Measuring the Collective Mind

Welcome to the MIT/University of Applied Sciences Northwestern Switzerland FHNW/University of Bamberg/University of Cologne/Jilin University Collaborative Innovation Networks (COINs2017) seminar.

Overview

This seminar shows how to measure and track collective consciousness both within organizations, and globally on the Internet using social media analysis. It combines latest insights from social media monitoring, machine learning, and big data. It introduces the concept of “coolhunting” in three information spheres, the crowd – mostly found on Twitter, the experts – found on blogs and Web sites, and the swarm – on Wikipedia and in online forums. It also shows how to do “coolfarming”, tracking and supporting the creation of Collaborative Innovation Networks (COINs) in organizations by analyzing e-mail and other communication archives and providing a mirror of their communication patterns to users. The goal is to improve communication, leading to better collaboration, leading to more innovation.

The degree of collaboration can be measured through six honest signals of collaboration, strong leadership, balanced contribution, rotating leadership, responsiveness, honest sentiment, and shared language. The seminar explains how to implement these concepts using the software tool Condor, developed by the lecturer and his team at MIT. Condor calculates the six honest signals of collaboration, tracking the degree of collective consciousness on online social media such as Twitter, blogs, or Facebook, or corporate e-mail, calendar, and skype archives using dynamic semantic social network analysis and machine learning.

Contents

The seminar describes how to track new trends by coolhunting – finding new trends by finding the trendsetters; and coolfarming – helping the trendsetters getting their idea over the tipping point. It is based on dozens of case studies done with companies around the world, analyzing the new idea creation process through tracking human interaction patterns on three levels:

On the global level, macro- and microeconomic indicators such as the valuation of companies and consumer indices, or election outcomes, are predicted based on social media analysis on Twitter, Blogs, and Wikipedia. On the organizational level, productivity and creativity of companies and teams is measured through extracting 'honest signals' from communication archives such as company e-mail. On the individual level, individual and team creativity is analyzed through face-to-face interaction with sociometric badges and personal e-mail logs.

The seminar also presents the concept of 'Virtual Mirroring', increasing individual and team creativity by analyzing and optimizing the six “honest signals of collaboration”: 'strong leadership', 'rotating leadership', 'balanced contribution', 'fast response', 'honest sentiment', and ‘shared context.’

It introduces the three phases of building your swarm, based on the concept of Collaborative Innovation Networks (COINs), small groups of self-organizing, emergent teams collaborating over the Internet. COINs are leading to larger groups, the Collaborative Learning Networks testing the prototypes of the COIN, and the Collaborative Internet Network spreading the word about the cool products of the COIN.

The seminar consists of two main parts:

1. Coolhunting - finding trends and trendsetter

2. Coolfarming - COIN building by reaching out to the trendsetters, getting them to collaborate, and develop a new product that will change the world.

Goals

In this seminar you will learn how

• the radical innovation process in small teams works
• to find trendsetters and trends on the Internet and social media
• to predict trends using social network analysis und statistical forecasting techniques
• to increase organizational efficiency and creativity through a virtual mirror created of organizational communication archives
• to promote your own cool ideas through viral marketing on the Internet

Course sequence

1. learning the necessary skills through teacher-supported online self-study
2. presenting the state of the art in research in class, and presenting a virtual mirror of oneself in class
3. deciding on a course topic
4. COIN creation (teams must be international)
5. coolhunting using Condor on course topic, connect to international experts
6. collaboration in international team, weekly meetings (team-members must only be present for their own projects)

Course parts

I) Self study of foundations

Skills to be acquired in (teacher-supported) online self-studies

• SNA (introduction and practical example in Condor + MOOC links)
• ONA (introduction and practical example in Condor + MOOC links)
• Trend forecasting (example: election prediction) (introduction and practical example in Condor + MOOC links)
• Statistics (MOOC links)
• Programming & web design (MOOC links)
• COINs, coolhunting and coolfarming (MOOCs developed by Peter)

Skill level will be assessed in exam

II) In class presentations of latest research by student teams

Students present most recent developments of social prediction in class in teams of 2, based on research papers, writing a handout – goals and content structure are given in topic descriptions, students will develop lessons

• Facebook
• Twitter
• ONA
• Stock trend prediction
• Behavioral economics

Presenting a virtual mirror of oneself in class

III) COIN project

• 4-6 team members from at least 2 locations (Cologne, Bamberg, Brugg, Jilin) (transparent selection in Google Docs spreadsheet)
• Topics can be nominated beforehand by participants (but only BEFORE the project phase starts)
• Weekly status meetings (members only need to attend for their own topic)
• Monthly all hand meetings
• Virtual mirror half-way
• Students need to document projects on Website

This is a demanding course, as it combines skills from many interdisciplinary fields:

• Social network analysis
• Using our own tool Condor for analyzing online social networks
• Statistical methods, Data Mining and Filtering
• Software development
• Concept visualization and information modeling

Why You Should Not Take This Course