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Disinformation on social media is a serious issue. This study examines the effects of disinformation on COVID-19 vaccination decision-making to understand how social media users make healthcare decisions when disinformation is presented in their social media feeds. It examines trust in post owners as a moderator on the relationship between information types (i.e. disinformation and factual information) and vaccination decision-making.

This study conducts a scenario-based web survey experiment to collect extensive survey data from social media users.

This study reveals that information types differently affect social media users' COVID-19 vaccination decision-making and finds a moderating effect of trust in post owners on the relationship between information types and vaccination decision-making. For those who have a high degree of trust in post owners, the effect of information types on vaccination decision-making becomes large. In contrast, information types do not affect the decision-making of those who have a very low degree of trust in post owners. Besides, identification and compliance are found to affect trust in post owners.

This study contributes to the literature on online disinformation and individual healthcare decision-making by demonstrating the effect of disinformation on vaccination decision-making and providing empirical evidence on how trust in post owners impacts the effects of information types on vaccination decision-making. This study focuses on trust in post owners, unlike prior studies that focus on trust in information or social media platforms.

The purpose of this paper is to further explore the co-citation and bibliographic-coupling relationship among the core authors in the field of Chinese information science (IS), to expose research activity and author impact, and to make induction analyses about Chinese IS research patterns and theme evolution.

The research data include 8,567 papers and 70,947 cited articles in the IS field indexed by Chinese Social Sciences Citation Index from 2000 to 2009. Author co-citation analysis, author bibliographic-coupling analysis, social network analysis, and factor analysis were combined to explore co-citation and bibliographic-coupling relationships and to identify research groups and subjects.

Scholars with greatest impact are different from the most active scholars of Chinese IS; there is no uniform impact pattern forming since authors’ impact subjects are scattered and not steady; while authors’ research activities present higher independence and concentration, there is still no steady research pattern due to no deep research existing. Furthermore, Chinese IS studies can be delineated by: foundation or extension. The research subjects of these two parts, as well as their corresponding/contributing authors, are different under different views. The general research status of core authors is concentrated, while their impact is broad.

The combined use of some related methods could enrich the development and methodology research of the discipline, and the results establish a reference point on the development of IS research.

Library science and information science, two subdisciplines of library and information science (LIS), are developed independently but interconnectedly. In this information age, LIS is in a special period of transformation and development, which has caused some changes in both library science and information science. By accurately capturing these changes and analyzing them, the authors can effectively map the development of LIS in the new century, thus providing a reference for the evolution and development of the field. The purposes of this paper are to explore the mainstream research fields and frontiers of library science and information science, respectively, since the new century, and to make a comparative analysis of the two subdisciplines.

By using CiteSpace to visualize LIS journals, this study draws knowledge maps of the two subdisciplines of LIS through the co-occurrence descriptors network. Using burst detection algorithm, this study detects words of high frequency variation by investigating the time frequency distribution.

The results show that the research focus of library science has experienced a change from traditional to digital library while information science has moved from information to data focus. This study also finds the similarities and differences between mainstream areas of library science and information science.

This study focuses on the evolution of library science and information science, and explores their mainstream research fields and frontiers in the 21st century. These findings will promote the transformation and development of LIS as well as provide research directions for scholars in the field.

The purpose of this paper is to examine the impact of the compensation amount as well as the mode through which compensations are paid on farmers’ satisfaction with the compensation received for farmland expropriation in China.

Using rural household survey data collected among 450 households in three provinces, located in eastern, central and western China, this paper estimates the impacts of compensation payments, compensation modes, household characteristics and other control variables on farmers’ satisfaction applying an ordinal probit model.

The major findings are: farmers’ satisfaction with the compensation depends not only on the size of the compensation but also on the gap between the compensation and the market value of the expropriated land; and the compensation amount positively affects farmers’ satisfaction when the social security compensation mode is used, but does not significantly affect farmers’ satisfaction when other modes are used.

First, it contributes to the literature on farmland expropriation by providing empirical evidence of the direct impact of the compensation amount and other factors on the degree of farmers’ satisfaction with farmland compensations. Second, potential interactions between compensation amount and compensation mode are taken into account in estimating factors affecting farmers’ satisfaction.

This paper aims to embrace the challenge of performing a state-of-the-art scientific literature analysis in data science for hospitality and tourism. This is important because relatively little contemporary analysis has been published.

Data on over 800 publications were collected from the Scopus database and analyzed by the differing types of publications, evolution of publications across time, top publishers and outlets, publications per area and per topic, top keywords used, most cited papers and most productive authors.

Conclusions are drawn and some suggestions are offered regarding topics that are likely to provide opportunities for future research.

This paper identifies the need for analysis on state-of-the-art academic research published to-date on the application of methods and techniques relating to data science in hospitality and tourism.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.