Sociometrics and Human Relationships

Peter A. Gloor

• Publisher: Emerald Publishing Limited
• Year: 2017
• ISBN:
  9781787147256
• Topic: Business
• Subtopic: Digital Marketing
• Index: Business

Sociometrics and Human Relationships translates the latest academic research into practical business strategies and techniques as well as actionable insights, providing a wealth of examples for social network analysis and predicting trends. Gloor illustrates how to improve organizational performance by optimizing communication and collaboration through email. Based on Collaborative Innovation Networks courses which have been taught for over a decade to students forming virtual teams across a number of universities, Gloor shows readers how to leverage virtual collaborative creativity in the Internet age, and helps them understand and apply the dynamics of online communication via a variety of tools. Gloor has also created a tool that analyses all types of social media such as: Twitter, Wikipedia, online blogs and Facebook as well as email or Skype logs to predict election outcomes, perception and strength of brands, customer and employment satisfaction, or fraudulent behavior. Gloor explains how to use his tool, Condor, to visualize, monitor and manage brands, products and topics online, as well as analyzing organizations through their email networks.

1

INTRODUCTION

Imagine being able to spot if a customer is becoming really unhappy with your product and service — and do something about it before they actually leave you.

Imagine finding out what the constituency of a politician or political party really thinks.

Imagine finding out what your customers love and hate about your product.

Imagine being able to identify your most creative employees, your external innovators, and lead users — and help them become even more creative.

Imagine being able to predict who wants to leave your company, your department, or your project team — and not just identify them, but help them become happy and motivated workers again.

Imagine identifying potentially fraudulent or risky behavior among your employees before they actually commit anything illegal.

If you are looking for answers to these and similar questions, read on. This book gives you a framework to analyze your organization from the inside, by mining e-mail, skype, and calendar data, and from the outside, by crunching Twitter, Wikipedia, and blog data.

From your and your organization’s e-mail, skype, and calendar data, you can:

• – Find out about the happiness of your employees (see Section 9.3).
• – Find out about the satisfaction of your customers (see Section 9.3).
• – Find out who might be leaving your company (see Section 9.3).
• – Find your most creative and motivated employees (see Chapter 10).
• – Find out about the willingness of your employees to take unnecessary risks (see Section 11.3).

From Twitter, Wikipedia, and blog interaction data, you can:

• – Find out about what your customers and prospects really think about your company and your brands (see Chapter 12).
• – Measure the strength of your brand (see Chapter 12).
• – Find out about the demographic profile of the customers and aficionados of your company and brands (see Section 14.3).
• – Forecast the popularity and voter share of a politician (see Section 14.2).
• – Find out about the demographic profile of the voters of a politician (see Section 14.3).

These are just a few use cases that we will address to study how humans communicate and collaborate inside the organization, through e-mail, chat, videoconferencing, and face-to-face communication, and outside on online social media. Better communication leads to better collaboration, which leads to more and better innovation! This book describes algorithms and tools to find and support collaboration within and between organizations. Our approach puts a lens to the organization by mining electronic communications such as e-mail, sociometric badges, telephone, chat, online meeting, Web/videoconferencing, and calendars to make existing communication patterns visible. The Condor software tool, which has been developed over the past decade at the MIT Center for Collective Intelligence and the University of Applied Sciences Northwestern Switzerland, mines these electronic archives and generates a broad range of structural, temporal, and content-based social network metrics which can be used to calculate and forecast all of these real-world insights mentioned above (Figure 1).

Figure 1: Focus of This Book.

This book provides a practical guide to Coolhunting and Coolfarming on online social media. It explains how to “Coolhunt” — to find cool trends by finding the trendsetters on Twitter, Facebook, Wikipedia, blogs, online forums, and e-mail. It also teaches how to optimize your own communication behavior by creating a personal virtual mirror from your own e-mail, skype log, online calendar, or chat log. It then extends this approach to “Coolfarming” an organization by improving collaboration and innovation through finding the best communication behavior to reach a certain goal. It mirrors back to the organization and its current communication behavior by mining its e-mail, phone, Web conferencing, or online calendars. This virtual mirror of communication deficiencies helps the organization to change its communication behavior for better performance and innovation.

The first part of the book explains the theory behind Coolhunting and Coolfarming, the second part provides a series of in-depth hands-on tutorials to analyze online social networks, and the third part introduces Automatic Media Insights COIN Assessment (AMICA), a specific method using Condor applying the procedures and processes introduced in Part II to measure and increase individual and organizational creativity and performance through virtual mirroring. After having worked through the examples, you will be able to improve yours and your organization’s communication for better collaboration and better innovation: First, you will know more about yourself by understanding the social network where you, as an individual, are embedded, through analyzing your mailbox and your Web network. Second, you will be able to understand and optimize the communication network of your organization by analyzing its e-mail and other communication archives. This analysis might increase an organization’s creativity, its employees’ satisfaction, or its sales success. Third, you will be able to identify your best customers, your key competitors, and your possible business partners through your communication patterns and position in online social media such as Twitter, blogs, Facebook, and Wikipedia.

This book is geared toward students and practitioners with a background in management, human resources, marketing, design, sociology, psychology, and the humanities. It includes numerous examples with the user-friendly software tool Condor that analyzes all types of online social networks such as Twitter, Wikipedia, blogs, Facebook, as well as e-mail. The book is a brief and targeted guide with step-by-step instructions, with an objective to deliver immediate actionable insights for anybody interested in analyzing online social networks. It explains how to visualize, track, and manage brands, products, and topics on the Internet through online social media, and to analyze organizations through their e-mail networks. The book translates latest academic research into practical business strategies and techniques. It provides a wealth of examples of how to apply social network analysis (SNA) for the prediction of trends by mining Twitter, Wikipedia, blogs, and Facebook. It also illustrates how to improve organizational performance by optimizing communication and collaboration using individual and organizational e-mail archives.

The book is based on a course on Collaborative Innovation Networks (COINs) that has been taught for the last 12 years to students forming virtual teams participating from universities in Boston, Savannah, Helsinki, Cologne, Brugg, Bamberg, Rome, and Chile,¹ with majors in business, statistics, education, design, computer science, psychology, and sociology. In this course, students use and analyze social media to answer complex questions impacting society. The course teaches students how to leverage virtual collaborative creativity in the Internet age. It helps them understand and apply the dynamics of online communication using e-mail, social media, Twitter, Wikipedia, and the Web. This is done using online SNA with Condor. The examples in this book have been drawn from class projects from this course.

The book includes a free academic license of Condor to analyze dynamic semantic social networks.

1.1. ROADMAP

1.1.1. Part I — Trend Prediction by Analyzing Social Networks

• Chapter 2, Coolfarming Organizations
  This chapter describes the key principles of how innovation can be improved by better collaboration and better communication. It shows how by analyzing social networks at companies through mining online communication archives, such as e-mail, skype, calendars, and phone logs works, and how through virtual mirroring organizational performance can be optimized.
• Chapter 3, Coolhunting and Trend Forecasting on the Web
  This chapter gives an introduction to the key principles of Coolhunting. Coolhunting measures global consciousness by analyzing the wisdom (and madness) of the crowd on Twitter, the (paid) wisdom of experts on blogs and online newspapers, and the wisdom of swarms on Wikipedia, Facebook groups, and online forums.
• Chapter 4, The Six Honest Signals of Collaboration
  This chapter introduces six social indicators of creative collaboration — “the six honest signals” developed by the MIT’s research group where Condor was created over the last 12 years. The indicators are collected and measured through tweets, bloglinks, Wikipedia entries, e-mail archives, and body signals captured through sensors. These “honest signals” are predictive of future creativity, performance, and outcomes of teams. Changing the individual communication behavior to adhere to these six indicators will lead to better communication, collaboration, and more innovative results. The six indicators are central leadership, rotating leadership, balanced contribution, rapid response, honest language, and shared context.
• Chapter 5, Essentials of Social Network Analysis and Statistics
  The chapter gives a short introduction to SNA, which is needed to do a social media analysis. It describes actor-level metrics such as degree and betweenness centrality, contribution index, and path length, as well as group-level metrics such as density, group degree, and group betweenness centrality. It also introduces the basic statistical techniques (t-tests, correlation, regression) illustrated using the KNIME environment, which is described in the appendix, to understand predictive analytics for forecasting organizational variables such as employee satisfaction, personality characteristics, or sales success based on e-mail communication in the organization. The same statistics is needed to analyze online social media such as Twitter to predict friends and foes of politicians, the outcome of elections, or who will win an Oscar.
• Chapter 6, How Ideas Spread in Online Social Networks — Readings
  This chapter briefly presents the insights from 22 key papers that provide the theoretical background for the examples described in Part II. They are structured into theories of information diffusion, how ideas spread on Facebook, how machine learning can be more accurate than human judgment in analyzing online social networks, how stocks and other financial indicators can be predicted from Twitter, Google, and Wikipedia, how demographic information can be mapp...

Table of contents

• Cover
• Title Page
• 1 Introduction
• Part I. Trend Prediction by Measuring Social Networks
• Part II. Analyzing Structure, Dynamics, and Content of Networks with Condor
• Part III. Automatic Media Insights COIN Assessment (AMICA)
• Part IV. Appendix — Useful Machine Learning and Graph Analysis Tools
• Biography
• Index