Boredom-Triggered Proactive Recommendations

The business model of many internet-service companies is primarily build around your attention: they offer best-in-class services for free in exchange for the users’ eyeballs, i.e. them paying attention to the contents of the services they offer. They pay for their expenses and generate revenue by selling the attracted attention to companies and individuals who’d like to promote their content.

One of the upcoming frontiers in this battle for the user’s attention are mobile devices. Engagement is now defined by push-driven notifications rather than the traditional pull-driven experience. Recommendations will become proactive and notifications will be one essential path to deliver them.

In this battle, we may be facing the tragedy of the commons: when individual companies behave rationally according to their self-interest by increasing their attempts to seek people’s attention, they behave contrary to the best interests of the whole group by depleting the attentional resources of the user and risk that people develop notification blindness (as an analogy to banner blindness).

Attention is not always scarce

However, attention is not always scarce. For example, when people are bored, attention is abundant, and people often turn to their phones to kill time.

In our recent research on When Attention is not Scarce – Detecting Boredom from Mobile Phone Usage, presented in September 2015 at the ACM International Joint Conference on Pervasive and Ubiquitous Computing, we showed that it is possible to detect phases of boredom from how people use their mobile phones. As part of the same research project, we showed that people are more likely to engage with suggested content when they are bored, as inferred by the detection algorithm.

Boredom-Triggered Proactive Recommendations

This finding opens the door to using boredom as a content-independent trigger for proactive recommendations. Assuming that proactive recommendations delivered via mobile phone notifications will become more common in the future, using boredom as trigger will benefit service providers as well as the end users:
End users will receive fewer recommendations that are triggered during times when they are busy. Service providers can use it to reduce the fraction of unsuccessful recommendations, which, for example, decreases the likelihood that users develop notification blindness towards proactive recommendations.

The results will be presented at the Workshop: Smarttention, Please! Intelligent Attention Management on Mobile Devices — Workshop @ MobileHCI ’15: ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, 2015 to be held from Aug 24 – 27 in Copenhagen, Denmark.

Boredom-Triggered Proactive Recommendations.
Martin Pielot, Linas Baltrunas, and Nuria Oliver.
Smarttention, Please! Intelligent Attention Management on Mobile Devices — Workshop @ MobileHCI, 2015.

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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 of notifications until opportune moments.

nummsgs For most people, the majority of notifications come from messengers, such as WhatsApp or SMS. This type of communication goes along with high this type of communication social expectations. The majority of the people expect people with whom they frequently communicate to respond within a few minutes. Thus, deferral cannot be indefinite: it requires a bound, that is, a maximum delay before the notification is delivered, not matter how disrupting it might be.

But, what is the right bound?
Social expectations suggest a few minutes maximum. However, how likely is it that an opportune moment occurs within 5 minutes?

We collected evidence regarding these questions in our work I’ll be there for you: Quantifying Attentiveness towards Mobile Messaging.

boxhour
This diagram visualizes how attentive people where predicted to be on average for the different hours of the day.
boxday
This diagram visualizes how attentive people where predicted to be on average for the different days of the week.

Over the course of two weeks, we collected more than 55,000 message notifications from 42 mobile phone users. On the basis of this data, we trained our previously described machine-learning model to predict attentiveness. This model uses sensor data from the phone to predict with close to 80% accuracy, whether a mobile phone user will attend to a message within 2 minutes or not.

We used this model to compute each participant’s predicted attentiveness for each minute of the study. In summary, our data shows that people are attentive to messages 12.1 hours of the day, attentiveness is higher during the week than on the weekend, and people are more attentive during the evening. When being inattentive, people return to attentive states within 1-5 minutes in the majority (75% quantile) of the cases.

Consequently, a bound of 5 minutes or less will ensure that bounded deferral strategies are likely to deliver messages in opportune moments, while reducing the likelihood to violate social expectations.

The results are presented at MobileHCI ’15: ACM International Conference on Human-Computer Interaction with Mobile Devices and Services.

Tilman Dingler and Martin Pielot
I’ll be there for you: Quantifying Attentiveness towards Mobile Messaging
MobileHCI ’15: ACM International Conference on Human-Computer Interaction with Mobile Devices and Services. 2015.

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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:

  1. On average, how fast do they typically respond to one of your messages?
  2. On average, how fast do you typically respond to one of their messages?

The results are stunning:

64% of the respondents believe that people with whom they message the most typically respond to their messages immediately or within a few minutes. Only 9% expect responses after more than an hour.

How fast do THEY respond

68% of the respondents believe that they typically respond to people with whom they exchange a lot of messages immediately or within a few minutes. Only 6% typically respond after more than an hour.

How fast do YOU respond

These numbers are notable, because they reflect people’s expectations. If a friend typically responds immediately, it might feel strange when one day s/he doesn’t. Also, if oneself typically responds within minutes, one might start feeling anxious if circumstances prevent to respond to a message for hours.

In another study, the Do Not Disturb Challenge, where people disabled notifications across all devices for a day, we actually had instances where participants did not respond fast enough and friends got angry as a consequence.

Think about how drastic these expectations are: many activities, such as meetings, driving to work, attending classes, last a lot longer than a few minutes – and they require people’s full attention. Hence, people are faced with a choice: text during meetings or from behind the wheel, or violate expectations.

 

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The Do Not Disturb Challenge (CHI ’15)

Do Not Disturb Mode

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 introduce notification centers and more and more apps generate notifications. However, little is known about how the increasing number of notifications affect us.

Hence, in a collaboration between the Scientific Group of Telefonica R&D and Human-Computer Interaction Institute at Carnegie Mellon University, Luz Rello and I envisioned the Do Not Disturb Challenge. As part of challenge, participants disable notifications on their phones, tablets, and computers for a full day.

In December 2014, we rolled out a pilot of the Do Not Disturb Challenge with 12 participants. While participants reacted wildly different to the lack of notifications, for many, it was a strong experience.

The hugest impact was social. People have come to expect timely responses to their messages. Without notifications, many participants felt no longer able to meet these expectations. Some were informing others before the study that they would be less responsive, some kept constantly checking the phone.

At the same time, many participants noted that without the constant interruptions by notifications, they felt more focus, relaxed, and productive. Others realised that not all notifications are the same and deserve the same treatment. For example, many participants felt relieved by the absence of group-chat notifications.

Probably the main take-away so far is that people have very strong and polarized opinions towards (missing) notification alerts. The only consistent findings across the participants was that none of them would keep notifications disabled altogether. Notifications may affect people negatively, but they are essential: can’t live with them, can’t live without them.

The results will be presented at CHI ’15: the ACM Conference on Human Factors in Computing Systems (CHI) to be held from April 18 – 23 in Seoul, South Korea.

Martin Pielot and Luz Rello
The Do Not Disturb Challenge – A Day Without Notifications
CHI EA ’15: Extended abstracts on Human factors in Computing Systems, 2015.

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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 that students who were heavy cellphone users tended to report higher anxiety levels and dissatisfaction with life than their peers who used their phones less often. 

Does this mean you should throw your mobile phone out of the window right now to live a healthier life??

The answer is no.

What we are reading in this except from the article is a classic misinterpretation of causation and correlation.

Let’s assume the findings are universally true and students who use their cellphone a lot report higher anxiety levels and dissatisfaction with life, then there are three possible explanations:

  1. As the article concludes, the use of cellphones indeed increases anxiety and dissatisfaction. In this case, use of cellphone is the cause and anxiety and dissatisfaction the effects.
  2. However, it could as well be true that cause and effect are reversed: anxiety and dissatisfaction turn people into heavy cellphone users.
  3. Finally, there is the possibility of a tertium quid, an unknown third factor that causes both. For example, people who find it more difficult to interact with others directly may prefer to use the phone, and at the same time be more anxious and dissatisfied with life.

Thus, using the phone less may not make anxiety and dissatisfaction disappear.

 

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Ambient Timer – Unobtrusively Reminding Users of Upcoming Tasks with Ambient Light

Alice is working on a report for the head of her department. At the same time, there is a meeting scheduled in thirty minutes, which she has to attend. The Ambient Timer is already illuminating the wall behind her monitor in a low-attention state, so Alice feels confident that she will be reminded of the meeting. A few minutes before the meeting, the status of the ambient light display has changed to a more salient, intense output. While she is still working on her report, she slowly becomes aware of the nearing deadline and starts finishing the paragraph she is currently working on. One minute before the meeting the light has become so salient that it is hard to ignore. Alice stores the document on the server, puts her computer into sleep mode, and arrives at the meeting on time.

ambienttimer

A timer that uses ambient light

The Ambient Timer is a research prototype developed in the Interactive Systems Group of the OFFIS Institute for Information Technology. Its goal is to gently remind information workers about upcoming events. such as illustrated in the scenario above. It uses LED glued to the back of the monitor to illuminate the wall in the peripheral field of vision of the worker.

User Study

With this prototype, we conducted a user study in collaboration with the HCI and Mobile Computing Group of Telefónica Research. We experimentally studied two instances of the Ambient Timer:

  • expo: a gradual change from green to red, becoming exponentially faster, and
  • sinus: a sinusoidal change between red and green which became increasingly faster.

We compared these reminders against two traditional techniques to keep track of appointments:

  • a clock, such as the one in the corner of your computer screen, and
  • a popup alarm, such as when you use Outlook, Lotus Notes, or the OS X Calendar for your appointments.

For the study, we asked participants to copy and correct texts. Meanwhile, a 10-minute timer was running in the background. The task was to finish as many texts as possible in 10 minutes, but without “overshooting”, i.e. having an unfinished text after 10 minutes. In the expo, sinus, and clock conditions, the remaining time was presented by the Ambient Timer or a clock, respectively. In the popup condition, no time was given, but a popup informed the participants 30 seconds before the end of the time limit.

The experiment used a repeated-measures design, i.e. each participant tested each of the four reminder systems in counter-balanced order.

Results

Our results show that participants experienced significantly fewer interruptions when using Ambient Timer in the expo condition, i.e. with an exponential change from green to red, compared to all other reminder techniques in our experiment. Their average typing speed was significantly faster when in this condition, too. Participants ranked this design best, felt most confident using it and preferred it over all other techniques.

Conclusions

This experiment shows that using light in the periphery around the monitor is a great way to provide information workers with information in an ambient way. Used as Ambient Reminder, ambient light might help to structure typical office work, which is often a mix of concentrated desktop work and scheduled meetings and appointments. It allows office worker to avoid to constantly check the clock or be interrupted by alarming popups interrupt.

Publication

The details of the experiment have been published in the 14th IFIP TC13 Conference on Human-Computer Interaction, held in September 2013 in Cape Town, South Africa:

Heiko Müller, Anastasia Kazakova, Martin Pielot, Wilko Heuten and Susanne Boll.
Ambient Reminder: Unobtrusively Reminding Users of Upcoming Tasks with Ambient Light.
INTERACT ’13: 14th IFIP TC13 Conference on Human-Computer Interaction, 2013.

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