Responsible Terrorism Coverage (ResTeCo) Project New York Times (NYT) Dataset

  • Scott Althaus (Creator)
  • Joseph Bajjalieh (Creator)
  • Marc Jungblut (Creator)
  • Dan Shalmon (Creator)
  • Subhankar Ghosh (Creator)
  • Pradnyesh Joshi (Creator)

Dataset

Description

Terrorism is among the most pressing challenges to democratic governance around the world. The Responsible Terrorism Coverage (or ResTeCo) project aims to address a fundamental dilemma facing 21st century societies: how to give citizens the information they need without giving terrorists the kind of attention they want. The ResTeCo hopes to inform best practices by using extreme-scale text analytic methods to extract information from more than 70 years of terrorism-related media coverage from around the world and across 5 languages. Our goal is to expand the available data on media responses to terrorism and enable the development of empirically-validated models for socially responsible, effective news organizations.
This particular dataset contains information extracted from terrorism-related stories in the New York Times published between 1945 and 2018. It includes variables that measure the relative share of terrorism-related topics, the valence and intensity of emotional language, as well as the people, places, and organizations mentioned.

This dataset contains 3 files:

1. <i>"ResTeCo Project NYT Dataset Variable Descriptions.pdf"</i>
<ul> <li>A detailed codebook containing a summary of the Responsible Terrorism Coverage (ResTeCo) Project New York Times (NYT) Dataset and descriptions of all variables. </li>
</ul>
2. <i>"resteco-nyt.csv"</i>
<ul><li>This file contains the data extracted from terrorism-related media coverage in the New York Times between 1945 and 2018. It includes variables that measure the relative share of topics, sentiment, and emotion present in this coverage. There are also variables that contain metadata and list the people, places, and organizations mentioned in these articles. There are 53 variables and 438,373 observations. The variable "id" uniquely identifies each observation. Each observation represents a single news article. </li>
<li> <b>Please note</b> that care should be taken when using "respect-nyt.csv". The file may not be suitable to use in a spreadsheet program like Excel as some of the values get to be quite large. Excel cannot handle some of these large values, which may cause the data to appear corrupted within the software. It is encouraged that a user of this data use a statistical package such as Stata, R, or Python to ensure the structure and quality of the data remains preserved.</li>
</ul>
3. <i>"README.md"</i>
<ul><li>This file contains useful information for the user about the dataset. It is a text file written in mark down language</li>

</ul>
<b>Citation Guidelines</b>

1) To cite this codebook please use the following citation:

Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project New York Times (NYT) Dataset Variable Descriptions. Responsible Terrorism Coverage (ResTeCo) Project New York Times Dataset. Cline Center for Advanced Social Research. May 13. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-4638196_V1

2) To cite the data please use the following citation:

Althaus, Scott, Joseph Bajjalieh, Marc Jungblut, Dan Shalmon, Subhankar Ghosh, and Pradnyesh Joshi. 2020. Responsible Terrorism Coverage (ResTeCo) Project New York Times Dataset. Cline Center for Advanced Social Research. May 13. University of Illinois Urbana-Champaign. doi: 10.13012/B2IDB-4638196_V1
Date made availableMay 13 2020
PublisherUniversity of Illinois at Urbana-Champaign

Keywords

  • Terrorism, Text Analytics, News Coverage, Topic Modeling, Sentiment Analysis

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