This recipe explores how to analyze a corpus for the locations that are mentioned within it. These results can be mapped to visualize the spatial focus of the corpus. This recipe is based on an iPython notebook by Matthew Wilkins.
This recipe uses Python and the NLTK to explore repeating phrases (ngrams) in a text. An ngram is a repeating phrase, where the 'n' stands for 'number' and the 'gram' stands for the words; e.g. a 'trigram' would be a three word ngram.
This recipe helps you explore how to analyze a text based on its parts of speech (e.g. nouns, adjectives, prepositions, etc.).
This recipe uses Python and WordNet to explore meaning in a text.
This recipe shows how to graph data in Python using the Matlablib library.
This recipe shows how to create a basic concordance tool in Python.
This recipe shows how to conduct dictionary-based sentiment analysis on a collection of passages, such as tweets or reviews. It uses pre-existing dictionaries of positive and negative words, and loads a text file of passages to analyze.
This recipe shows how to analyze the sentiment of a simple passage of text, such as a tweet.
This is a recipe for analyzing the mood or opinion of a text or corpus.