Happimetrics Workshop - Measuring Collaboration using SNA and AI


Lappeenranta University of Technology, Lahti Campus, Mukkulankatu 19, Lahti.

Monday October 3 at 9:30 - 17 / A128 and Tuesday October 4 at 9:30 - 12 / D223 and at 12 - 16 / A122



Registration is open until September 25th .
Max. 20 participants. First priority is given to students who complete the course to gain credits.


Peter A. Gloor, MIT Center for Collective Intelligence


This short course will teach participants how combining AI (artificial intelligence) with SNA (Social Network Analysis) enables accurate measurement of teamwork, leading to highly improved collaboration among team members, for example in software teams, healthcare settings, and many other industries.


Knowing what makes you happy will make you happier!  Analyzing people’s communication patterns and making them self-aware by mirroring their behavior back to them in a privacy-respecting way will increase individual happiness and team performance.  This course describes the three key steps to building happiness and better performance through groupflow, starting with how to create happiness by analyzing communication, how to measure happiness, and how to optimize communication for more happiness and better teamwork by mirroring back the measurements to the individual. It is based on 20 years of research from our MIT Collaborative Innovation Networks (COIN) project on leadership, creativity, team building, and positive psychology published in over 250 peer-reviewed scientific papers and hundreds of industry and research projects our team conducted on individual and organizational creativity and performance.

The course is based on the new book “Happimetrics - Leveraging AI to Untangle the Surprising Link Between Ethics, Happiness and Business Success” (draft manuscript here).


Learning Outcomes

  • Understand the basic concepts of groupflow – when teams collaborate at their best through intrinsic motivation and positive stress
  • Understand how to measure communication behavior from Email, Twitter, smartwatch sensors using the Griffin, SocialCompass, and Happimeter tools.
  • Understand how tracking your own communication behavior through virtual mirroring increases business performance and individual satisfaction
  • Understand how to build “entangled” teams by measuring synchronicity among team members using AI (artificial intelligence), SNA (social network analysis), and time series analysis.


Read the "happimetrics" manuscript, and be prepared for in-class discussion in the course. Choose a topic from the list of the 20 topics listed in the detailed program below for a 10-to-15-minute presentation in the course, preparing a few slides for the presentation, and be prepared to lead the discussion in class about your topic. The goal is that all topics will be introduced by students. The duration of each presentation will depend on the number of participants in the course.

Take the personality, ethics, morals, risk taking tests on the Happimeter Web site (FFI, Dospert, Schwartz, Moral, you need to register/login on the Happimeter Website first to be able to take the tests). You can compare that with your values computed from your emotional response to provocative videos.


Complete an online social media analysis on Twitter of your choice with Griffin.

Complete a virtual mirroring/e-mail analysis, analyzing your own mailbox with Griffin.

Both will be explained in the course. 

Detailed program

Detailed Program

Day 1

1.                      Introduction

Introduction to  happimetrics, the AI-based science to measure human emotions for better teamwork and higher organizational performance

2.                      What is Groupflow?

Introduction to flow, the highest state of human productivity, when people work at their best. It extends it to groupflow, where teams reach the highest state of collective performance. It shows how success is the capability to suffer, and that teams need both diversity and similarity in team member composition to reach groupflow.

3.                      The Influence of Morality on Emotions

Describes the interplay between morality and emotions. It shows how our emotional response to external events is dependent on our morals and value system. It explains how controlling our emotions can reduce stress, and introduces the moral value frameworks of Schwartz and Haidt, and the DOSPERT risk taking measurement system.

4.                      Building Blocks of Happiness

Introduction to the link between happiness and business success. It explains what we can do to be liked, and the connection between happiness and showing others respect and compassion. It demonstrates that kindness is more than being nice and discusses personality characteristics that increase longevity and happiness.

5.                      Virtual Tribes

Concept of virtual tribes, whose members live in alternative realities. In particular, it introduces the four key tribes of fatherlanders, nerds, treehuggers, and spiritualists, which directly correspond to the Indian Varna caste system. It also shows how emotional reactions indicate tribe membership. It discusses how collective consciousness is built, and how interaction with other tribe members creates emotional energy for the individual.

6.                      Beeflow, Antflow, and Leechflow

There are three categories of team members, the bees, who create new things, the ants, who try to win at all costs, and the leeches, who will manipulate others for personal gain.  Bees are key for high performing teams operating in groupflow, they will spread positive energy among their team members, while leeches are energy sinks, who will deprive their team members of energy. It is also shown how beeflow starts in childhood, and what we can do to become bees.

7.                      Entanglement is more than collaboration

Concept of entanglement between humans. Entangled humans know what others with whom they are entangled, think, independent of where they are. It shows how entanglement is created, and how entanglement increases happiness and groupflow.  It introduces the characteristics of entangled organizations, synchronization in movement, shared emotions, shared language, shared facial expressions, and shared values.

8.                      Creating Entangled COINs

Introduces Collaborative Innovation Networks (COINs), and how they are the most powerful engine of disruptive innovation. It presents the COIN creation process, inspired by the swarming of bees. It shows how entanglement among COIN members is the key for successful COINs.

9.                      Virtual Mirroring

Introduces the concept of virtual mirroring, showing individuals how they communicate with others, and how they can change their communication behavior to be better team members. The social compass computes the interaction patterns based on electronic communication archives, while the happimeter measures individual happiness and emotions through a smartwatch tracking the body signals of the individual wearing the smartwatch. Creating positive stress will induce groupflow.

10.                    Steps to Entanglement

Introduces six steps for the individual towards building entanglement: intrinsic aligned motivation, diversity mediated by homophily, turn taking, selective entanglement, acknowledgment of the virtual mirror, and increased emotional awareness. It also introduces three steps for the organization, creating weakly connected COINs, creating synchronicity, and knowing the tribes in the organization.

Day 2

11.                    AI makes Emotions Measurable by Aggregating the Wisdom of the Crowd

Shows how computers and the Internet empower us to measure inter-human interaction on a high level of granularity and detail. Sensors combined with AI give the capability to constantly analyze and interpret communication. Wearable technologies, cloud computing, and artificial intelligence measure happiness, wellbeing, workplace satisfaction, and stress, and mirror back these measurements to the individual. This will lead to more connected, collectively aware, entangled team members, and thus to teams collaborating in groupflow.

12.                    AI-Based Interaction Analysis between Humans (and other Living Creatures)

The analysis process to predict human behavior from communication logs through machine learning, NLP, and social network analysis follows four steps. This section outlines how to use these techniques for predicting human behavior by analyzing archives of traces of human-to-human and human-to-other-living-creatures interaction such as email or GPS sensor data. The aim is to find general patterns of human behavior indicative of future actions. Learning about these patterns, and then analyzing past behavior and comparing it with desirable behavior –  “the best against the rest” – will  change future behavior towards better performance and happiness.

13.                    Measuring Social Network Structure

Social Network Analysis” or SNA is the science that makes “networking” measurable. SNA tracks relations between different people through the structure of their network. SNA applies graph theory to determine the strength of interactions between individuals. This section introduces work done in the last twenty years analyzing email and other electronic communication archives using SNA with the Web-based Griffin analysis tool, a Griffin version is freely available. Griffin can be used to create a virtual mirror of one’s own communication behavior by analyzing individual email.

14.                    Measuring Emotions

With what emotions somebody responds to an external trigger is indicative of personality, ethical values, and risk attitudes. Understanding emotions opens the door to improved collaboration. Emotions can be measured in many different ways, looking at facial expressions, body signals of how somebody moves, voice patterns such as the tone of the voice, and at the choice of words somebody uses when communicating with others.

15.                    Measuring Moral Values from Facial Expressions

Facial expressions indicate personality characteristics and ethical and moral values. Facial emotion recognition combined with machine learning automates this process. Because emotional responses predict tribal affiliation, the emotion shown on one’s face in response to an external event predicts personality characteristics and moral values.

16.                    Measuring Moral Values from Email

Moral values and personality characteristics can be computed from honest signals in emails and other interaction archives. Based on a combination of structural and dynamic social network metrics such as degree and betweenness centralities, and oscillation in betweenness centrality, a machine learning model can predict FFI personality characteristics, moral foundations, Schwartz values, and risk-taking attitudes.

17.                    Measuring Influence through Quoting Novel Words

How quickly inventors of new words get others to use their newly created words is an excellent measure for the persuasive power of the inventor. More generally, the speed with which new concepts are picked up by others is an efficient metric for the influence that the inventor of the new concept has within a community. Using Natural Language Processing (NLP) this influence can easily be measured.

18.                    Measuring Entanglement

To measure the flow state in teams, an entanglement metric for email logs of an organization has been defined. It looks at how synchronized the email exchange between two people is. The more they exchange messages in a similar rhythm, the more entangled they are. This metric has been validated in different organizations, finding that selective, focused entanglement of employees is a strong predictor of team creativity, employee satisfaction, employee performance, and customer satisfaction.

19.                    Measuring Tribes

Tribefinder flags the use of similar words in similar contexts through applying deep learning.  It assigns tribal membership based on word usage of individual tribe members on social media. The central tribal dimension of “alternative realities” consists of the four tribes “fatherlanders”, “nerds”, “treehuggers”, and “spiritualist”, complemented by four other dimensions. Tribefinder also includes the bee, ant, and leech tribes, these can be cross-compared with emotional and alternative reality dimensions.

20.                    Building a Social Compass

Just like Google Maps shows where somebody is in the physical world, where they can go, and where the bottlenecks and traffic jams are, the “Social Compass” helps individuals navigate the social landscape of their emotions and the emotions of others to become a better member of a team. It tells individuals how they see others, how others see them, and what they can do to be happier, and more collaborative and productive. The SocialCompass can be used to find the ideal team members, based on their moral and ethical values, based on their personality, and based on their tribes. The same technology can also be used to measure emotions of horses and dogs, and to use plants as biosensors by analyzing their feedback to human movement.


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Credit points

Doctoral students participating in the seminar can obtain  2 credit points. This requires participating and completing the assignments.

Registration fee

This seminar is free-of-charge for Inforte.fi member organization's staff and their PhD students. For others the participation fee is 400 €. The participation fee includes access to the event and the event materials. Lunch and dinner are not included.