Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability

Yu, Chong Ho; Jannasch-Pennell, Angel; DiGangi, Samuel

doi:10.46743/2160-3715/2011.1085

Cited by 48 publications

(46 citation statements)

References 61 publications

(27 reference statements)

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“…Furthermore, numerous researchers have applied text mining to qualitative research projects and see text exploitation as a feasible qualitative research method (Rajman & Besançon, 1998;Camillo et al, 2005;Hong, 2009;Janasik et al, 2009;Yu et al, 2011;Mahmoudi & Abbasalizadeh, 2019;Tian et al, 2019;Wang et al, 2020). According to Rose & Lennerholt (2017), advances in text mining accompany with the widespread adoption of information technology has granted wider access to large amounts of text documents as well as automated analysis techniques.…”

Section: Text Mining and Data Clustering Methodsmentioning

confidence: 99%

Text mining in the trend of education 4.0: A study on clustering mathematical terms of algebra textbooks in Vietnamese high schools

Bui

Nguyen

et al. 2020

VJE

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In the context of Educational Revolution 4.0, text mining with digital tools plays an important role. Various techniques and softwares have been employed in text mining, among which the clustering technique using Atlas.ti, a German software, is widely used thanks to its versatility and open access. This article presents the results of clustering Mathematical terms in Algebra textbook in Vietnamese high schools with the support of Atlas.ti. Initial research results can yield the insight into the relationship among Mathematical terms in the curriculum, thereby, aiming for a better teaching process.

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Section: Text Mining and Data Clustering Methodsmentioning

confidence: 99%

Text mining in the trend of education 4.0: A study on clustering mathematical terms of algebra textbooks in Vietnamese high schools

Bui

Nguyen

et al. 2020

VJE

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“…From the tag clouds obtained, the final analysis of this research was carried out by estimating the meaning of the most relevant terms highlighted by LSA, evidenced in these tag clouds, along with the content analysis to emphasize the meaning of the messages analyzed in the literature. This is because text mining techniques are closely related to content analysis, which extracts data-driven categories for analysis, allowing one technique to complement the other in the process (Yu, Jannasch-Pennell, & Digangi, 2011). Four data- Disruptive business models driven categories were identified in our analysis: Disruptive technology and innovation; value proposition to consumers; maintenance of existing business models; and pattern within DBM.…”

Section: Methodsmentioning

confidence: 99%

Conceptualizing and qualifying disruptive business models

Behr

Marcolin

2019

RAUSP

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Purpose This paper aims to elaborate a set of characteristics that conceptualize and qualify a disruptive business model. Design/methodology/approach The literature on disruptive business models will be analyzed using the latent semantic analysis (LSA) technique, complemented by content analysis, to obtain a more precise qualification and conceptualization regarding disruptive business models. Findings The results found described concepts already described in the theory. However, such findings, highlighted by the LSA, bring new perspectives to the analysis of the disruptive business models, little discussed in the literature and which reveal important considerations to be made on this subject. Research limitations/implications It should be noted, about the technique used, a limitation on the choice of the number of singular values. For this to be a problem in the open literature, the authors tried to work not just with the cost-benefit ratio given the addition of each new dimension in the analysis, as well as a criterion of saturation of the terms presented. Practical implications The presentation of this set of characteristics can be used as a validation tool to identify if a business is or is not a disruptive business model by managers. Originality/value The originality of this paper is the achievement of a consolidated set of characteristics that conceptualize and qualify the disruptive business models by conducting an in-depth analysis of the literature on disruptive business models through the LSA technique, considering the difficulty of obtaining precise concepts on this subject in the literature.

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“…Given the recent increase in prevalence and use of data analysis software applications, text-mining methods have been increasingly used as research tools to extract meaningful keywords from bulk data to answer research inquiries. Text mining provides an efficient method of identifying pairs of words that are frequently adjacent within reviews, but the extent to which the relationship of keywords is meaningful in any given context has been questioned (Feldman et al , 1998; Yu et al , 2011). The pilot test found that counting the frequency that the word “wine” appears in a review can provide only a limited understanding of the application of wine in hotels.…”

Section: Methodsmentioning

confidence: 99%

Wine attractions at hotels: study of online reviews

Hsieh

Lee

Yin

2019

IJWBR

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Purpose The purpose of this study is to delineate the role of wine at hotels from the customer’s perspective by analyzing New York City hotel reviews posted on TripAdvisor. Design/methodology/approach This study used content analysis to study 26,831 wine-relevant reviews that had been posted on TripAdvisor’s New York City hotels by April 12, 2018. Two trained coders quantified and tallied the presence of themes based on the pre-established coding scheme. Findings Wine was mentioned in the online reviews in expressing positive, negative or neutral hotel experiences. Of the 877,616 New York City hotel reviews, about 3 per cent contained the keyword “wine.” The three most frequently mentioned wine-related positive experiences were free happy hours, a surprise bottle of complimentary wine and the fun of pairing food and wine. The top three wine-related negative experiences were pricey/expensive/overpriced wine, poor wine list and poor quality of wine. The study found that hotel guests liked wine and that it had become a significant aspect of their lodging experience. Originality/value This study adds value to the literature of hotel wines by divulging hotel customers’ wine-related experiences through their online comments and by providing a snapshot of hotel guests’ wine-drinking behavior. The findings can provide an insight for hotels to further the use of wine as a means to enhance guest experience and to generate additional revenue.

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Compatibility between Text Mining and Qualitative Research in the Perspectives of Grounded Theory, Content Analysis, and Reliability

Cited by 48 publications

References 61 publications

Text mining in the trend of education 4.0: A study on clustering mathematical terms of algebra textbooks in Vietnamese high schools

Text mining in the trend of education 4.0: A study on clustering mathematical terms of algebra textbooks in Vietnamese high schools

Conceptualizing and qualifying disruptive business models

Wine attractions at hotels: study of online reviews

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