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Category: Text Analysis

Word Embedding Models Are the New Topic Models

Word Embedding Models Are the New Topic Models

By Jonathan Fitzgerald, Ph.D. Candidate in English, Northeastern University I remember the first time I trained a topic model. It was in a course called Humanities Data Analysis, taught by Ben Schmidt. He provided us a corpus of the Federalist Papers and some code that he adapted from David Mimno, contributor to the original MALLET package and author of the R implementation of MALLET. After the initial confusion–“topics” aren’t topics in the traditional sense, after all–it felt like magic. The computer…

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The WWP Begins Research into Word Vector Analysis

The WWP Begins Research into Word Vector Analysis

We are thrilled to announce that the Women Writers Project has begun work on a new project “Word Vector Analysis for TEI/XML: A user-Friendly Toolkit,” funded under a Tier 1 grant from Northeastern University, awarded to project co-PIs, professors Julia Flanders, Elizabeth Dillon, and Cody Dunne. “Word Vector Analysis for TEI/XML” brings together two major digital humanities methodologies: text encoding and text analysis, as we aim to develop an exploratory web interface as part of the WWO Lab, which will…

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