2015
DOI: 10.5465/ambpp.2015.10882abstract
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Linguistic Analysis: The Study of Textual Data in Management and Organization Studies with NLP

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Cited by 4 publications
(4 citation statements)
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“…Many models of language analysis have been developed by researchers to address the issues raised by domain experts like cognitive folk model for schema analysis 12,13 , schema analysis model 14 and content analysis model 15 . A few researchers came up with frameworks and algorithms to solve problems of syntactic and semantic structures of languages 16 , morphological alterations and morphotactics 17 , and language analysis techniques compatible with Natural Language Processing ('meaning extraction' and 'named entity extraction') 18 . There are some ground-breaking software models in the domain of language documentation specifically meant for language analysis and results visualisation like 'Computer Aided Text Analysis (CATA)' 19 , 'Corpus Linguistics (CL)' 20 and text analyses of indigenous literature 21…”
Section: Review Of Literature and Overview Of Systemsmentioning
confidence: 99%
“…Many models of language analysis have been developed by researchers to address the issues raised by domain experts like cognitive folk model for schema analysis 12,13 , schema analysis model 14 and content analysis model 15 . A few researchers came up with frameworks and algorithms to solve problems of syntactic and semantic structures of languages 16 , morphological alterations and morphotactics 17 , and language analysis techniques compatible with Natural Language Processing ('meaning extraction' and 'named entity extraction') 18 . There are some ground-breaking software models in the domain of language documentation specifically meant for language analysis and results visualisation like 'Computer Aided Text Analysis (CATA)' 19 , 'Corpus Linguistics (CL)' 20 and text analyses of indigenous literature 21…”
Section: Review Of Literature and Overview Of Systemsmentioning
confidence: 99%
“…NLP involves the use of software‐based systems to quantitatively analyze and organize text information (Bates, ). Use of NLP has expanded rapidly in recent years, and scholarly work has begun to emerge in areas such as organizational studies (Goldenstein, Poschmann, & Handschke, ), as well as practical applications such as team formation (Montelisciani, Gabelloni, Giacomo Tazzini, & Gualtiero Fantoni, ) and diversity and inclusion (Morgan, Dunleavy, & DeVries, ). An important enabler of this work has been the increasing availability and sophistication of open source applications capable of running NLP analytics, such as NLTK and Gensim, which can be operated using the open source programming language, Python (Coehlo & Richert, ).…”
Section: Introductionmentioning
confidence: 99%
“…The rapidly increasing number of publications using text analytics for economics, business, and management (for surveys, cf. Lu et al (2010); Goldenstein et al (2015); Kumar and Ravi (2016)) indicates the emergence of an entirely new application domain for NLP systems (see Section 2). At first sight, one might argue that domain-specific corpora such as the PENN TREEBANK are sufficient since they already contain economy-related language data.…”
Section: Introductionmentioning
confidence: 99%