Textual Data Science with R by Monica Becue-Bertaut
Textual Data Science With R targets an important and rela-tively understudied area of data science: the statistical analysisof largely unstructured data in the form of natural languagetext. Using examples spanning fields such as free-form sur-vey responses, bibliographies, and speeches, the book pre...
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2021
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| Online Access: | https://ink.library.smu.edu.sg/soss_research/4014 https://ink.library.smu.edu.sg/context/soss_research/article/5272/viewcontent/Textual_Data_Science_with_R.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Textual Data Science With R targets an important and rela-tively understudied area of data science: the statistical analysisof largely unstructured data in the form of natural languagetext. Using examples spanning fields such as free-form sur-vey responses, bibliographies, and speeches, the book presentsmulti-dimensional methods for mining patterns and insightsfrom textual data. Beginning with a practical and conceptualoverview of textual data and how to pre-preprocess and struc-ture this data, the book proceeds to explain the framework ofcorrespondence analysis and its application to textual data. Itthen discusses two other major approaches: clustering and afocus on cluster features, including characteristic words, andmultiple factor analysis. It finishes with an extensive practicalsection presenting examples and workflows for bibliographicdatabases, a rhetorical speech, political speeches, and a corpusof sensory descriptions. |
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