11 research outputs found
Word Embedding Enrichment for Dictionary Construction: An Example of Incivility in Cantonese
Dictionary-based methods remain valuable to measure concepts based on texts, though supervised machine learning has been widely used in much recent communication research. The present study proposes a semi-automatic and easily implemented method to build and enrich dictionaries based on word embeddings. As an example, we create a dictionary of political incivility that contains vulgarity and name-calling words in Cantonese. The study shows that dictionary-based classification outperforms supervised machine learning methods, including deep neural network models. Furthermore, a small number of random seed words can generate a highly accurate dictionary. However, the uncivil content detected is only weakly correlated with uncivil perceptions, as we demonstrate in a population-based survey experiment. The strengths and limitations of dictionary-based methods are discussed
On Nonequivalence of Several Procedures of Structural Equation Modeling
generalized least squares, incorrect model, incremental fit index, maximum likelihood, noncentrality parameter,
Longitudinal sampling is required to maximize detection of intrahost A/H3N2 virus variants
10.1093/ve/veaa088Virus Evolution62veaa08
A unified approach to exploratory factor analysis with missing data, nonnormal data, and in the presence of outliers
simple structure, standard errors, test statistics, equivariance, invariance, nonnormal data, outliers, missing data,