School of Computational and Integrative Sciences, Jawaharlal Nehru University, New Delhi, 110067, India.
TCS Research, New Delhi, India.
Sci Rep. 2017 Aug 15;7(1):8283. doi: 10.1038/s41598-017-09101-8.
News reports in media contain records of a wide range of socio-economic and political events in time. Using a publicly available, large digital database of news records, and aggregating them over time, we study the network of ethnic conflicts and human rights violations. Complex network analyses of the events and the involved actors provide important insights on the engaging actors, groups, establishments and sometimes nations, pointing at their long range effect over space and time. We find power law decays in distributions of actor mentions, co-actor mentions and degrees and dominance of influential actors and groups. Most influential actors or groups form a giant connected component which grows in time, and is expected to encompass all actors globally in the long run. We demonstrate how targeted removal of actors may help stop spreading unruly events. We study the cause-effect relation between types of events, and our quantitative analysis confirm that ethnic conflicts lead to human rights violations, while it does not support the converse.
媒体新闻报道中记录了各种社会经济和政治事件。我们使用一个公开的、大型的新闻记录数字数据库，随着时间的推移对其进行汇总，从而研究种族冲突和侵犯人权行为的网络。对事件和涉及的行为者进行复杂的网络分析，为参与的行为者、群体、机构，有时甚至国家提供了重要的见解，指出了它们在空间和时间上的长期影响。我们发现，行为者的提及次数、共同行为者的提及次数以及行为者的度和支配地位的分布呈幂律衰减。最有影响力的行为者或群体形成了一个随时间增长的巨大连通组件，预计从长远来看，它将囊括全球所有的行为者。我们展示了如何有针对性地移除行为者，以帮助阻止无序事件的传播。我们研究了事件类型之间的因果关系，我们的定量分析证实了种族冲突会导致侵犯人权行为，但不支持相反的情况。
