Anthony Scime
Biographic Data
| ID | 4403601 |
|---|---|
| NAME | Anthony Scime |
| GIVEN NAMES | Anthony |
| FAMILY NAME | Scime |
| SIGNATURE | SCIME A |
| AFFILIATIONS | SUNY Brockport |
| VERIFIED | No |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 38 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 4 |
Comparing Classification Trees to Discern Patterns of Terrorism
Objective Though applied widely in the fields of medicine, finance, ecology, psychology, and computer science, machine learning algorithmic‐based methods are a relatively novel approach to social scientific analysis that have yet to be extensively applied. Yet as we argue in this article, a specific form of algorithmic analysis known as C4.5 classification trees has much to offer social analysis and, specifically, the study of social and politica…
Data Mining
This essay introduces data mining as an analytical technique for novice to professional social and behavioral scientists. It presents data mining, which is also known as, among other things, data analytics and predictive analytics , as an effective tool for researchers who are interested in the analysis of “big data” as well as small, unique data sets. It addresses foundational elements of data mining such as how to avoid “data dredging” and the …
Explaining religious terrorism: A data-mined analysis
What is the relationship between religious liberty and faith-based terrorism? The wider literature on freedom and terrorism has failed to reach a conclusive verdict: some hold that restricting civil liberties is necessary to prevent acts of terrorism; others find that respecting such rights undermines support for terrorist groups, thus making terrorism less likely. This article moves the debate on liberty and terrorism forward by looking specific…
Achieving Democratic Leadership: A Data‐Mined Prescription
Objective To understand what kind of individuals lead particular regimes, this study examines the most influential people in politics, the executives, to uncover the relationship between their characteristics and the type of regime they govern. Methods This article employs data mining with characteristics of executives worldwide against the state's Freedom House ranking. Results Through data mining, the results indicate that while there are still…
Microtargeting and Electorate Segmentation: Data Mining the American National Election Studies
Business marketers widely use data mining for segmenting and targeting markets. To assess data mining for use by political marketers, we mined the 1948 to 2004 American National Elections Studies data file to identify a small number of variables and rules that can be used to predict individual voting behavior, including abstention, with the intent of segmenting the electorate in useful and meaningful ways. The resulting decision tree correctly pr…
Pre-Election Polling: Identifying Likely Voters Using Iterative Expert Data Mining
One often-noted difficulty in pre-election polling is the iden tification of likely voters. Our objective is to build a likely voter model for presidential elections that efficiently balances accuracy and number of questions used. We employ the Iterative Expert Data Mining tech nique and data from the American National Election Studies to identify a small number of survey questions that can be used to classify likely vot ers while maintaining or …
Explaining religious terrorism: A data-mined analysis
What is the relationship between religious liberty and faith-based terrorism? The wider literature on freedom and terrorism has failed to reach a conclusive verdict: some hold that restricting civil liberties is necessary to prevent acts of terrorism; others find that respecting such rights undermines support for terrorist groups, thus making terrorism less likely. This article moves the debate on liberty and terrorism forward by looking specific…
Pre-Election Polling: Identifying Likely Voters Using Iterative Expert Data Mining
One often-noted difficulty in pre-election polling is the iden tification of likely voters. Our objective is to build a likely voter model for presidential elections that efficiently balances accuracy and number of questions used. We employ the Iterative Expert Data Mining tech nique and data from the American National Election Studies to identify a small number of survey questions that can be used to classify likely vot ers while maintaining or …
Comparing Classification Trees to Discern Patterns of Terrorism
Objective Though applied widely in the fields of medicine, finance, ecology, psychology, and computer science, machine learning algorithmic‐based methods are a relatively novel approach to social scientific analysis that have yet to be extensively applied. Yet as we argue in this article, a specific form of algorithmic analysis known as C4.5 classification trees has much to offer social analysis and, specifically, the study of social and politica…
Microtargeting and Electorate Segmentation: Data Mining the American National Election Studies
Business marketers widely use data mining for segmenting and targeting markets. To assess data mining for use by political marketers, we mined the 1948 to 2004 American National Elections Studies data file to identify a small number of variables and rules that can be used to predict individual voting behavior, including abstention, with the intent of segmenting the electorate in useful and meaningful ways. The resulting decision tree correctly pr…
Pre-Election Polling: Identifying Likely Voters Using Iterative Expert Data Mining
One often-noted difficulty in pre-election polling is the iden tification of likely voters. Our objective is to build a likely voter model for presidential elections that efficiently balances accuracy and number of questions used. We employ the Iterative Expert Data Mining tech nique and data from the American National Election Studies to identify a small number of survey questions that can be used to classify likely vot ers while maintaining or …
Microtargeting and Electorate Segmentation: Data Mining the American National Election Studies
Business marketers widely use data mining for segmenting and targeting markets. To assess data mining for use by political marketers, we mined the 1948 to 2004 American National Elections Studies data file to identify a small number of variables and rules that can be used to predict individual voting behavior, including abstention, with the intent of segmenting the electorate in useful and meaningful ways. The resulting decision tree correctly pr…
Explaining religious terrorism: A data-mined analysis
What is the relationship between religious liberty and faith-based terrorism? The wider literature on freedom and terrorism has failed to reach a conclusive verdict: some hold that restricting civil liberties is necessary to prevent acts of terrorism; others find that respecting such rights undermines support for terrorist groups, thus making terrorism less likely. This article moves the debate on liberty and terrorism forward by looking specific…
Achieving Democratic Leadership: A Data‐Mined Prescription
Objective To understand what kind of individuals lead particular regimes, this study examines the most influential people in politics, the executives, to uncover the relationship between their characteristics and the type of regime they govern. Methods This article employs data mining with characteristics of executives worldwide against the state's Freedom House ranking. Results Through data mining, the results indicate that while there are still…
Data Mining
This essay introduces data mining as an analytical technique for novice to professional social and behavioral scientists. It presents data mining, which is also known as, among other things, data analytics and predictive analytics , as an effective tool for researchers who are interested in the analysis of “big data” as well as small, unique data sets. It addresses foundational elements of data mining such as how to avoid “data dredging” and the …
Comparing Classification Trees to Discern Patterns of Terrorism
Objective Though applied widely in the fields of medicine, finance, ecology, psychology, and computer science, machine learning algorithmic‐based methods are a relatively novel approach to social scientific analysis that have yet to be extensively applied. Yet as we argue in this article, a specific form of algorithmic analysis known as C4.5 classification trees has much to offer social analysis and, specifically, the study of social and politica…
Computer Science (5 works) · Law (4 works) · Political science (4 works) · Politics (4 works) · Data mining (3 works) · Data science (3 works) · Sociology (3 works) · Crime Patterns and Interventions (2 works) · Democracy (2 works) · Electoral Systems and Political Participation (2 works)