LEADER 04382nam 22006975 450 001 9910299990503321 005 20220627185715.0 010 $a3-319-03164-3 024 7 $a10.1007/978-3-319-03164-4 035 $a(CKB)3710000000143791 035 $a(EBL)1782119 035 $a(SSID)ssj0001278049 035 $a(PQKBManifestationID)11757863 035 $a(PQKBTitleCode)TC0001278049 035 $a(PQKBWorkID)11278766 035 $a(PQKB)10307440 035 $a(DE-He213)978-3-319-03164-4 035 $a(MiAaPQ)EBC6312135 035 $a(MiAaPQ)EBC1782119 035 $a(Au-PeEL)EBL1782119 035 $a(CaPaEBR)ebr10965359 035 $a(OCoLC)881681427 035 $a(PPN)179765671 035 $a(EXLCZ)993710000000143791 100 $a20140610d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aText Analysis with R for Students of Literature /$fby Matthew L. Jockers 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (199 p.) 225 1 $aQuantitative Methods in the Humanities and Social Sciences,$x2199-0956 300 $aIncludes index. 311 $a3-319-03163-5 327 $aR Basics -- First Foray into Text Analysis with R -- Accessing and Comparing Word Frequency Data -- Token Distribution Analysis -- Correlation -- Measures of Lexical Variety -- Hapax Richness -- Do It KWIC -- Do It KWIC (Better) -- Text Quality, Text Variety, and Parsing XML -- Clustering -- Classification -- Topic Modeling -- Appendix A: Variable Scope Example -- Appendix B: The LDA Buffet -- Appendix C: Code Repository -- Appendix D: R Resources -- Practice Exercise Solutions -- Index. 330 $aText Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale ?microanalysis? of single texts to large scale ?macroanalysis? of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book?s focus is on making the technical palatable and making the technical useful and immediately gratifying. 410 0$aQuantitative Methods in the Humanities and Social Sciences,$x2199-0956 606 $aStatistics 606 $aComputational linguistics 606 $aR (Computer program language) 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 606 $aComputational Linguistics$3https://scigraph.springernature.com/ontologies/product-market-codes/N22000 606 $aStatistics for Social Sciences, Humanities, Law$3https://scigraph.springernature.com/ontologies/product-market-codes/S17040 615 0$aStatistics. 615 0$aComputational linguistics. 615 0$aR (Computer program language) 615 14$aStatistics and Computing/Statistics Programs. 615 24$aComputational Linguistics. 615 24$aStatistics for Social Sciences, Humanities, Law. 676 $a006.35 700 $aJockers$b Matthew L$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721648 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299990503321 996 $aText Analysis with R$92351479 997 $aUNINA