Text Mining and Digital Humanities: Quantitative Analysis of African American Poetry

Hdl Handle:
http://hdl.handle.net/10675.2/582990
Title:
Text Mining and Digital Humanities: Quantitative Analysis of African American Poetry
Authors:
Jenkins, Diamond; Brown, Taylohr; Quiller, Walter
Abstract:
“Text Mining and Digital Humanities: Quantitative Analysis of African American Poetry uses quantitative and qualitative analysis to formulate research questions about African American poetry. In this project, we use text-mining software to determine whether distinctive word patterns can be used to quantify the characteristics of African American poetry. For the purposes of this study, we rejected the notion that Black poetry is defined as poetry written by black authors. Instead, we argue, the distinctions in black poems should be specific enough to be classified in a separate category from other kinds of literature such as American literature, and we assert the definition of black poetry should not reduce “blackness”- what we describe as the shared cultural traditions or practices of African Americans- to certain experiences or tropes such as the rural, folk black experience. We selected Langston Hughes and the Harlem Renaissance as the earliest historical point for our inquiry, and we used Margaret Walker, Gwendolyn Brooks, Maya Angelou, and Alice Walker, poets whom Hughes directly influenced, as comparisons. We created a text database of the collected poems of the five authors and assessed the frequency of words/phrases related to three main categories that recur in the scholarship of black poetry: memory, identity, and music. After running our text data through mining software and looking specifically for words coded as memory, identity, and music variables, we were able to support our initial claim that quantitative analysis can be used as to support qualitative assertions of black poetry as a distinct genre of American poetry. Begin Time: 08:02 End Time: 37:58
Affiliation:
Katherine Reese Pamplin College of Arts, Humanities, and Social Sciences
Issue Date:
11-Sep-2015
URI:
http://hdl.handle.net/10675.2/582990
Additional Links:
https://lecture.gru.edu/ess/echo/presentation/eeb7244a-d357-43ba-b880-53326b5018cb?ec=true
Type:
Presentation
Language:
en_US
Description:
Presentation given at the CURS Brown Bag Seminar Series on September 11, 2015
Series/Report no.:
Fall; 2015
Sponsors:
Center for Undergraduate Research and Scholarship; Katherine Reese Pamplin College of Arts, Humanities, and Social Sciences; Department of English and Foreign Language
Appears in Collections:
CURS Brown Bag Presentations

Full metadata record

DC FieldValue Language
dc.contributor.authorJenkins, Diamonden
dc.contributor.authorBrown, Taylohren
dc.contributor.authorQuiller, Walteren
dc.date.accessioned2015-11-30T19:08:59Zen
dc.date.available2015-11-30T19:08:59Zen
dc.date.issued2015-09-11en
dc.identifier.urihttp://hdl.handle.net/10675.2/582990en
dc.descriptionPresentation given at the CURS Brown Bag Seminar Series on September 11, 2015en
dc.description.abstract“Text Mining and Digital Humanities: Quantitative Analysis of African American Poetry uses quantitative and qualitative analysis to formulate research questions about African American poetry. In this project, we use text-mining software to determine whether distinctive word patterns can be used to quantify the characteristics of African American poetry. For the purposes of this study, we rejected the notion that Black poetry is defined as poetry written by black authors. Instead, we argue, the distinctions in black poems should be specific enough to be classified in a separate category from other kinds of literature such as American literature, and we assert the definition of black poetry should not reduce “blackness”- what we describe as the shared cultural traditions or practices of African Americans- to certain experiences or tropes such as the rural, folk black experience. We selected Langston Hughes and the Harlem Renaissance as the earliest historical point for our inquiry, and we used Margaret Walker, Gwendolyn Brooks, Maya Angelou, and Alice Walker, poets whom Hughes directly influenced, as comparisons. We created a text database of the collected poems of the five authors and assessed the frequency of words/phrases related to three main categories that recur in the scholarship of black poetry: memory, identity, and music. After running our text data through mining software and looking specifically for words coded as memory, identity, and music variables, we were able to support our initial claim that quantitative analysis can be used as to support qualitative assertions of black poetry as a distinct genre of American poetry. Begin Time: 08:02 End Time: 37:58en
dc.description.sponsorshipCenter for Undergraduate Research and Scholarship; Katherine Reese Pamplin College of Arts, Humanities, and Social Sciences; Department of English and Foreign Languageen
dc.language.isoen_USen
dc.relation.ispartofseriesFallen
dc.relation.ispartofseries2015en
dc.relation.urlhttps://lecture.gru.edu/ess/echo/presentation/eeb7244a-d357-43ba-b880-53326b5018cb?ec=trueen
dc.subjectLangston Hughesen
dc.subjectHarlem Renaissanceen
dc.subjectMargaret Walkeren
dc.subjectGwendolyn Brooksen
dc.subjectMaya Angelouen
dc.subjectAlice Walkeren
dc.titleText Mining and Digital Humanities: Quantitative Analysis of African American Poetryen_US
dc.typePresentationen
dc.contributor.departmentKatherine Reese Pamplin College of Arts, Humanities, and Social Sciencesen
dc.contributor.mentorWilliams, Serethaen
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