, stages, and how such variation was manifested in the likelihood, valence, and magnitude of their overall influence.2024YLYu-Jen Lee et al.Notification & Interruption ManagementMobileHCI
“I Prefer Regular Visitors to Answer My Questions”: Users’ Desired Experiential Background of Contributors for Location-based Crowdsourcing PlatformThis three-phase study explores the experiential background of contributors to platforms that provide crowdsourced location-related information. Initially, we utilized interviews to understand users' expectations for location-related information and the contributors’ experiential background they believe would enhance this information's utility. We then deployed a survey to identify the top eight sought-after location-information types and their perceived characteristics. Then the concluding online scenario-based study provided quantitative evidence about the interrelationships of eight types of location-related information, ten crucial quality attributes, and aspects of the contributors' experiential background believed to enhance the utility of the descriptions they provide. Notably, although certain experiential background aspects were deemed universally advantageous across all information types, unique connections were identified among specific information types and distinct experiential background aspects seen as augmenting the contributor's descriptions' utility. These insights underline the importance of location-based crowdsourcing platforms incorporating contributors’ experiential background when assigning tasks.2024FLFang-Yu Lin et al.National Yang Ming Chiao Tung UniversityCitizen Science & Crowdsourced DataParticipatory DesignCHI
Scanning or Simply Unengaged in Reading? Opportune Moments for Pushed News Notifications and Their Relationship with Smartphone Users’ Choice of News-reading ModesNews notifications on smartphones provide a convenient way to stay informed, but their delivery timing can influence user engagement. Despite this, research on the impact of notification timing on reading behavior remains limited. Therefore, we developed NewsMoment, a news aggregation app that monitors user reading patterns and sends news notifications. Our experience sampling study with 46 NewsMoment users revealed four distinct reading modes: typical, comprehensive, scanning, and unengaged. Deep reading, encompassing typical and comprehensive modes, more often occurred during self-initiated browsing rather than through pushed news. Interestingly, shallow reading modes - unengaged and scanning - showed varying prevalence, associated triggers, and engagement, despite their similarities. Importantly, unengaged reading persisted regardless of users' perceived moment opportuneness, whereas scanning reading was more common during inopportune moments. These findings suggest that identifying opportune moments for news reading may primarily reduce scanning reading, without substantially impacting unengaged reading.2023CLChen-Chin Lin et al.Social Platform Design & User BehaviorNotification & Interruption ManagementMobileHCI
Not Merely Deemed as Distraction: Investigating Smartphone Users’ Motivations for Notification-InteractionNotifications are commonly considered a distraction when they arrive during a task, and consequently, prior research has consistently sought effective ways of deferring their arrival until task transitions. However, many smartphone users still interact with notifications during tasks. In our qualitative study combining diary study and semi-structured interviews, we examined 34 research participants' motivations for interacting with smartphone notifications at different times, including during tasks. Our findings resulted in a human-notification interaction framework comprised of 12 unique motivations frequently associated with three activity timings for interacting with notifications, including before-task, during-task, and after-task. Notably, participants frequently perceived interaction with notifications as a tool for improving or optimizing task performance, making the most of their time, and promoting personal well-being, rather than only as a distraction. The before-the-task timing, in particular, has received little attention in previous research and deserves more attention as it was related to specific user motivations for notification interaction.2023XCXiJing Chang et al.National Yang Ming Chiao Tung UniversityVisualization Perception & CognitionPrivacy by Design & User ControlNotification & Interruption ManagementCHI
I Like Their Autonomy and Closeness to Me: Uncovering the Perceived Appeal of Social-Media InfluencersThe proliferation of influencers on social-media platforms has drawn considerable research attention, particularly in the field of marketing. Nevertheless, there is limited understanding among HCI and communication researchers of what leads these social-media influencers’ (SMIs’) audiences to favor and choose their content over traditional media. To fill this gap, we conducted semi-structured interviews with 45 SMI audience members. Our findings revealed a total of eight categories of SMIs’ appeals, i.e., factors that made the interviewees favor their content over traditional media. These appeals can further be grouped into three categories: content, presentation, and closeness. In particular, we identified the key role of SMIs’ perceived high autonomy and independence, which led both their content and their presentation styles to be seen as distinct from and more appealing than traditional media. Likewise, four closeness appeals made our participants feel emotionally attached to SMIs, resulting in sustained engagement.2023YCYu-Ling Chou et al.National Yang Ming Chiao Tung UniversityAgent Personality & AnthropomorphismAI Ethics, Fairness & AccountabilitySocial Platform Design & User BehaviorCHI
Multiple Device Users' Actual and Ideal Cross-Device Usage for Multi-Stage Notification-Interactions: An ESM Study Addressing the Usage Gap and Impacts of Device ContextPeople nowadays can use multiple devices to interact with notifications, whether via noticing, glancing, reading, or acting upon them. Prior research has focused on actual usage or on device preferences. However, users’ ideal experience of cross-device notification-interaction might differ from their current practices (due to situational limitations) and/or across the four notification-interaction stages. We therefore conducted an experience-sampling method study with multi-device users to investigate these gaps and the influence of device context. Our results reveal that nearly half of the time, the non-phone devices the participants had ranked as their top preferences for notification-interaction were not actually used, due to the devices’ context. Beyond device context, the participants’ choices of devices for notification-interaction were heavily determined by 1) their preferences that particular notification-interaction stages to take place (or not) on particular devices; and 2) the device on which they had undertaken the former stage.2023FTFang-Ching Tseng et al.National Taiwan University, National Yang Ming Chiao Tung UniversityNotification & Interruption ManagementCHI
Are You Killing Time? Predicting Smartphone Users’ Time-killing Moments via Fusion of Smartphone Sensor Data and ScreenshotsTime-killing on smartphones has become a pervasive activity, and could be opportune for delivering content to their users. This research is believed to be the first attempt at time-killing detection, which leverages the fusion of phone-sensor and screenshot data. We collected nearly one million user-annotated screenshots from 36 Android users. Using this dataset, we built a deep-learning fusion model, which achieved a precision of 0.83 and an AUROC of 0.72. We further employed a two-stage clustering approach to separate users into four groups according to the patterns of their phone-usage behaviors, and then built a fusion model for each group. The performance of the four models, though diverse, yielded better average precision of 0.87 and AUROC of 0.76, and was superior to that of the general/unified model shared among all users. We investigated and discussed the features of the four time-killing behavior clusters that explain why the models’ performance differ.2023YCYu-Chun Chen et al.National Yang Ming Chiao Tung UniversityContext-Aware ComputingCHI
Get Distracted or Missed the Stop? Investigating Public Transit Passengers’ Travel-Based Multitasking Behaviors, Motives, and ChallengesMobile users commonly multitask during travel, but doing so on public transit can be challenging due to the dynamic nature of the environment as well as long-standing lack of infrastructural support. Nevertheless, HCI scholars and practitioners have devoted relatively little attention to developing technology for enhancing travel multitasking. To facilitate such development, we sought to understand travel multitaskers’ practices and challenges while on public transit, and to that end, conducted a multi-methods study that involved shadowing and interviewing 30 of them. We identified four travel-multitasking patterns, characterized by distinct motives that affected these travelers’ multitasking practices, receptivity to environmental stimuli, and task persistence. The two main challenges they encountered during travel multitasking resulted from mutual interference from their tasks and from the dynamic nature of transit environments. Based on these findings, design recommendations for public-transit agencies and mobile services are also provided.2023HLHsinju Lee et al.National Tsing Hua UniversityNotification & Interruption ManagementPublic Transit & Trip PlanningCHI
“Because I’m Restricted, 2–4 PM Unable to See Messages”: Exploring Users’ Perceptions and Likely Practices around Exposing Attention-management Information on IM StatusesAttention-management tools can restrict online communication, but may cause collateral damage to their users’ fulfillment of communication expectations. This paper explores the idea of integrating attention management into instant messaging (IM), by 1) disclosing restriction status via an online status indicator (OSI) to manage contacts’ expectations, and 2) imposing communication limits to reduce communication distraction. We used a speed-dating design method to allow 43 participants to rapidly compare 48 types of OSI restriction in various conversational contexts. We identified two “tug-of-wars” that take place when attention management is integrated into IM apps: one between fulfilling one’s contacts’ expectations and protecting one’s own attention, and the other, between protecting one’s privacy and asserting the justifiability of using communication restrictions. We also highlighted the participants’ desire to be diplomatic for sustaining their positive images and maintaining relational connectedness. Finally, we provide design recommendations for integrating attention management into IM apps.2022YCYu-Ling Chou et al.National Tsing Hua University, National Yang Ming Chiao Tung UniversityNotification & Interruption ManagementCHI
Predicting Opportune Moments to Deliver Notifications in Virtual RealityVirtual reality (VR) has increasingly been used in many areas, and the need to deliver notifications in VR is also expected to increase accordingly. However, untimely interruptions could largely impact the experience in VR. Identifying opportune times to deliver notifications to users allows for notifications to be scheduled in a way that minimizes disruption. We conducted a study to investigate the use of sensor data available on an off-the-shelf VR device and additional contextual information, including current activity and engagement of users, to predict opportune moments for sending notifications using deep learning models. Our analysis shows that using mainly sensor features could achieve 72% recall, 71% precision and 0.86 area under receiver operating characteristic (AUROC); performance can be further improved to 81% recall, 82% precision, and 0.93 AUROC if information about activity and summarized user engagement is included.2022KCKuan-Wen Chen et al.National Yang Ming Chiao Tung UniversityNotification & Interruption ManagementCHI
Why Did You/I Read but Not Reply? IM Users’ Unresponded Read-Receipt Practices and ExplanationsWe investigate instant-messaging (IM) users’ sense-making and practices around read-receipts: a feature of IM apps for supporting the awareness of turn-taking, i.e., whether a message recipient has read a message. Using a grounded-theory approach, we highlight the importance of five contextual factors – situational, relational, interactional, conversational, and personal – that shape the variety of IM users’ sense-making about read-receipts and strategies for utilizing them in different settings. This approach yields a 21-part typology comprising five types of senders’ speculation about why their messages with read-receipts have not been answered; eight types of recipients’ causes/reasons behind such non-response; and four types of senders’ and recipients’ subsequent strategies, respectively. Mismatches between senders’ speculations about un-responded-to read-receipted messages (URRMs) and recipients’ self-reported explanations are also discussed as sources of communicative friction. The findings reveal that, beyond indicating turn-taking, read-receipts have been leveraged as a strategic tool for various purposes in interpersonal relations.2022YCYu-Ling Chou et al.National Tsing Hua University, National Yang Ming Chiao Tung UniversitySocial Platform Design & User BehaviorOnline Identity & Self-PresentationCHI
How to Guide Task-oriented Chatbot Users, and When: A Mixed-methods Study of Combinations of Chatbot Guidance Types and Timings The popularity of task-oriented chatbots is constantly growing, but smooth conversational progress with them remains profoundly challenging. In recent years, researchers have argued that chatbot systems should include guidance for users on how to converse with them. Nevertheless, empirical evidence about what to place in such guidance, and when to deliver it, has been lacking. Using a mixed-methods approach that integrates results from a between-subjects experiment and a reflection session, this paper compares the ef- fectiveness of eight combinations of two guidance types (example-based and rule-based) at four guidance timings (service-onboarding, task-intro, after-failure, and upon-request), as measured by users’ task performance, improvement on subsequent tasks, and subjec- tive experience. It establishes that each guidance type and timing has particular strengths and weaknesses, thus that each type/timing combination has a unique impact on performance metrics, learning outcomes, and user experience. On that basis, it presents guidance-design recommendations for future task-oriented chatbots.2022SYSu-Fang Yeh et al.National Yang Ming Chiao Tung UniversityConversational ChatbotsPrototyping & User TestingCHI
Making Meals Both Appealing and Healthy: A Food Presentation Simulation System``You eat with your eyes first.'' Marcus Gavius Apicius, the insightful first-century Roman gourmand, stated. Although arranging foods in attractive ways can increase one's appetite, creating an aesthetic food presentation is challenging. For instance, users have to cut ingredients into pieces of specific shapes and sizes, while imagining the overall appearance of their desired composition. To overcome such challenges, we introduce a system that assists users to arrange ingredients to present appealing patterns in meals. The system enables them to perform a process of trial-and-error in the simulation prior to creating a real food presentation. Due to machines' high computing power, our automatic simulation provides users with a variety of food presentation results and inspires their creativity accordingly. It also computes the nutritional composition of each simulated food presentation so that both visual quality and health are considered simultaneously. Results demonstrate that the simulated food presentations are visually appealing and could be physically created. Participants who joined the user study also favored our food presentation simulation system.2021LZLi-Hsing Zheng et al.Food Culture & Food InteractionC&C
“Put it on the Top, I’ll Read it Later”: Investigating Users’ Desired Display Order for Smartphone NotificationsSmartphone users do not deal with notifications strictly in the order they are displayed, but sometimes read them from the middle, suggesting a mismatch between current systems’ display order and users’ needs. We therefore used mixed methods to investigate 34 smartphone users’ desired notification display order and related it with users’ self-reported order of attendance. Classifying using these two orders as dimensions, we obtained seven types of notifications, which helped us not only highlight the distinct attributes but understand the implied roles of these seven types of notifications, as well as the implied meaning of display orders. This is especially manifested in our identification of three main mismatches between the two orders. Qualitative findings reveal several meanings that participants attached to particular positions when arranging notifications. We offer design implications for notification systems, including calling for two-dimensional notification layout to support the multi-purpose roles of smartphone notifications we identified.2021TLTzu-Chieh Lin et al.National Chiao Tung University, National Chiao Tung UniversityNotification & Interruption ManagementCHI