WMDecompose: A Framework for Leveraging the Interpretable Properties of Word Mover’s Distance in Sociocultural Analysis
Mikael Brunila, Jack LaViolette
Abstract
Despite the increasing popularity of NLP in the humanities and social sciences, advances in model performance and complexity have been accompanied by concerns about interpretability and explanatory power for sociocultural analysis.
Topics & Concepts
InterpretabilityComputer scienceNatural language processingPopularityArtificial intelligenceSociocultural evolutionSet (abstract data type)Word (group theory)Social mediaExtrapolationContext (archaeology)Classifier (UML)Sentiment analysisLinguisticsData scienceWorld Wide WebMathematicsSociologyStatisticsPaleontologySocial psychologyPhilosophyBiologyProgramming languageAnthropologyPsychologyTopic ModelingComputational and Text Analysis MethodsMisinformation and Its Impacts