More Tech, More Rights? Text Analysis Uncovers Shifting Human Rights Classifications

Human Rights Machine Learning Media Effects Text Analysishuman rights pluralismtaxonomy evolutioncategorical distinctionsrights monitoringComparative Politics @APSR Dataverse

Human rights monitoring via technology reveals an evolving taxonomy. This study examines how increased information density influences the classification of human rights using NLP techniques.

Sources: US State Department reports, Amnesty International publications, and Human Rights Watch documents.

We analyze trends showing growing attention to diverse rights categories over time. Key findings highlight:

Increased Diversity: More distinct rights types being recognized in contemporary reporting.
Sharper Distinctions: Finer-grained categorization replacing earlier broad groupings.
Temporal Shifts: Clear evidence of taxonomy evolution from the 1990s through recent years.

This research provides new insights into how digital tools reshape human rights discourse, bridging political science and computational methods.

Article card for article: Human Rights are (Increasingly) Plural: Learning the Changing Taxonomy of Human Rights from Large-scale Text Reveals Information Effects

Human Rights are (Increasingly) Plural: Learning the Changing Taxonomy of Human Rights from Large-scale Text Reveals Information Effects was authored by Michael Colaresi, Baekkwan Park and Kevin Greene. It was published by Cambridge in APSR in 2020.