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Category: Text Analysis

Stylometry and Women Writers Online

Stylometry and Women Writers Online

By Molly Nebiolo, Research and Encoding Specialist I was able to fly to Victoria, British Columbia to to attend DHSI 2018 thanks to a course waiver awarded by DHSI and a NuLab Seedling Grant that funded my transportation and housing for the class. Details on my experience with DHSI can be read here. Stylometry is a way to compare the similarity of texts in vector space and visualize those connections or changes between authors, over time, or across genres. The…

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Investigating Crime in the Vector Space of Early Modern Women’s Writing

Investigating Crime in the Vector Space of Early Modern Women’s Writing

by Lara Rose, PhD Student: Literature, Northeastern University This post is part of the Women Writers Project sub-project that explores the intersection of text encoding and text analysis using word embedding models. For brief explanations and early explorations, please see this post by Elizabeth Polcha, and this post by Jonathan Fitzgerald. “When a woman killed her husband, it was petty treason—a crime against the nation—When a man killed his wife, it was only murder.” -Professor Marina Leslie, on gender and…

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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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