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The purpose of this paper is to provide a review of hospitality and tourism studies that have used social media analytics to collect, examine, summarize and interpret “big data” derived from social media. It proposes improved approaches by documenting past and current analytic practice addressed by the selected studies in social media analytics.

Studies from the past 18 years were identified and collected from five international electronic bibliographic databases. Social media analytics-related terms and keywords in the titles, keywords or abstracts were used to identify relevant articles. Book chapters, conference papers and articles not written in English were excluded from analysis. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) guided the search, and Stieglitz and Dang-Xuan’s (2013) social media analytics framework was adapted to categorize methods reported in each article.

The research purpose of each study was identified and categorized to better understand the questions social media analytics were being used to address, as well as the frequency of each method’s use. Since 2014, rapid growth of social media analytics was observed, along with an expanded use of multiple analytic methods, including accuracy testing. These factors suggest an increased commitment to and competency in conducting comprehensive and robust social media data analyses. Improved use of methods such as social network analysis, comparative analysis and trend analysis is recommended. Consumer-review networks and social networking sites were the main social media platforms from which data were gathered; simultaneous analysis of multi-platform/sources of data is recommended to improve validity and comprehensive understanding.

This is the first systematic literature review of the application of social media analytics in hospitality and tourism research. The study highlights advancements in social media analytics and recommends an expansion of approaches; common analytical methods such as text analysis and sentiment analysis should be supplemented by infrequently used approaches such as comparative analysis and spatial analysis.

本文对酒店旅游学科中采用社交媒体数据分析的文献进行梳理。本文通过审阅其相关分析方法的文献来提出分析方法的改进策略。

样本数据包括过去18年中五个国际在线文献索引库中的文献。搜索通过标题、关键词、或者摘要中出现社交媒体数据分析等相关字样的文章。书章节、会议文章、以及非英文文章未被收录在索引中。系统回顾和文献综述的方法（PRISMA）指导本文文献索引, Stieglitz和Dang-Xuan（2013）社交媒体数据分析框架作为本文文献分类的方法。

本文汇报了每篇文献的研究目的以及系统归类以更好理解社交媒体数据分析的研究问题以及每种方法的使用频率。自2014年起, 社交媒体数据分析快速增长, 以及其他相关分析方法, 包括精度测试（accuracy testing）。这些结果表明更多全面、稳定的分析方法需求增强以及竞争激烈。本文推荐使用改良方法, 比如社交网络分析法、比较分析、趋势分析等。消费者评价网络和社交网站成为主要社交媒体网络数据的提供平台。本文推荐多源数据应该同步分析以提高有效性和全面性的理解。

本文是首篇酒店旅游领域中对社交媒体数据分析的系统文献回顾型文章。本文强调了社交媒体数据分析的先进性以及扩展其方法的全面性；常见分析方法比如文本分析和情感分析应该结合非常见的分析方法比如比较分析法和空间分析法进行系统分析。

关键词 – 关键词 对比分析, 情感分析, 用户原创内容,社交媒体分析, 主题模型, 空间分析, 文本分析文章类型 文献综述

This study aims to quantify the underlying feelings of online reviews and discover the role of seasonality in customer dining experiences.

This study applied sentiment analysis to determine the polarity of a given comment. Furthermore, content analysis was conducted based on the core attributes of the customer dining experiences.

Positive feelings towards the food and the service do not show a linear relationship, while the overall dining experiences increase in line with the positive feelings on food quality. Moreover, feelings towards the atmosphere of the restaurants are the most positive in peak season.

This study provides guidelines for restaurateurs regarding the aspects that need more attention in different seasons.

The paper contributes to the knowledge of customer feelings in local restaurants/gastronomy and the role seasonality plays in fostering such feelings. In addition, the novel methodological procedures provide insights for tourism research in discovering new dimensions in theories based on big data.

本论文旨在量化在线评论中的情感导向以及发掘季节性对消费者用餐体验的作用。

本论文采用情感分析法对既定评论做出情感判断。此外, 本文还依据消费者用餐体验中的核心价值采用了内容分析法。

研究发现消费者对食物和服务的正向情感并不是线性关系。然而, 整体用餐体验与对食物质量的正向情感是线性正向的关系。此外, 消费者对饭店氛围的情感在旺季的时节是最为突出的。

本论文对饭店从业者在不同季节的关注点上起到了指导作用。

本论文对地方饭店/美食的消费者情感认知做出了贡献, 此外, 本论文还对季节性如何促进消费情感的作用做出了研究。本论文还采用了新型的研究方法, 这对于旅游研究来说, 做出了基于大数据的新理论研究方向。

This study aims to analyze a backchannel account on news of the coronavirus at the beginning of the pandemic, with information not disseminated in official media due to the social alarm it might cause and the negative image of government management. Specifically, it examines acceptance and dissemination of this type of content in a period of lack of information, while reflecting on what would constitute proper management of this type of channel.

First, based on a literature review, this study classifies possible explanatory variables of online content dissemination into content richness and psychological content. Second, this study performs sentiment analysis of the Twitter backchannel account @COVID_19NEWS and use Qualitative Comparative Analysis to find causal configurations of variables that obtained a high rate of retweets.

The results reveal predominance of one combination of three factors in backchannel information diffusion: emotional, identifying and video content. Other interesting combinations of factors were shown to be attractive enough to contribute to success of the tweets.

Knowledge of the main configurations that attract information dissemination in backchannel accounts is useful for public management of a health crisis such as the Covid-19 outbreak. Rather than suppressing these channels, the authors discuss different solutions.

This study advances scholarship on backchannel communications in emergency situations, providing insights to understand and manage such channels.

Este estudio analiza una cuenta extraoficial sobre noticias del coronavirus al inicio de la pandemia, con información no difundida en los medios oficiales por su posible repercusión en la alarma social y la imagen negativa de la gestión gubernamental. Concretamente examina la aceptación y difusión de este contenido en un periodo de desinformación, así como reflexiona sobre la gestión de este tipo de canales.

En primer lugar, en base a la revisión de la literatura, clasificamos las variables explicativas según la riqueza de contenido y el contenido psicológico. En segundo lugar, sobre la cuenta extraoficial de @COVID_19NEWS en Twitter, realizamos análisis de sentimiento y utilizamos Análisis Comparativo Cualitativo (QCA) para encontrar configuraciones causales de variables que obtuvieron una alta tasa de retweets.

Los resultados revelan la importancia de una combinación de tres factores en la difusión de información del canal secundario: contenido emocional, identificativo y video. Otras combinaciones de factores también contribuyeron al éxito del tweet.

Estas configuraciones podrían ser útiles para la gestión pública ante una crisis sanitaria como la Covid-19, prestando atención a los factores cuya configuración atrae la difusión de información en las RRSS. En lugar de suprimir estos canales, se presentan soluciones para garantizar una colaboración eficaz.

Este estudio realiza una contribución académica a las comunicaciones extraoficiales en situaciones de emergencia, proporcionando información para comprender y gestionar este tipo de canales.

Covid-19, Coronavirus, Canal extraoficial, Twitter, Análisis cualitativo comparado

Trabajo de investigación

在新冠疫情初期, 由于可能引起社会恐慌和政府管理部门的负面形象, 官方媒体缺少相关的新闻报道。本文研究了在这种官方信息匮乏的危机时期, 非正式渠道（backchannel）对于新冠病毒内容的接受和传播情况, 本文同时反思了如何对这类非正式渠道进行正确的管理。

基于文献综述, 我们先将在线内容传播的可能解释变量分为内容丰富度和心理内容这两个方面。其次, 我们对推特上的非正式渠道账户@COVID_19NEWS发布的内容进行情感分析, 并使用定性比较分析法来寻找内容获得高转发率的原因。

结果显示, 对于非正式渠道信息的成功传播, 情绪化、具有辩认度和包含视频内容这三个要素的组合占主导地位。此外, 其他要素的组合也有来助于推文的成功传播和扩散。

了解非正式渠道吸引信息传播的主要原因, 将有利于应对健康危机（例如Covid-19爆发）和进行公共管理。文本讨论了不同的解决方案, 而不是简单地压制这些非正式渠道。

这项研究推进了危机背景下非正式渠道传播的学术研究, 为理解和管理这类非正式渠道提供了见解。

关键词 - Covid-19, 新冠病毒, 非正式渠道, 推特, 定性比较分析

The purpose of this study is to determine the satisfaction of the guests who stay at hotels offering technology-supported products and services related to the services and products they receive by using the opinion mining technique.

In this research, 12,396 customer reviews on booking.com related to ten hotels belonging to a hotel chain using technology-supported products were evaluated with aspect-based sentiment analysis techniques.

As a result of this study, it has been determined that using technology in hotel businesses creates a positive impression on customer satisfaction. It has been determined that the enrichment of standard hotel business products such as beds and room lighting with technology, in a way that will not be very costly, affects the guests. In addition, it is interesting that technological features such as robots and room service robots, which are called “High & Technology” in this study, are evaluated by customers in the service process.

The hotel managements have the opportunity to evaluate the services we offer by analyzing their online comments and to see their own image from the eyes of the guests. Hotel businesses must learn about customer expectations for technologies with high investment costs. This study, which analyzes online customer reviews, enables tourism businesses that offer technology-supported products and services and invest in technology in service delivery, to understand how customers evaluate the service.

In this study, customer reviews of a hotel group operating in many countries belonging to a hotel group that enriches its standard products with technology and provides service with the concept of a “smart hotel” were examined. This study contributes to the understanding of customers' experience of using technological products in hotel businesses. This study contributes to the literature on customers' satisfaction with technological hotel products and services and the decision of hotels to invest in technology.

本研究通过使用意见挖掘技术旨在确定入住酒店的客人的满意度。这些客人接受酒店提供的产品相关的技术支持和服务。

在这项研究中, 使用基于特定方面的情感分析技术评估了 booking.com 上与属于连锁酒店的 10 家酒店相关的 12,396 条客户评论, 这些酒店均使用科技支持的产品。

作为这项研究的结果, 已经确定在酒店业务中使用科技会对客户满意度产生积极的影响。已经确定, 标准酒店商务产品（例如床、房间照明等）的丰富科技以不会非常昂贵的方式影响客人。此外, 客户感兴趣的是在本研究的服务过程中包括机器人和技术特征, 例如客房服务机器人, 作为“高科技”层面。

酒店管理层分析了客人的在线评论, 并有机会评估他们的服务并从客人的眼中看到自己的形象。酒店企业必须了解客户对高投资成本技术的期望。本研究分析了直接体验过的消费者的意见。因此, 研究结果将使决定投资服务技术的酒店企业受益。

在这项研究中, 我们对一家在许多国家经营的酒店集团的客户评论进行了调查。该酒店属于一家酒店集团, 该集团以技术丰富其标准产品, 并以“智能酒店”的概念提供服务。该研究有助于了解客户在酒店业务中使用技术产品的体验。该研究扩展了客户对酒店科技产品和服务的满意度的文献, 以及对酒店投资技术的决策做出贡献。