Text Mining for Discourse Analysis: An Exemplary Study of the Debate on Minimum Wages in Germany

Wiedemann, Gregor

doi:10.1007/978-3-319-97370-8_7

Cited by 5 publications

(5 citation statements)

References 23 publications

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“…We recognize that the dictionary by Pitt et al [14] is an important antecedent to the BP lexical approach, and that using text mining to modify it moves the study forward. We have therefore built on previous research [14][15][16][17][18][19], and taken advantage of the vast amount of data on TripAdvisor and advances in text mining [71] to deduce WHS personality traits. These traits are essential criteria for content validity when constructing a BP scale.…”

Section: Methodological Contributionsmentioning

confidence: 99%

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Brand Personality Traits of World Heritage Sites: Text Mining Approach

2021

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UNESCO World Heritage Sites (WHSs) must necessarily display Outstanding Universal Values (OUVs), as these play a vital role in constructing competitive brand personality (BP) in tourism marketing. However, how these WHS qualities are perceived by visitors still needs substantial investigation. Adopting a visitor-driven approach, this study seeks to explore the intangible attributes of WHSs and, for the first time, uses the BP concept to measure these attributes in cultural attractions. To investigate how visitors perceive WHS personality traits, 5579 visitor-generated reviews of 175 French (39), German (44), Italian (50), and Spanish (42) cultural WHSs on TripAdvisor were analysed using empirical, mixed methods. Results show that four personality dimension categories can be attributed to WHSs: Sophistication, Sincerity, Competence, and Excitement. Moreover, a novel BP lexical technique is presented along with a 222-item personality trait dictionary, which can be used to measure personality traits in cultural attractions. Theoretical and practical implications of the study are also discussed.

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Section: Methodological Contributionsmentioning

confidence: 99%

“…Computer-based analysis of digital text has gained importance in social science due to the availability of a huge amount of digital text [71]. By text pre-processing in the data mining, we were able to reduce the size and complexity of the vocabulary to allow for computational efficiency and limit irrelevant words [72].…”

Section: Data Preparationmentioning

confidence: 99%

Brand Personality Traits of World Heritage Sites: Text Mining Approach

2021

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“…The accounts collected via critical incident technique were transcribed in full, and the resulting corpus of texts was subjected to a lexicometrical analysis (Lebart et al, 1997;Wiedemann, 2019). Lexicometrical analysis refers to a set of techniques used to perform statistical analysis on textual data, including analysis of specificities, similarities, descending hierarchical classification, and factorial analysis of correspondences.…”

Section: Qualitative Data Analysis With Lexicometrymentioning

confidence: 99%

Perceived unfairness of revenue management pricing: developing a measurement scale in the context of hospitality

Meatchi

Camus

Lecointre-Erickson

2021

IJCHM

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Purpose This paper aims to offer a multi-dimensional scale for measuring the concept of perceived unfairness of revenue management pricing (RMP) in the context of hospitality. Design/methodology/approach To develop a measurement scale for the perceived unfairness of RMP, the authors conducted a qualitative study using the critical incident technique to identify the key components of our measurement tool. They then collected two samples of quantitative data enabling them to have compelling evidence of the scale’s reliability and validity. Findings This research identified three dimensions of perceived unfairness of RMP in the context of hospitality: perceived normative deviation, perceived opacity and negative effects. The new scale proposed here is an alternative measurement instrument that could be useful for detecting and correcting some negative aspects of RMP. Practical implications This measurement scale will help hotel managers to detect potential feelings of unfairness in relation to the RMP policies. It might also be used within the framework of market analyses and pricing strategy plans. Finally, the results of this research show that transparency, fairness and ethics based pricing could help hotel managers increase their revenue-per-available-room during and post COVID-19 pandemic. Originality/value This research develops a complete measurement scale for perceived unfairness of RMP, including cognitive and affective dimensions. The richness of this scale will help hospitality companies effectively identify the indicators that denote perceived unfairness of RMP, making them better equipped to handle customer dissatisfaction.

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“…Applying the text-mining frequency criteria, items would be considered if they averaged between 0.01 and 0.05 of the processed text (Denny & Spirling, 2018; Wiedemann, 2018). LIWC software was used, as it includes a psychological process analysis known as “category analysis.” This transforms the whole potential personality list into a dictionary, where each item is perceived as an individual category.…”

Section: Methodsmentioning

confidence: 99%

Section: Refining the Itemsmentioning

confidence: 99%

A Model for Brand Personality Word Embedding: Identifying UNESCO World Heritage Personality Categories

Hassan

Zerva

Aulet

2023

Journal of Travel Research

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Despite having received considerable academic attention, existing brand personality (BP) scales are difficult to generalize and likely need further development. The aim of this study was to design a novel method for constructing context driven-BP categories through the use of a multi-disciplinary approach and advances in personality studies in psychology and natural language processing. Based on a textual analysis that relies on devising hypotheses of psycholexical representation and the distributed representation of words, the aforementioned method was employed to explore World Heritage Site (WHS) personalities using information from all 1,121 UNESCO World Heritage Sites (WHSs) and 9,920 user-generated reviews on TripAdvisor. The study identified a 192-item WHS personality dictionary organized into five clusters: Exceptionality; Attractiveness; Identification; Responsibility; and Prominence. These categories could be employed to measure other tourism attractions. The results show that UNESCO strongly associates WHSs with the attributes of Attractiveness and Identification.

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Text Mining for Discourse Analysis: An Exemplary Study of the Debate on Minimum Wages in Germany

Cited by 5 publications

References 23 publications

Brand Personality Traits of World Heritage Sites: Text Mining Approach

Brand Personality Traits of World Heritage Sites: Text Mining Approach

Perceived unfairness of revenue management pricing: developing a measurement scale in the context of hospitality

A Model for Brand Personality Word Embedding: Identifying UNESCO World Heritage Personality Categories

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