when attention is not scarce – detecting boredom from mobile phone usage
TRANSCRIPT
When Attention is not ScarceDetecting Boredom from Mobile Phone Usage
Research
UbiComp ‘15, Osaka, Japan
Martin Pielot
TelefonicaResearch
Tilman Dingler
University of Stuttgart
JoseSan Pedro
TelefonicaResearch
Nuria Oliver
TelefonicaResearch
times square night 2013. chensiyuan. Apr 16, 2013 via Wikipedia. CC BY-SA 4.0
War on
Attention*
* http://www.forbes.com/sites/onmarketing/2012/10/19/the-attention-war/
Revenue per active user$45 in Q1 2014 = 50 cents per day
SocialMediaCube. Yoel Ben-Avraham. Apr 8, 2013 via Flickr. CC BY-ND 2.0
The trade we make:Our attention so they can pay their bills
Our engagement is now defined by push-driven notifications rather than the traditional pull-driven experience. We’re “hunting and pecking” through our app grid a lot less; the apps that notify us (without over-notifying to the point of uninstall) are rewarded with our engagement (and our dollars).
Example: Push-Driven Notifications
‚Attention is a limited resource—a person has only so much of it ‘ [Matthew B. Crawford]
Attention Economy: treating human attention as a scarce commodity[Davenport and Beck, 2001]
times square night 2013. chensiyuan. Apr 16, 2013 via Wikipedia. CC BY-SA 4.0
Wild-West Land-Grab Phase
“Wild West Hotel, Calamity Av., Perry, 0. T., Sept. 93”. National Archives and Records Administration. Public Domain
Overload
“Ahhhhhhh” by Kenny Louie, Jun 06, 2010, via Flickr, CC BY 2.0
From “Banner Blindness: New and Old Findings” by Jakob Nielsen on August 20, 2007
Banner Blindness
Overload
“Ahhhhhhh” by Kenny Louie, Jun 06, 2010, via Flickr, CC BY 2.0
Notification blindness
Wild-West Land-Grab Phase
“Wild West Hotel, Calamity Av., Perry, 0. T., Sept. 93”. National Archives and Records Administration. Public Domain
If the tradeattention for free servicesis to be sustainedwe need to better protect mobile phone users
Boredom as part of the solution
Attention is not always scarce
Show them this photo if someone said technology … . Adam Rifkin. May 21, 2014 via Flickr. CC BY 2.0
Attention is not always scarce
Show them this photo if someone said technology … . Adam Rifkin. May 21, 2014 via Flickr. CC BY 2.0
Boredom displeasure caused by “lack of stimulation” [Fenichel, 1951]
“a bored person is not just someone who does not have anything to do; it’s someone who is actively looking for stimulation” [Eastwood, 2002]
Attention is not always scarce
Show them this photo if someone said technology … . Adam Rifkin. May 21, 2014 via Flickr. CC BY 2.0
Boredom displeasure caused by “lack of stimulation” [Fenichel, 1951]
“a bored person is not just someone who does not have anything to do; it’s someone who is actively looking for stimulation” [Eastwood, 2002]
Mobile phones are a commonly used tool to kill time when bored [Brown et al. 2014]
Attention is not always scarce
Mobile phones are a commonly used tool to fill or kill time when bored [Brown et al. 2014]
Show them this photo if someone said technology … . Adam Rifkin. May 21, 2014 via Flickr. CC BY 2.0
Boredom displeasure caused by “lack of stimulation” [Fenichel, 1951]
“a bored person is not just someone who does not have anything to do; it’s someone who is actively looking for stimulation” [Eastwood, 2002]
If phones knew when their users are killing time
maybe they could suggest them to make better use of the moment
How well can we detect boredom from mobile phone usage patterns?
Borapp – Sensor-Data Collection
Always collected
Only collected if phone in use
Experience Sampling“Right now, I feel bored” [5-point Likert scale]
Min. 6 times per dayPreferably triggered when phone in use
Borapp – Experience Sampling
Data Collection
54 Participantsaged 21 – 46 (M = 30.6) years11 female, 23male, 19 not disclosed
For two weeks in July 2014Over 40M sensor log entries4398 valid self-reports of boredom
Absolute ground truthBored: ratings 3, 4446 (10.1%) instances
Absolute ground truthBored: ratings 3, 4446 (10.1%) instances
Normalized ground truthZ-score per personBored: z > 0.251518 (34.5%) instances-2 -1 0 1 2
0
400
800
1200
1600
2000
Normalized Subjective Boredom, (higher number = more bored than
usual)
Freq
uenc
y
Category Example Feature Explanation
Context Semantic Location Home, work, other, unknown
Demographics Age, gender 38, female
Last Communication Activity
Time last incoming call Time passed since somebody called the participants
Usage (intensity) Bytes received Number of bytes downloaded in the last 5 minutes
Usage (externally triggered) Number of notifications Number of notifications received in the last 5 minutes
Usage (idling) Number of apps Number of apps launched in the last 5 minutes
Usage (type) Most used app App used for the most time in the last 5 minutes.
35 Features, 7 Categories
RQ1: how well can phones detect killing-time boredom events from these usage patterns?
RQ2: which usage patterns are related to killing time with the phone?
RQ3 is the model good enough to be useful?
normalized
absolute
0.0% 20.0% 40.0% 60.0% 80.0% 100.0%
74.6%
82.9%
Model Performance | Random Forest (AUCROC)
normalized
absolute
0.0% 20.0% 40.0% 60.0% 80.0% 100.0%
76.5%
82.5%
74.6%
82.9%
Model Performance (AUCROC) Including Boredom Proneness scores of 22 participants
normalized
absolute
0.0% 20.0% 40.0% 60.0% 80.0% 100.0%
76.5%
82.5%
74.6%
82.9%
Model Performance (AUCROC) Including Boredom Proneness scores of 22 participants
Primary data set
0% 20% 40% 60% 80% 100%0%
20%
40%
60%
80%
100%
34.7%42.8%
48.3%52.1%
56.6%62.4%
66.2%70.1%
74.3%76.3%
Recall
Precision
Precision: 70.1% for 30% recall,
62.4% for
50% recall
Boredom can be detected from phone-usage patterns with an accuracy of ca. 75% to 83% AUCROC
Take Away #1
RQ1: how well can phones detect killing-time boredom events from these usage patterns?
RQ2: which usage patterns are related to killing time with the phone?
RQ3 is the model good enough to be useful?
Recency of communication activity i.e., time since last incoming or outgoing communication;
Recency of communication activity i.e., time since last incoming or outgoing communication;
Phase of the dayi.e., hour of the day, ambient light
Recency of communication activity i.e., time since last incoming or outgoing communication;
Phase of the dayi.e., hour of the day, ambient light
Demographics, i.e., gender and age;
Recency of communication activity i.e., time since last incoming or outgoing communication;
Phase of the dayi.e., hour of the day, ambient light
Demographics, i.e., gender and age;
General usage intensity i.e, phone out of pocket, or time since last phone use …;
Recency of communication activity i.e., time since last incoming or outgoing communication;
Phase of the dayi.e., hour of the day, ambient light
Demographics, i.e., gender and age;
General usage intensity i.e, phone out of pocket, or time since last phone use …;
Intensity of recent usage i.e. # of unlocks, or # of apps launched in last 5 minutes, …
Apps
Co-occur with being bored Co-occur with NOT bored
… and uncategorized apps
Boredom was related to Regency of communication Phase of the day Demographics Intensity and type of phone usage Type of used apps
Take Away #2
RQ1: how well can phones detect killing-time boredom events from these usage patterns?
RQ2: which usage patterns are related to killing time with the phone?
RQ3 is the model good enough to be useful?
Borapp2
Model running on Mobile PhoneUsing primary data set with
Constantly predicts when user is bored on the fly
Suggest Reading Buzzfeed Articles
Data Collection
16 Participants (different from 1st study)aged 18 – 51(M = 39) years13 male, 2 female, rest did not disclose
For two weeks in Feb 2015941 Buzzfeed recommendations48% when predicted bored
Click-ratio
Fraction of times people clicked on notification (Mdn)
8% when not bored20.5% when bored(as inferred by the model)
Difference significantz = -2.102, p = .018
Large effectr = -.543
Engagement-ratio
Fraction of times people spent more than 30 sec reading (Mdn)
4% when not bored15% when bored(as inferred by the model)
Difference significantz = -2.102, p = .018
Large effectr = -.511
When predicted bored, participants were …
More likely to click More likely to read for > 30 seconds
The generic model was powerful enough to create significant, large effects on click- and engagement-ratios
Take Away #3
Application Scenarios
Show them this photo if someone said technology … . Adam Rifkin. May 21, 2014 via Flickr. CC BY 2.0
Recommend content to alleviate boredom
Shield user from non-important interruptions during non-bored times
Suggest useful but not necessarily boredom-curing activities
Encourage embracing boredom
Recommend content to alleviate boredom
Shield user from non-important interruptions during non-bored times
Suggest useful but not necessarily boredom-curing activities
Encourage embracing boredomX
Recommend content to alleviate boredom
Shield user from non-important interruptions during non-bored times
Suggest useful but not necessarily boredom-curing activities
Encourage embracing boredom
Recommend content to alleviate boredom
Shield user from non-important interruptions during non-bored times
Suggest useful but not necessarily boredom-curing activities
Encourage embracing boredom
Being bored is good for you
Why don’t you turn me off?
Recommend content to alleviate boredom
Shield user from non-important interruptions during non-bored times
Suggest useful but not necessarily boredom-curing activities
Encourage embracing boredom
When Attention is not ScarceDetection Boredom from Mobile Phone Usage
Research
Contact: [email protected] | @martinpielot | UbiComp ‘15, Osaka, JapanNuria Oliver
Jose San Pedro
Tilman Dingler
Martin Pielot
MotivationIn general, attention is scarce, hence valuableThread of overload / notification blindnessHowever, boredom is defined is state of seeking stimuli
ContributionsA machine learning model to predict boredom from mobile phone usage patternsAn analysis of usage patterns related to boredomEvidence that people are more likely to engage with suggested content when bored
ApplicationEngage user with proactive recommendations – possibly to alleviate boredomShield from interruptions when not boredSuggest useful, but not necessarily boredom-curing activitiesEncourage to embrace boredom to foster creativity