Leadership Analysis and Influence Operations Laboratory (LA/IO)

Understanding leaders and followers to predict and manage change.

About

The Leadership Analysis and Influence Operations Laboratory (LA/IO) is an interdisciplinary laboratory within the College of Emergency Preparedness, Homeland Security and Cybersecurity (CEHC) at the University at Albany.

 

What We Do

We focus on leadership, group and population analysis as carried out in the academic field of Foreign Policy Analysis and by various United States and Allied intelligence agencies.

More specifically, our research attempts to measure aspects of leader, group and population psychology and dispositions from open-source intelligence, including written and verbal communication.

We conduct primarily basic research on the individual differences between leaders and how these differences influence their decision-making and subsequent policy choices.

To support these efforts, we also develop tools to assess individual differences and analyze leader, group and population behavior. 

 

Why We Do It

World leaders (and their followers) have an undeniable impact on global politics and the course of history. Leaders such as Adolf Hitler, Mahatma Gandhi, Mao Zedong, Saddam Hussein, Nelson Mandela, Charles de Gaulle and Martin Luther King Jr. all affected national and global life. 

 

Our Primary Goals

To understand the characteristics of leaders and of their followers to predict and manage change in local, provincial, national and global contexts.

Projects

 

The Textual Assessment of Leaders Individual Differences (TALID) Dataset

The Textual Assessment of Leaders Individual Differences (TALID) dataset is a growing dataset of individual difference scores for more than 700 global leaders.

Scores are included in the dataset for:

  • Leadership Trait Analysis

  • Operational Code Analysis

  • Motive Analysis

  • Conceptual/Integrative Complexity

  • Verbal Behavior Analysis

Researcher: Michael Young

 

Topics Coding Scheme

This project is developing an automated Topics Coding Scheme for use with Profiler Plus to enhance the analyses that can be conducted on leader individual differences and behavior.

The topic categories are based on those used in the U.S. Policy Agendas Project to take advantage of existing hand-coded data for testing and evaluation. 

Researchers: Shao-Yun Tsai (New York State Division of Homeland Security and Emergency Services) and Michael Young

 

Rhetoric and Terrorist Attacks

This project uses survival analysis to assess whether the rhetoric of terrorist groups can be used to predict their next attack. We are currently examining the rhetoric of three terrorist groups in the Middle East but intend to extend the study to additional groups.

Researchers: Natasha Mather, Shilpa Hanchinal and Michael Young

 

Validation of the Conceptual Complexity Coding Scheme for Profiler Plus

This project is validating the Conceptual Complexity Coding Scheme against gold standard human coding, exploring improvements to the coding schemes and assessing its performance.

Journal editors are requiring more information on validity and replication, and this is one of what may be several projects assessing the validity of automated coding schemes that run on Profiler Plus.

Researchers: Cassidy LoSasso and Michael Young

 

Cognitive Mapping Coding Scheme

This project is developing an automated cognitive mapping coding scheme based on the hand coding protocols developed by Femke van Esch.

A previous attempt using machine learning failed and this project will enable direct comparison of the two approaches and perhaps demonstrate the superiority of a rule-based approach for such endeavors.

Researchers: Femke van Esch (Utrecht University), Jeroen Snellens (GreenMont Systems) and Michael Young

 

Russian Language Motive Coding Scheme

Using documents translated into English for the assessment of individual differences greatly limits the number and variety of documents that can be used for analysis and at the same time machine translation systems do not yet have the fidelity to translate often implicit meaning.

In this project we are developing an automated motive coding scheme for the Russian language and hope to use it to analyze individual differences among Russian leaders.

Researchers: Michael Young and Ella Honcharenko (Ukraine)

Methods & Data

 

Methods

LA/IO serves as a dedicated space for activities examining leadership and influence operations using open-source intelligence.

The primary research techniques used are rule-based text analysis, behavioral analysis, cognitive mapping and social network analysis along with appropriate-to-the-project statistical modeling and simulation techniques.

Text analysis and computational modeling involves modeling individuals, simulation of individual decision making, modeling groups and simulation of group decision making.

 

Data

By downloading a LA/IO dataset, you agree to the following terms and conditions:

  • You may use LA/IO datasets for academic research and publication.

  • You will not sell or use LA/IO data as part of any financial profit-making activity.

  • You will cite each dataset as directed.

  • You will not distribute the dataset to any third party without written permission of the LA/IO director.

  • You will secure permission before any dissemination, posting, or other use of LA/IO data that is not covered by the above restrictions.
     

Textual Assessment of Leaders Individual Differences (TALID) Dataset

TALID Version 1 Scores by Document: Cite Young, Michael. D (2023) “Introducing TALID” LA/IO Working paper.

TALID Version 1 Scores by Leader: Cite Young, Michael. D (2023) “Introducing TALID” LA/IO Working paper.

Our Team

Researchers and collaborators at LA/IO come from interdisciplinary backgrounds, such as political science, computer science, philology, public administration and history.

In addition, we partner with other laboratories at CEHC and draw students from a wide variety of undergraduate and graduate programs in information science, emergency management, homeland security, history and public administration.

 

Leadership

Michael D. Young

Michael D. Young

Director, Leadership Analysis and Influence Operations Laboratory (LA/IO)
Assistant Professor, Department of Emergency Management and Homeland Security

Dr. Michael D. Young is a Political Scientist trained in International Relations, Theory and Methods, as well as Political Psychology. He is the President and co-founder of Social Science Automation, Inc. and the Executive for Threat Triage LLC.

Michael is an expert in the field of automated text analysis. He has been recognized for his development of Profiler Plus — a general-purpose platform for automated text coding with a broad range of applications including psychological assessment, media analysis, social network analysis and political analysis — and of WorldView, a program for building and analyzing graphical representations of belief systems in the cognitive mapping tradition.

His research focuses on assessing and forecasting foreign leadership behavior and decision making.

 

Lab Members

Ella Honcharenko

Dr. Ella Honcharenko

Dr. Ella Honcharenko is an independent scholar with numerous articles on Literature of Foreign Countries, on the issues of Consecutive, Simultaneous Interpreting, and Literary Translation.

After completing her term as head of Foreign Languages chair for Humanities at the Ukrainian, Foreign Philology and Study of Art Department, Oles Honchar Dnipro National University, she turned her attention to problems surrounding the communication and translation of terrorism.

Most recently, Ella has joined the Leadership Assessment and Influence Operations Lab at the University at Albany to work on developing automated Russian language coding schemes for motive imagery assessment.

Natasha K. Mather — Department of History, UAlbany

Cassidy LoSasso — Rockefeller College of Public Affairs & Policy, UAlbany

Shilpa Hanchinal — Department of Information Science, UAlbany

 

Undergraduate Research Assistants

Trey Lapham III

Ana Carina Pereira

 

Alumni

Evan Essex

Gustavo De La Torre

Deirdre Neider

Briana Neira

 

Collaborators

Dr. Femke van Esch

Ir. Jereon Snellens