Quantifying Attentiveness towards Mobile Messaging (MobileHCI ’15)

Social norm has it that people are expected to respond to mobile phone messages quickly. However, notifications may arrive to our mobile phones at any place and any time, which, depending on the concurrent activity, can be disruptive for the user. Hence, research has explored ways to reduce the chance of disrupting users by deferring the delivery […]

Cost Explosion in the Health System

Research projects on eHealth are often motivated by the so-called cost explosion that we are supposed to face in Europe. For example, The Economist Insights writes that “basic problem is the spiralling cost of healthcare” and that “healthcare systems [..] are facing financial ruin“. I used to believe this prediction until a very good book called […]

The Do Not Disturb Challenge (CHI ’15)

Notifications are alerts intended to draw attention to new online content. Traditionally used in text messaging, email clients and desktop instant messengers, notifications are becoming used by all types of applications across all types of computing devices. Today in 2015, we are still living in the ‘wild-west land-grab phase’ of notifications: more and more OSes […]

An In-Situ Study of Mobile Phone Notifications (MobileHCI ’14)

Notifications on mobile phones alert users about new messages, emails, social network updates, and other events. However, little is understood about the nature and effect of such notifications on the daily lives of mobile users. Hence, we conducted a one-week, in-situ study involving 15 mobile phones users, where we collected real-world notifications through a smartphone […]

The fallacy of WhatsApp’s “last seen” status

Last Seen = Fast Response? When sending a message with WhatsApp, senders often check the receivers “last seen” status to judge whether the message will be read soon. It shows when the receiver had last openend the application. “it gives me a timeframe and allows me to estimate when my message will be read” Intuitively, […]

Exporting RandomForest Models to Java Source Code

This post shares a tiny toolkit to export WEKA-generated Random Forest models into light-weight, self-contained Java source code for, e.g., Android. It came out of my need to include Random Forest models into Android apps. Previously, I used to use Weka for Android. However, I did not find a way to export a Random Forest […]

How fast people expect responses to texts and messages

In February 2013, we did a survey across 44 mobile phone users asking two questions: Think about the people you exchange the most messages with via your mobile phone: On average, how fast do they typically respond to one of your messages? On average, how fast do you typically respond to one of their messages? […]

Correlations and Causation

Why Using Your Phone Less Won’t Necessarily Make You Healthier “There is evidence that resisting the pull of your device can lead to healthier living.” This is the conclusion of the article Trying to Live in the Moment (and Not on the Phone) from citing “a recent study by researchers at Kent State University found […]

Large-Scale Evaluation of Call-Availability Prediction (UbiComp ’14)

Roughly 1/3 of all phones calls are not picked up. With this work, we explored whether the called phone can know in advance, whether its user is likely to pick up a call. This would allow to, amongst other things, communicate (non)availability in advance to the call or trigger intelligent muting. Large-Scale Evaluation of Call-Availability […]

Didn’t you see my message?! (CHI ’14)

“Didn’t you see my message?!” For the younger generations, not receiving a timely response to a SMS or message is a major source of irritation and frustration. However, people cannot or do not want to always attend to their phones all the time. What if your phone would infer these situations and communicate them to […]

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