A Mathematical Approach to Categorization and Labeling of Qualitative Data

The Latent Categorization Method

Dados Bibliográficos

ID8019772
AutoresKai R Larsen (0000-0002-8812-9866, University of Colorado Boulder), David E Monarchi (University of Colorado Boulder)
Ano2004
Volume34
Fascículo1
Páginas349-392
Data de publicação2004-11-26
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoSociological Methodology (JOURNAL)
Identificadores do periódicoISSN: 0081-1750 • E-ISSN: 1467-9531
EditoraSAGE Publishing (PUBLISHER • US)
DOI10.1111/j.0081-1750.2004.00156.x
OpenAlexW2079155715
IdiomaEN
Citações recebidas3
Referências citadas48

As text databases increasingly become available to researchers, the limits to human cognition are rapidly reached. Focusing on examining objective realities, this paper introduces the latent categorization method, a novel new research method for analysis of large and midsize data sets. This method clusters text artifacts and extracts the words that were most important in creating the clusters. Further, it demonstrates a set of techniques for extracting knowledge from a representative data set involving 6135 abstracts from a variety of business-related journals

Categorization · Cognition · Data science · Data set · Information retrieval · Natural language processing · Set (abstract data type · Text categorization · Variety (cybernetics · Advanced Text Analysis Techniques · Artificial Intelligence · Computer Science · Data Mining Algorithms and Applications · Psychology · Semantic Web and Ontologies