Automated Author ProfileChoi, Hyun Jin
Kyunghee University
Choi, Hyun Jin
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Conflicts are complex, dynamic processes wherein the frequency and intensity of violence changes throughout the contest. In this article, we explore the temporal dynamics of two long-term civil wars—DR-Congo and Sudan—to identify systematic and random conditions that lead to changes in civilian targeting. Violence committed by rival political actors, territorial exchange, and the number and addition of violent agents strongly shape the likelihood that civilian targeting events and casualties increase or decrease over time. General and country differences emerge from vector autoregression analysis to suggest that (1) three types of violent agents—rebels, militias, and the government—are locked in spirals of violence where violence against civilians by one actor leads to subsequent violence by another actor; (2) rebels and government forces respond to the other side’s acquisition of contested territory by increasing counterattacks on civilians, specifically in DR-Congo; and (3) increasing numbers of active nonstate agents lead to higher violence rates in the following months. Among these, civilian targeting by rival actors triggers the most follow-on violent events against civilians.
Authors
- Clionadh Raleigh ;
- Choi, Hyun Jin
Our article analyzes how transitioning political institutions create incentives and disincentives for opposition groups to incite different forms of political violence. We argue that variation on two specific parameters of governance—checks and balances and political participation—compels states toward one of the three forms of conflict, including civil wars, political militia, and riots. Using disaggregated data on different types of political violence across Africa from 1997 to 2012, we analyzed two parameters of governance in both count and change models. We also identified high-risk conflict periods. Typical regime types (democracy, autocracy, anocracy) cannot explain manifestations of conflict, as violence occurs in regimes with varying levels of political openness and competition. Opposition groups actively respond to regime transitions, as changes in institutional parameters correlate with shifts into alternative forms of violence within states.
Authors
- Choi, Hyun Jin ;
- Raleigh, Clionadh