Statistical semantics: methods and applications

This book discusses the application of various statistical methods to texts, rather than numbers, in various fields in behavioral science. It proposes an approach where quantitative methods are applied to data whereas previously such data were analyzed only by qualitative research methods. To emphasize the quantitative aspects of semantics, and the possibilities of conducting scientific interferences, the book introduces the concept of statistical semantics and presents the reader with a subset of techniques found in that domain. More specifically, the book focuses on methods that allow the investigation of semantic relationships between words, based on empirical corpus data. It shows the reader how to apply various statistical methods on texts, for example statistical tests to ascertain whether two sets of text are statistically different, ways to predict variables from text, as well as how to summarize and graphically illustrate texts. Thus, the book presents an accessible hands-on introduction to a selection of techniques, indispensable for cognitive psychologists, linguists, and social psychologists.

Cross Validation Using a Training-Set and a Test-Set

Intro -- Preface -- Preface -- Acknowledgment -- Contents -- Contributors -- Part I: Methods -- Chapter 1: Introduction to Statistical Semantics -- References -- Chapter 2: Creating Semantic Representations -- Vector Space Model -- Feature Hashing -- Random Indexing -- Latent Semantic Analysis -- Non-negative Matrix Factorization -- Explicit Semantic Analysis -- Word Embeddings -- Deep Learning Representations -- Creating Explicit Semantic Representations -- Creating Semantic Representations with Non-linguistic Information -- Evaluating Semantic Representations -- Word Similarity/Relatedness

Verbal Analogies -- Word Intrusion -- Sentiment Analysis -- Challenges: Polysemy, Homograph, Bias and Compounds -- What Does It Mean? -- References -- Chapter 3: Software for Creating and Analyzing Semantic Representations -- Introduction -- Natural Language Processing Toolkit, NLTK -- spaCy -- Pattern -- Polyglot -- MediaWiki Processing Software -- Scikit-Learn -- Word Embedding -- Word2vec -- GloVe -- FastText -- Other Word Embedding Software -- Other Embedding Software -- Gensim -- Deep Learning -- Keras -- Explicit Creation of Semantic Representations -- References

Chapter 4: Semantic Si…