2021
DOI: 10.22148/001c.22333
|View full text |Cite
|
Sign up to set email alerts
|

Feminist Bestsellers: A Digital History of 1970s Feminism

Abstract: Feminism of the 1970s remains among the most influential social movements within the United States. Bestselling texts played a crucial role in spreading feminism beyond early activists into the mainstream of American society. Contemporary scholars of feminism continue to rely on these works as pivotal historical sources. This paper utilizes quantitative methods to compare six feminist bestsellers from 1970. Our data consists of three subcorpora of digitized books published in 1970 found in the Hathi Trust: six… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 10 publications
0
1
0
Order By: Relevance
“…Named Entity Recognition (NER), the identification and extraction of words representing named people, places, and groups, is a common and relatively accurate (Dekker et al, 2019) methodology in text and data mining. Across the humanities, NER‐derived data has been used to make novel arguments about interpersonal relationships in Swedish literature (Kokkinakis et al, 2014), to trace how feminist ideas travel through novels (Moravec & Chang, 2021), and to study networks of day‐to‐day life contained in historical personal diaries (Fields et al, 2023). Outside of the humanities, NER is commonly used to mine research literature for new medical insights (Wang et al, 2020; Ramachandran & Arutchelvan, 2020), and to study manufacturing processes (Kumar & Starly, 2022) and marketing strategies in high‐end fashion (Chilet et al, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Named Entity Recognition (NER), the identification and extraction of words representing named people, places, and groups, is a common and relatively accurate (Dekker et al, 2019) methodology in text and data mining. Across the humanities, NER‐derived data has been used to make novel arguments about interpersonal relationships in Swedish literature (Kokkinakis et al, 2014), to trace how feminist ideas travel through novels (Moravec & Chang, 2021), and to study networks of day‐to‐day life contained in historical personal diaries (Fields et al, 2023). Outside of the humanities, NER is commonly used to mine research literature for new medical insights (Wang et al, 2020; Ramachandran & Arutchelvan, 2020), and to study manufacturing processes (Kumar & Starly, 2022) and marketing strategies in high‐end fashion (Chilet et al, 2016).…”
Section: Introductionmentioning
confidence: 99%