Predicting Conflict in Space and Time

By Nils B. Weidmann, Michael D. Ward. 2010

183 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Sociology and Political Science, Soil Science

View Paper: https://www.semanticscholar.org/paper/657fe7e9c5fb46863616a0a512eb9424cc078f7d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Frank Xing
2. Roy E. Welsch
3. Halvard Buhaug
4. Håvard Strand
5. Erik Cambria
6. A. Tøllefsen

In Sociology and Political Science

1. Frank Xing
2. Roy E. Welsch
3. Halvard Buhaug
4. Håvard Strand
5. Erik Cambria
6. A. Tøllefsen

In Soil Science

1. Frank Xing
2. Roy E. Welsch
3. Halvard Buhaug
4. Håvard Strand
5. Erik Cambria
6. A. Tøllefsen

Citations in the corpus

• PRIO-GRID: A unified spatial data structure (2012, methodology): “Asecond set of contributions uses subnational administrative entities as the unit of observation (e.g. Østby, Nordås & Rød, 2009; Weidmann & Ward, 2010).”
• Saving Human Lives: What Complexity Science and Information Systems can Contribute (2014, unknown): “Efforts at finer-grained codification of geopolitical tensions are labor-intensive [96, 97] and costly and limited in time [98, 99].”
• Natural language based financial forecasting: a survey (2017, methodology): “This can be achieved either by following the framework of, for example, Open Information Extraction [5], or leveraging on existing event databases, such as GDELT [61] or ICEWS [121].”