Counting the Unknown Victims of Political Violence

2014 ◽

pp. 139-156

Author(s):

Ann Harrison

Keyword(s):

Human Rights ◽

Data Analysis ◽

Political Violence ◽

Large Scale ◽

Data Sources ◽

Human Rights Violations ◽

Multiple Data Sources ◽

Analysis Group ◽

Human Rights Organizations ◽

Multiple Data

The Benetech Human Rights Data Analysis Group (HRDAG) (http://www.hrdag.org/) analyzes the patterns and magnitude of large-scale human rights violations. Together with local partners, HRDAG collects and preserves human rights data and helps NGOs and other human rights organizations accurately interpret quantitative findings. HRDAG statisticians, programmers, and data analysts develop methodologies to determine how many of those killed and disappeared have never been accounted for - and who is most responsible. This account illustrates how HRDAG pioneered the calculation of scientifically sound statistics about political violence from multiple data sources including the testimony of witnesses who come forward to tell their stories. It describes methodologies that HRDAG analysts have developed to ensure that statistical human rights claims are transparently, demonstrably, and undeniably true.

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Collective violence and the culture of peace: researching the social psychology of memory and social reconciliation

Deusto Journal of Human Rights ◽

10.18543/djhr.2282 ◽

2021 ◽

pp. 11-16

Author(s):

Nekane Basabe ◽

Darío Páez

Keyword(s):

Human Rights ◽

Political Violence ◽

Transitional Justice ◽

Large Scale ◽

Community Intervention ◽

Human Rights Violations ◽

Collective Violence ◽

Psychosocial Effects ◽

Post Conflict ◽

Culture Of Peace

This monograph aims to disseminate the results of various research studies carried out in the field of social and community psychology. The studies focus on efforts to build a culture of peace in post-conflict contexts and societies that have suffered collective and socio-political violence, with multiple and persistent human rights violations. Six studies on the psychosocial effects of transitional justice rituals from Argentina, Colombia, Brazil, Basque country, Chile, and Ecuador compose this issue. This issue presents a series of results regarding the effects of reparation rituals and Truth Commissions, combining different methods and analysis strategies, including general population surveys, newspaper and social media content analysis, community intervention assessments and qualitative documentary analysis. Finally, two review books were included. First, a Peace Psychology Book that explores the implications and difficulties faced by societies that have experienced large-scale collective violence. Second, the problem of human rights violations and how to confront them, socio-political conflicts and the building of a culture of democracy and peace in Latin America are transversal axes of the chapters of this second book.

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making-the-case-investigating-large-scale-human-rights-violations-using-information-systems-and-data-analysis-2000-310-pp

Human Rights Documents online ◽

10.1163/2210-7975_hrd-1193-0121 ◽

2016 ◽

Keyword(s):

Human Rights ◽

Information Systems ◽

Data Analysis ◽

Large Scale ◽

Human Rights Violations

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Identifying Illicit Drug Dealers on Instagram with Large-scale Multimodal Data Fusion

ACM Transactions on Intelligent Systems and Technology ◽

10.1145/3472713 ◽

2021 ◽

Vol 12 (5) ◽

pp. 1-23

Author(s):

Chuanbo Hu ◽

Minglei Yin ◽

Bin Liu ◽

Xin Li ◽

Yanfang Ye

Keyword(s):

Social Media ◽

Drug Users ◽

Large Scale ◽

Illicit Drug ◽

Data Sources ◽

Multimodal Fusion ◽

Severe Problem ◽

Drug Dealer ◽

Multiple Data Sources ◽

Multiple Data

Illicit drug trafficking via social media sites such as Instagram have become a severe problem, thus drawing a great deal of attention from law enforcement and public health agencies. How to identify illicit drug dealers from social media data has remained a technical challenge for the following reasons. On the one hand, the available data are limited because of privacy concerns with crawling social media sites; on the other hand, the diversity of drug dealing patterns makes it difficult to reliably distinguish drug dealers from common drug users. Unlike existing methods that focus on posting-based detection, we propose to tackle the problem of illicit drug dealer identification by constructing a large-scale multimodal dataset named Identifying Drug Dealers on Instagram (IDDIG). Nearly 4,000 user accounts, of which more than 1,400 are drug dealers, have been collected from Instagram with multiple data sources including post comments, post images, homepage bio, and homepage images. We then design a quadruple-based multimodal fusion method to combine the multiple data sources associated with each user account for drug dealer identification. Experimental results on the constructed IDDIG dataset demonstrate the effectiveness of the proposed method in identifying drug dealers (almost 95% accuracy). Moreover, we have developed a hashtag-based community detection technique for discovering evolving patterns, especially those related to geography and drug types.

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