Ian Mcculloh
Biographic Data
| ID | 141131 |
|---|---|
| NAME | Ian Mcculloh |
| GIVEN NAMES | Ian |
| FAMILY NAME | Mcculloh |
| SIGNATURE | MCCULLOH I |
| AFFILIATIONS | United States Military Academy |
| ORCID | 0000-0003-2916-3914 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 10 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Isis in Iraq
This study follows the human side of ISIS’s amazing rise and fall in Iraq. It does not do this as a battle-by-battle history of the group, but rather explores how common Iraqis viewed the group, interacted with the group, joined the group, fought in the group, and ultimately suffered under its brutal rule. Specifically, we seek to answer the following questions: What factors conditioned public support and opposition toward ISIS in Iraq? Why did s…
Making social neuroscience less Weird
The large majority of social neuroscience research uses WEIRD populations-participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sampl…
Spectral Analysis of Social Networks to Identify Periodicity
Two key problems in the study of longitudinal networks are determining when to chunk continuoustime data into discrete time periods for network analysis and identifying periodicity in the data. In addition, statistical process control applied to longitudinal social network measures can be biased by the effects of relational dependence and periodicity in the data. Thus, the detection of change is often obscured by random noise. Fourier analysis is…
Social networks and spatial configuration—How office layouts drive social interaction
Detecting Change in Longitudinal Social Networks
Changes in observed social networks may signal an underlying change within an organization, and may even predict significant events or behaviors. The breakdown of a team’s effectiveness, the emergence of informal leaders, or the preparation of an attack by a clandestine network may all be associated with changes in the patterns of interactions between group members. The ability to systematically, statistically, effectively and efficiently detect …
Detecting Change in Longitudinal Social Networks
Changes in observed social networks may signal an underlying change within an organization, and may even predict significant events or behaviors. The breakdown of a team’s effectiveness, the emergence of informal leaders, or the preparation of an attack by a clandestine network may all be associated with changes in the patterns of interactions between group members. The ability to systematically, statistically, effectively and efficiently detect …
Making social neuroscience less Weird
The large majority of social neuroscience research uses WEIRD populations-participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sampl…
Spectral Analysis of Social Networks to Identify Periodicity
Two key problems in the study of longitudinal networks are determining when to chunk continuoustime data into discrete time periods for network analysis and identifying periodicity in the data. In addition, statistical process control applied to longitudinal social network measures can be biased by the effects of relational dependence and periodicity in the data. Thus, the detection of change is often obscured by random noise. Fourier analysis is…
Social networks and spatial configuration—How office layouts drive social interaction
Detecting Change in Longitudinal Social Networks
Changes in observed social networks may signal an underlying change within an organization, and may even predict significant events or behaviors. The breakdown of a team’s effectiveness, the emergence of informal leaders, or the preparation of an attack by a clandestine network may all be associated with changes in the patterns of interactions between group members. The ability to systematically, statistically, effectively and efficiently detect …
Spectral Analysis of Social Networks to Identify Periodicity
Two key problems in the study of longitudinal networks are determining when to chunk continuoustime data into discrete time periods for network analysis and identifying periodicity in the data. In addition, statistical process control applied to longitudinal social network measures can be biased by the effects of relational dependence and periodicity in the data. Thus, the detection of change is often obscured by random noise. Fourier analysis is…
Making social neuroscience less Weird
The large majority of social neuroscience research uses WEIRD populations-participants from Western, educated, industrialized, rich, and democratic locations. This makes it difficult to claim whether neuropsychological functions are universal or culture specific. In this study, we demonstrate one approach to addressing the imbalance by using portable neuroscience equipment in a study of persuasion conducted in Jordan with an Arabic-speaking sampl…
Isis in Iraq
This study follows the human side of ISIS’s amazing rise and fall in Iraq. It does not do this as a battle-by-battle history of the group, but rather explores how common Iraqis viewed the group, interacted with the group, joined the group, fought in the group, and ultimately suffered under its brutal rule. Specifically, we seek to answer the following questions: What factors conditioned public support and opposition toward ISIS in Iraq? Why did s…
Artificial Intelligence (3 works) · Computer Science (3 works) · Psychology (3 works) · Data mining (2 works) · Longitudinal data (2 works) · Mathematics (2 works) · Mental Health Research Topics (2 works) · Process (computing (2 works) · Social media (2 works) · Social network (sociolinguistics (2 works)