Write Blurb for "Word Embeddings" (github repo)

[stephbuon]

(see syllabus for instructions).

[HaileyHazen]

Word Embeddings

Word embeddings demonstrate how a word’s semantic context changes across time and location. The word embedding process at its finest answers questions like, “How did the United States Congress discuss race during the Civil War in comparison to the Civil Rights Movement?” or, “In what ways do school boards in Texas discuss gun violence when compared to schools in New York?”

The embedding process starts with word vectors, which take note of which words in a document have similar meanings. These vectors successfully associate phrases like ‘Mark Antony’ with ‘Rome’ or ‘Louis XIV’ with ‘Versailles.’ Moreover, historians can use word embeddings to compare how people discussed words over time. For instance, scholars can analyze how the British Parliament discussed the term, ‘India’ during the 1857 Indian Uprising in comparison to how Britain discussed the country during the 1919 Amritsar Massacre. Scholars can also analyze how speakers use words today as one politician in California may discuss the term, ‘abortion’ differently than a politician in Georgia may utilize the same word.