Conflict resolution initial findings #1: which values and norms matter the most when it comes to sharing location?

I’m still quite busy analyzing the large dataset (~1600 cases) collected from the conflict resolution online user study conducted earlier this year. Before delving into detailed model building, and findings related to specific types of normative conflicts, I thought I’d present two simple yet quite clear findings that appeared upon the initial inspection of the data:

1. Which of the five values in the experiment were found to matter the most, in the general sense?

We have asked participants to use a pie chart to indicate, in the general sense, and assuming a role (either a parent or a child), their preference for five human values that we found to matter the most in the location sharing domain. Below was the description we provided for these values.

Friendship: for you, or your family members to build friendships, a social life, and be recognized amongst others in the social circle.

Privacy: for you, or your family members to be free from unwanted outside intrusion, and undesirably shared information.

Safety: for you, or your family members to be free from dangers or harm.

Independence: for you, or your family members to be capable of doing what they need to do without other’s control or support.

Responsibility: for you, or your family members to know and be able to do the tasks they’re expected to do.

The pie chart below shows how, on average, users ranked the importance of these values:


What I find interesting is that (1) the fact that there was a significant preference for some values over others and (2) that privacy, long considered a pivotal value in social data sharing (especially location!), was ranked lowest. Now, the domain of the experiment is indeed family life, so that makes this finding a little less surprising, yet still interesting as privacy ranked last amongst all five values, not just second to safety, the expected winner.

2. Obligations vs. Prohibitions (to share and receive data)?

Throughout the experiment we asked participants to create conflicting normative statements regarding sharing and receiving location, and we then asked them to indicate their preference (and by how much, using a slider), in the case a conflict occurs. Now, a conflict always included an obligation commitment (e.g. I want someone to share/receive data with/from me/somebody else under some circumstances), and a prohibition (e.g. I want someone to not share/receive data with/from me/somebody else under some circumstances). Again, before going into details on predicting user preference using statistical models, another simple yet clear finding presented itself upon early data inspection:


Data here was modified so that all obligations are to the left side (negative values), and all prohibitions are to the right side (positive values). In the experiment itself the order of course was random. We can see that there is a clear tendency for obligations of sharing and receiving data to be preferred to prohibitions. If we make this discrete, obligations were preferred around 63% of the time:


So, and without drawing any detailed conclusion yet, these two simple findings could alone increase prediction accuracy in conflict resolution in location sharing, by quite some margin.

Website for conflict resolution user study is now online!

We have at last finalized the website for the conflict resolution user study mentioned here, and it is online now for anyone to participate. We have also launched a campaign on to add more participants. You can check it out at:

Don’t forget to watch the instructional video(s)!

ICT Open 2015

Presented both a poster and a demo at ICT Open 2015! This is my second participation in ICT Open after the 2012 edition, and this time it was held in De Flint theater, Amersfoort, over the course of two days. There was around 50 or more demos in the hallway, and plenty of interesting talks/events, however I had to stay by my demo (and poster) almost the whole time. Overall, there was plenty of interest especially in my app, and plenty of research/industry contacts made. It was also great to see my supervisor at TU Delft awarded the Dutch prize for ICT in 2014, though unfortunately she couldn’t come to accept it in person. See below the poster, and more photos from the event here.


Brainstorming on some of the privacy models of some location sharing apps

In the effort of trying to create a spectrum of autonomy/accountability for location sharing apps that can be used in the family domain, and place our app on that spectrum as well, I’ve come up with this sharing/receiving analysis for some of the apps that appear to be on the “extreme” sides of the spectrum:


mSpy is an app A can install on B’s phone to send all types of data (including location updates) to A.  B cannot disable the app and may not even be aware it is installed.


Life360 allows users to create and join (or refuse invitations to join) “circles”.

A user can define with which circle their location updates (x minute interval updates of their GPS position) are shared (e.g. yes with family, but not with colleagues) at any time.

(Not sure if relevant in this paper’s context, but 1. The above implies a traceable history, limited to one day backwards for non-premium users, and 2. Users can create locations to get notified when members of certain circles enter those places).

Users can check-in, which means they share their GPS position with all their circles. This cannot be enabled/disabled for different circles (considered to be a voluntary declaration of their whereabouts).

There are other features such as the “panic button” which sends a panic alert (plus text messages and emails) with your location to every person in your circles.

High autonomy for the child, because Life360 cannot oblige them to share any info they do not want to share or join any circles they do not want to join. But it suffers from the same disability as our non-commitment ePartner (e.g. you can’t promote independence without demoting family security).

Swarm (4sq)

  • With Swarm we can make the distinction between “friends”, “venue managers” and “public”.
  • Users have the ability to request friendship and accept (or refuse) friendship requests from others. Users have the following for privacy options:
  • They can select where their check-ins (place-defined check-ins, like cafés or bars) are shared with venue managers (if the check-in happens in their venue) and/or the public (if they are currently in that venue). Check-ins are always shared with friends.
  • Check-ins are not forced to match GPS location (unlike the above two apps)
  • They can enable a “neighborhood locator” which uses GPS-location to reveal location on the neighborhood level to friends at all time (e.g. Manhattan, Scheveningen, etc.) if no recent check-in has been made for a period of time. This is correct info and cannot be manipulated like check-ins.
  • Swarm can post to third party apps (e.g. Facebook and Twitter) where that app’s privacy settings override that of Swarm.

Friends can include you in their check-in, apparently you cannot prevent them from doing so, even if that was an incorrect check-in. Apparently you can only decide whether that check-in will automatically appear on their Facebook or Twitter feed with your name included. (I need to check this item more).


This week I attended the 2014 Normative Multi-Agent Systems conference which took place in Bertinoro, Italy. NORMAS is always interesting for me because it’s a small community where one can have interesting discussions with leading members in this very specialized field. This conference has a unique setup that, every day in the afternoon, discussion groups form (there were four in this edition), each around a certain topic related to normative frameworks.

Aside from that, the location of the conference was quite exquisite: an isolated castle on a hilltop in the region of Bologna. See photos below!

IMAG0438 IMAG0440 IMAG0442

App usability test

We have conducted a usability test using an implementation of the paper prototype on Participants in this test included 2 children (aged 7 and 8), 2 of the their parents, in addition to one more adult volunteer. The test took place in Hendrik-Ido-Ambacht, at a community center.

The test included 6 tasks that each participant had to perform. The tasks were:

  1. Add a user to your Family list.
  2. Remove a user from your Friends list.
  3. Enable sharing locations with the list “Family”.
  4. Perform a Check-in.
  5. Create an agreement (sharing with someone based on a location).
  6. Create an agreement (not receiving from someone based on a time).

In general, the test went pretty well. Most of the participants performed tasks without any wrong actions/clicks. One of the participants (a child) had some trouble finding the agreement menu. One of the adults had trouble constructing the first agreement, but not with the second.

CCS: more qualitative data analysis

Have performed more qualitative data analysis using collected CCS data. Results show that our normative concept can actually model the domain’s requirements pretty well! In the transcribed audio, we found 12 normative statements spoken by parents and children, and our normative concept model (source, target, norm, trigger, expiry, deadline) is capable of expressing 11 out of these 12. Examples include:

Normative statement: parent says, if five minutes pass after the start of class, and a child isn’t there, the school should call the parents.

Expressed through the model: <parent, teacher, obligation(call parent), child not in school after 5 mins, child is in school, ASAP>.



Attended NORMAS 2013 (stands for Normative Multi Agent Systems) conference which took place in the Lorentz Center, Leiden, the Netherlands. Many of the faces were also present at AAMAS earlier this year, but this crowd is much more focused on normative systems. Many interesting philosophical discussions took place in the group sessions in the afternoon, and an idea for a collaborative paper including the group’s members as authors was suggested.

Paper accepted to UMAP 2013 Doctoral Consortium!

Got my paper “Socially Adaptive Electronic Partners for Socio-geographical Support” accepted for the doctoral consortium at 2013 UMAP (User Modeling, Adaptation, and Personalization) conference, which will be held at the Roma Tre University in June. Awesome!

It will be interesting as I will be assigned a “doctoral mentor” from another university, and get input on this document which is meant to give an overview of my research so far and how it needs to develop for the next 3 years.