Natural Language Processing for Corpus Linguistics

Description

LOL the watermark is so embarassing... USE VPN ALL THE TIME! Cover Tilte Page Coypright Page Natural Language Processing for Corpus Linguistics Contents Accessing the Code Notebooks 1 Computational Linguistic Analysis 1.1 Scaling Up Corpus Linguistics 1.2 The Case Studies 1.3 Categorization Problems 1.4 Comparison Problems 1.5 Language in Vector Space 1.6 Ethics: Data Rights 2 Text Classification 2.1 Evaluating Classifiers 2.2 Representing Content 2.3 Representing Structure 2.4 Representing Context 2.5 Representing Sentiment 2.6 Logistic Regression 2.7 Feed-Forward Networks 2.8 Ethics: Implicit Bias 3 Text Similarity 3.1 Categorization and Cognition 3.2 Measuring Corpus Similarity 3.3 Measuring Document Similarity 3.4 Measuring Word Similarity Using Association 3.5 Measuring Word Similarity in Vector Space 3.6 Clustering by Similarity 3.7 Ethics: Model Discrimination 4 Validation and Visualization 4.1 Reporting Results for Political Speech Prediction 4.2 Ensuring Validity Using Box Plots 4.3 Unmasking Pseudonymous Authors Using Line Plots 4.4 Comparing Word Embeddings Using Heat Maps 4.5 Following Linguistic Diversity using Choropleth Maps 4.6 Ethics: Equal Access 5 Conclusions References Acknowledgments Data Availability Statement