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Article

Eunhye (Olivia) Park, Bongsug (Kevin) Chae and Junehee Kwon

The purpose of this study was to explore influences of review-related information on topical proportions and the pattern of word appearances in each topic (topical…

Abstract

Purpose

The purpose of this study was to explore influences of review-related information on topical proportions and the pattern of word appearances in each topic (topical content) using structural topic model (STM).

Design/methodology/approach

For 173,607 Yelp.com reviews written in 2005-2016, STM-based topic modeling was applied with inclusion of covariates in addition to traditional statistical analyses.

Findings

Differences in topic prevalence and topical contents were found between certified green and non-certified restaurants. Customers’ recognition in sustainable food topics were changed over time.

Research limitations/implications

This study demonstrates the application of STM for the systematic analysis of a large amount of text data.

Originality/value

Limited study in the hospitality literature examined the influence of review-level metadata on topic and term estimation. Through topic modeling, customers’ natural responses toward green practices were identified.

研究目的

本研究旨在通过结构性话题建模(STM)方法以开拓评论性内容对于话题组成和词条构成的影响。

研究设计/方法/途径

本论文采用 173,607 份 Yelp.com 在 2015 至 2016 年间的评论内容为样本,STM 分析结合共变量形成话题性建模。

研究结果

话题趋势和话题内容的不同存在于认证过的绿色餐馆与非认证的绿色餐馆中。消费者对于可持续性的食物话题兴趣随着时间而改变。

研究理论限制/意义

本研究对 STM 相关大规模文本型数据的系统分析方法给与启示。

研究原创性/价值

在酒店管理文献中很少有文章研究评论性元数据对于话题和词条预估的影响。通过话题建模,消费者对于绿色措施的反馈获得了梳理和确认。

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Article

Jun Wang, Yunpeng Li, Bihu Wu and Yao Wang

The purpose of this paper is to study tourists’ spatial and psychological involvement reflected through tourism destination image (TDI), TDI is divided into on-site and…

Abstract

Purpose

The purpose of this paper is to study tourists’ spatial and psychological involvement reflected through tourism destination image (TDI), TDI is divided into on-site and after-trip groups and the two groups are compared in the frame of three-dimensional continuums.

Design/methodology/approach

By conducting latent Dirichlet allocation (LDA) modeling to tourism user-generated content, structural topic models are established. The topics separated out from unstructured raw texts are structural themes and representations of TDI. Social network analysis (SNA) reveals the quantitative and structural differences of three-dimensional continuums of the two TDI groups.

Findings

The findings reveal that from the stage of on-site to after-trip, tourist perception of TDI shifts from psychologically to functionally-oriented, from common to unique, and from holistic to more attribute focused. Also, it is suggested that from a postmodernism perspective, TDI is never unique, fixed or universal, but has different image perceptions and feedbacks for different tourists.

Research limitations/implications

With the assistance of social sensing, a panoramic view of TDI could be established. Targeted and precision destination marketing and image promotion could be applied out to each individual tourist.

Originality/value

Combining with the perspectives of the tourist-destination space system and the tourism involvement theory, this research proposes a TDI transformation model and an explanation of the internal mechanism. The originality of research also lies in the methodological innovation of social sensing data and the LDA topic model.

研究目的

本研究针对旅游目的地形象(TDI)及其体现出的游客空间和心理涉入, 将旅游目的地形象划分为在场形象和游后形象, 并将二者在TDI三维连续体(Three-dimensional continuums)框架下进行比较。

研究方法

本研究应用内容分析法, 通过对旅游用户生成内容(tourism UGC)进行LDA(Latent Dirichlet Allocation)建模, 从非结构化的原始文本中建立起结构化的语义主题模型, 并且应用社会网络分析(Social Network Analysis), 从定量和结构化的角度揭示了游中与游后目的地形象的差异。

研究发现

研究发现, 从游中到游后, 游客的目的地形象感知经历了从心理到功能、从一般到特殊、从整体到属性的转变。同时, 基于后现代主义的视角, 旅游目的地形象并不是唯一的、固定的或放之四海而皆准的, 而是在不同的游客感知中有不同的形象和体现。

研究应用

应用社会感知(Social Sensing)理论可以全面解析旅游目的地形象。同时可以针对特定游客采取精准定点的旅游目的地营销和形象推广手段。

研究价值

本研究从旅游目的地空间系统和旅游涉入理论视角出发, 提出了旅游目的地形象转变的模型和其内在机制解释, 在方法上创新性地使用了社会感知数据和LDA主题模型。

关键词

关键词 旅游目的地形象, 在场形象, 游后形象, 旅游用户生成内容 (tourism UGC), LDA(Latent Dirichlet Allocation)建模, 社会感知

Propósito

Para estudiar el grado de participación espacial y psicológica de los turistas reflejado en la imagen del destino turístico (TDI), el TDI se divide en grupo en el sitio y grupo posterior al viaje, y los dos grupos se comparan en el marco del continuo tridimensional.

Diseño/Metodología

Al modelar la posible asignación de Dirichlet (LDA) del contenido generado por el usuario turístico (UGC), se estableció un modelo de tema estructural. El tema que está separado del texto original no estructurado es el tema estructurado y la representación de TDI. El análisis de redes sociales reveló diferencias en el número y la estructura de los continuos tridimensionales de los dos grupos de TDI.

Resultados

Los resultados de la encuesta muestran que, desde la escena hasta los viajes, la percepción de los turistas de TDI cambia de orientación psicológica a funcional, de lo ordinario a lo único, y de una atención general a más. Además, se sugiere que desde una perspectiva posmoderna, TDI nunca es único, fijo o universal, sino que tiene diferentes percepciones de imagen y comentarios para diferentes visitantes.

Implicaciones practicas

Con la ayuda de la detección social, se podría establecer una vista panorámica de TDI. El marketing de destino y la promoción de imágenes dirigidos y precisos podrían aplicarse a cada turista individual.

Originalidad/valor

Combinando con las perspectivas del sistema espacial de destino turístico y la teoría de la participación turística, esta investigación propone un modelo de transformación TDI y la explicación del mecanismo interno. La originalidad de la investigación también radica en la innovación metodológica de los datos de detección social y el modelo de tema LDA.

Details

Tourism Review, vol. 76 no. 1
Type: Research Article
ISSN: 1660-5373

Keywords

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Article

Faizan Ali, Eunhye (Olivia) Park, Junehee Kwon and Bongsug (Kevin) Chae

This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary

Abstract

Purpose

This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary Hospitality Management (IJCHM). To be specific, this paper uncovers IJCHM’s latent topics and hidden patterns in published research and highlights the differences across three decades and before and after Social Sciences Citation indexing.

Design/methodology/approach

In total, 1,573 documents published over 199 issues of IJCHM were analyzed using two computational tools, i.e. metaknowledge and structural topic modeling (STM), as the basis of the mixed method. STM was used to discover the evolution of topics over time. Moreover, bibliometrics (and network analysis) were used to highlight IJCHM’s top researchers, top-cited references, the geographical networks of the researchers and differences in the collaborative networks.

Findings

The number of papers published continually increased over time with changes of key researchers publishing in IJCHM. The co-authorship networks have also changed and revealed an increasing diversity of authorship and collaborations among authors in different countries. Moreover, the variety of topics and the relative weight of each topic have also changed.

Research limitations/implications

Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided.

Originality/value

It is the first attempt to apply topic modeling to a leading academic journal in hospitality and tourism and explore the diversity in contemporary hospitality management research (topics and contributors) from 30 years of published research.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 7
Type: Research Article
ISSN: 0959-6119

Keywords

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Article

Mu Yang and Chunjia Han

This study aims to conduct a “real-time” investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus…

Abstract

Purpose

This study aims to conduct a “real-time” investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus (Covid-19) pandemic. Specifically, using the hospitality industry as an example, the study analyses how Covid-19 has impacted the industry, what are the challenges and how the industry has responded.

Design/methodology/approach

With 94,340 tweets collected between October 2019 and May 2020 by a programmed Web scraper, unsupervised machine learning approaches such as structural topic modelling are applied.

Originality/value

This study contributes to the literature on business response during crises providing for the first time a study of using unstructured content on social media for industry-level analysis in the hospitality context.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 4
Type: Research Article
ISSN: 0959-6119

Keywords

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Article

Xiaolin (Crystal) Shi and Zixi Chen

This study aims to examine the factors influencing hotel employee satisfaction and explores the different sentiments expressed in these factors in online reviews by hotel…

Abstract

Purpose

This study aims to examine the factors influencing hotel employee satisfaction and explores the different sentiments expressed in these factors in online reviews by hotel type (premium versus economy) and employment status (current versus former).

Design/methodology/approach

A total of 78,535 online reviews by employees of 29 hotel companies for the period of 2011-2019 were scraped from Indeed.com. Structural topic modeling (STM) and sentiment analysis were used to extract topics influencing employee satisfaction and examine differences in sentiments in each topic.

Findings

Results showed that employees of premium hotels expressed more positive sentiments in their reviews than employees of economy hotels. The STM results demonstrated that 20 topics influenced employee satisfaction, the top three of which were workplace bullying and dirty work (18.01%), organizational support (16.29%) and career advancement (8.88%). The results indicated that the sentiments in each topic differed by employment status and hotel type.

Practical implications

Rather than relying on survey data to explore employee satisfaction, hotel industry practitioners can analyze employees’ online reviews to design action plans.

Originality/value

This study is one of only a few to use online reviews from an employment search engine to explore hotel employee satisfaction. This study found that workplace bullying and dirty work heavily influenced employee satisfaction. Moreover, analysis of the comments from previous employees identified antecedents of employees’ actual turnover behavior but not their turnover intention.

Details

International Journal of Contemporary Hospitality Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-6119

Keywords

Content available
Article

Helen Cripps, Abhay Singh, Thomas Mejtoft and Jari Salo

The purpose of this research is to investigate the use of Twitter in business as a medium for knowledge sharing and to crowdsource information to support innovation and…

Abstract

Purpose

The purpose of this research is to investigate the use of Twitter in business as a medium for knowledge sharing and to crowdsource information to support innovation and enhance business relationships in the context of business-to-business (B2B) marketing.

Design/methodology/approach

This study uses a combination of methodologies for gathering data in 52 face-to-face interviews across five countries and the downloaded posts from each of the interviewees' Twitter accounts. The tweets were analysed using structural topic modelling (STM), and then compared to the interview data. This method enabled triangulation between stated use of Twitter and respondent's actual tweets.

Findings

The research confirmed that individuals used Twitter as a source of information, ideas, promotion and innovation within their industry. Twitter facilitates building relevant business relationships through the exchange of new, expert and high-quality information within like-minded communities in real time, between companies and with their suppliers, customers and also their peers.

Research limitations/implications

As this study covered five countries, further comparative research on the use of Twitter in the B2B context is called for. Further investigation of the formalisation of social media strategies and return on investment for social media marketing efforts is also warranted.

Practical implications

This research highlights the business relationship building capacity of Twitter as it enables customer and peer conversations that eventually support the development of product and service innovations. Twitter has the capacity for marketers to inform and engage customers and peers in their networks on wider topics thereby building the brand of the individual users and their companies simultaneously.

Originality/value

This study focuses on interactions at the individual level illustrating that Twitter is used for both customer and peer interactions that can lead to the sourcing of ideas, knowledge and ultimately innovation. The study is novel in its methodological approach of combining structured interviews and text mining that found the topics of the interviewees' tweets aligned with their interview responses.

Details

Marketing Intelligence & Planning, vol. 38 no. 5
Type: Research Article
ISSN: 0263-4503

Keywords

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Article

Roger Bennett and Rohini Vijaygopal

This paper aims to explore the use of an appeal, belonging and commitment social marketing intervention to rescue a failing corporate “charity of the year” exercise that…

Abstract

Purpose

This paper aims to explore the use of an appeal, belonging and commitment social marketing intervention to rescue a failing corporate “charity of the year” exercise that involved a mental disability charity. It describes the improvements experienced consequent to the introduction of volunteer “charity ambassadors” (CAs) appointed to champion the charity’s cause.

Design/methodology/approach

The study revolved around company employees’ responses to an open-ended question concerning their attitudes towards people with mental disabilities. A semi-automated qualitative research technique (structural topic modelling [STM]) was used to analyse the replies both pre- and post-intervention. Regression analyses were undertaken to explain whether employees’ replies to the question fell in specific categories.

Findings

The intervention was successful. Employees’ attitudes regarding mentally impaired people shifted substantially away from fear and towards feelings of benevolence and compassion. Employees’ financial donations to the charity increased significantly consequent to the intervention. Levels of benevolence and compassion depended significantly on participants’ prior exposure to people with mental disabilities, gender and degree of involvement in activities associated with the intervention.

Research limitations/implications

Stakeholders other than employees were not sampled. Open-ended responses to a single question can oversimplify complex issues.

Practical implications

Outcomes to the research demonstrate how CAs can induce positive attitudes and behaviour towards an “unpopular cause”.

Originality/value

The results highlight some of the problems attached to corporate sponsorship of unpopular causes. A relatively recently developed open-ended qualitative research technique, STM, was used to examine employees’ attitudes. Classifications of findings emerged from the data and did not depend on a predetermined coding scheme.

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Article

Eunhye (Olivia) Park, Bongsug Chae and Junehee Kwon

This paper aims to identify the intellectual structure of four leading hospitality journals over 40 years by applying mixed-method approach, using both machine learning…

Abstract

Purpose

This paper aims to identify the intellectual structure of four leading hospitality journals over 40 years by applying mixed-method approach, using both machine learning and traditional statistical analyses.

Design/methodology/approach

Abstracts from all 4,139 articles published in four top hospitality journals were analyzed using the structured topic modeling and inferential statistics. Topic correlation and community detection were applied to identify strengths of correlations and sub-groups of topics. Trend visualization and regression analysis were used to quantify the effects of the metadata (i.e. year of publication and journal) on topic proportions.

Findings

The authors found 50 topics and eight subgroups in the hospitality journals. Different evolutionary patterns in topic popularity were demonstrated, thereby providing the insights for popular research topics over time. The significant differences in topical proportions were found across the four leading hospitality journals, suggesting different foci in research topics in each journal.

Research limitations/implications

Combining machine learning techniques with traditional statistics demonstrated potential for discovering valuable insights from big text data in hospitality and tourism research contexts. The findings of this study may serve as a guide to understand the trends in the research field as well as the progress of specific areas or subfields.

Originality/value

It is the first attempt to apply topic modeling to academic publications and explore the effects of article metadata with the hospitality literature.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 11
Type: Research Article
ISSN: 0959-6119

Keywords

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Article

Praveen S.V., Rajesh Ittamalla and Dhilip Subramanian

The word “digital contact tracing” is often met with different reactions: the reaction that passionately supports it, the reaction that neither supports nor oppose and the…

Abstract

Purpose

The word “digital contact tracing” is often met with different reactions: the reaction that passionately supports it, the reaction that neither supports nor oppose and the one that vehemently opposes it. Those who support the notion of digital contact tracing vouch for its effectiveness and how the complicated process can be made simpler by implementing digital contact tracing, and those who oppose it often criticize the imminent threats it possesses. However, without earning the support of a large population, it would be difficult for any government to implement digital contact tracing to perfection. The purpose of this paper is to analyze, using machine learning, how different continents have different sentiments over digital contact tracing being used as a measure to curb COVID-19.

Design/methodology/approach

For the analysis, data were collected from Twitter. Tweets that contain the hashtag and the word “digital contact tracing” were crawled using Python library Tweepy. Tweets across countries of four continents were collected from March 2020 to August 2020. In total, 70,212 tweets were used for this study. Using the machine learning algorithm, the authors detected the sentiment of all the tweets belonging to each continent. Structural topic modeling was used to understand the overall significant issues people voice out by global citizens while sharing their opinions on digital contact tracing.

Findings

This study was conducted in two parts. Study one results show that North American and European citizens share more negative sentiments toward “digital contact tracing.” The citizens of the Asian and South American continent mostly share neutral sentiments regarding the digital contact tracing. Overall, only 33% of total tweets were positively related to contact tracing, whereas 52% of the total tweets were neutral. Study two results show that factors such as fear of government using contact tracing to spy on its people, the feeling of being unsafe and contact tracing being used to promote an agenda were the three major issues concerning the overall general public.

Originality/value

Despite numerous studies being conducted about how to implement the contact tracing efficiently, minimal studies were done to explore the possibility and challenges in implementing it. This study fills the gap.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

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Book part

Ayse Lokmanoglu and Yannick Veilleux-Lepage

Purpose – In order to explore how gender and sexual politics are played out in everyday practice within both the extreme right and jihadi-Salafist movements online, this…

Abstract

Purpose – In order to explore how gender and sexual politics are played out in everyday practice within both the extreme right and jihadi-Salafist movements online, this chapter analyzes the content of two women’s only forums: The Women’s Forum on Stormfront.org and Women Dawah, a Turkish language pro-IS group chat on Telegram.

Methodology – The Women’s Forum and the Women Dawah data sets were analyzed using structural topic modeling to uncover the differences and similarities in salient topics between White Nationalist and Islamic State women-only forums.

Findings – The cross-ideological and multi-linguistic thematic analysis suggests that the safety of online spaces enables women to be more active, and serves digital support network for like-minding individuals. It also highlights that religion and ideology, whilst interwoven throughout posts on both platforms, they were more explicitly discussed within Women Dawah data.

Originality/Value – This research uses a unique data set which was collected over one year to conduct a cross-ideological and multi-linguistic thematic analysis, a relatively uncommon approach.

Details

Radicalization and Counter-Radicalization
Type: Book
ISBN: 978-1-83982-988-8

Keywords

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