Use of an automatic content analysis tool: A technique for seeing both local and global scope

Stockwell, Paul; Colomb, Robert M.; Smith, Andrew; Wiles, Janet

doi:10.1016/j.ijhcs.2008.12.001

Cited by 57 publications

(60 citation statements)

References 17 publications

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“…Several such approaches have been developed, including hyperspace analogue to language (Burgess & Lund, 1997), LSA (Landauer et al, 1998), and data mining tools such as Leximancer (Smith & Humphreys, 2006). Hyperspace analogue to language approaches are restricted in that they assume symmetric relationships and close term co-occurrence (Stockwell et al, 2009), which is why we focus on LSA and data mining-based approaches.…”

Section: Lsa Vs Data Miningmentioning

confidence: 99%

“…Third, it provides useful visualization of coded themes and concepts together with an interface that allows the researcher to drill down to the underlying data to understand the context of the concepts/themes, identify the sources and common discussion of the concepts, and identify relevant data files. Last, Leximancer has been used in several academic studies on content analysis and appears to be a popular data mining-based content analysis tool (e.g., Davies et al, 2006;Martin & Rice, 2007;Stockwell et al, 2009).…”

Section: Data Miningmentioning

confidence: 99%

“…First, during semantic extraction, Leximancer discovers concepts from the text data, with no requirement for a pre-defined dictionary (although one can be used if desired) or limitation of a specific spoken language. Leximancer defines a concept as a term that is less frequently, yet consistently, used with a more common term (Stockwell et al, 2009) -that is, a concept is a collection of words that occurs together often. Common stop-words (such as 'the', 'an', etc.…”

Section: Data Miningmentioning

confidence: 99%

“…Further details about the algorithms underlying Leximancer are available in Smith & Humphreys (2006) and Stockwell et al (2009).…”

Section: Data Miningmentioning

confidence: 99%

“…For details of all Leximancer outputs we refer the reader to explanations provided in Stockwell et al (2009). The main interactive output of the Leximancer data mining tool is the concept map, which is based on the co-occurrence matrix and is a visual representation of the core concepts and their interrelationships.…”

Section: Data Miningmentioning

confidence: 99%

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Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Indulska

Hovorka²,

Recker

2012

European Journal of Information Systems

111

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Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.

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Section: Lsa Vs Data Miningmentioning

confidence: 99%

Section: Data Miningmentioning

confidence: 99%

Section: Data Miningmentioning

confidence: 99%

“…Further details about the algorithms underlying Leximancer are available in Smith & Humphreys (2006) and Stockwell et al (2009).…”

Section: Data Miningmentioning

confidence: 99%

Section: Data Miningmentioning

confidence: 99%

See 3 more Smart Citations

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Indulska

Hovorka²,

Recker

2012

European Journal of Information Systems

111

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Circular economy disclosure and integrated reporting: The role of corporate governance mechanisms

2023

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In recent years, attention to the circular economy (CE) has grown considerably and it is now recognised as a model capable of overtaking the current linear economy of unsustainable production and consumption. Organisations have started to implement circular practices to transition towards this sustainable business model and to disclose CE performance to their stakeholders. In this context, the integrated report serves as a suitable tool to provide a holistic representation of how CE could impact the companies' ability to create value over time. The relevance of this model has prompted various scholars to examine CE disclosure. However, only some studies have investigated this topic in the integrated reporting (IR) context. To the best of the authors' knowledge, no studies have examined how corporate governance mechanisms can affect the amount of CE information disseminated through the integrated reports. By applying the lens of stakeholder‐agency theory, this study aims to fill this important gap by analysing the effect of the characteristics of the corporate governance mechanisms on the level of CE disclosure within the integrated reports. The analysis, conducted using a sample of 124 European companies, indicates a positive impact of the board size, board gender diversity and the presence of the corporate social responsibility (CSR) committee on the level of CE disclosure within the integrated reports.

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pyResearchInsights—An open‐source Python package for scientific text analysis

Shetty

Ramesh

2021

Ecology and Evolution

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Use of an automatic content analysis tool: A technique for seeing both local and global scope

Cited by 57 publications

References 17 publications

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Circular economy disclosure and integrated reporting: The role of corporate governance mechanisms

pyResearchInsights—An open‐source Python package for scientific text analysis

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