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The purpose of this study is to investigate the relationship of the post-publication peer review (PPPR) polarity of a paper to that paper's citation count.

Papers with PPPRs from Publons.com as the experimental groups were manually matched 1:2 with the related papers without PPPR as the control group, by the same journal, the same issue (volume), the same access status (gold open access or not) and the same document type. None of the papers in the experimental group or control group received any comments or recommendations from ResearchGate, PubPeer or F1000. The polarity of the PPPRs was coded by using content analysis. A negative binomial regression analysis was conducted to examine the data by controlling the characteristics of papers.

The four experimental groups and their corresponding control groups were generated as follows: papers with neutral PPPRs, papers with both negative and positive PPPRs, papers with negative PPPRs and papers with positive PPPRs as well as four corresponding control groups (papers without PPPRs). The results are as follows: while holding the other variables (such as page count, number of authors, etc.) constant in the model, papers that received neutral PPPRs, those that received negative PPPRs and those that received both negative and positive PPPRs had no significant differences in citation count when compared to their corresponding control pairs (papers without PPPRs). Papers that received positive PPPRs had significantly greater citation count than their corresponding control pairs (papers without PPPRs) while holding the other variables (such as page count, number of authors, etc.) constant in the model.

Based on a broader range of PPPR sentiments, by controlling many of the confounding factors (including the characteristics of the papers and the effects of the other PPPR platforms), this study analyzed the relationship of various polarities of PPPRs to citation count.

This paper aims to construct a spatio-temporal emotional framework (STEF) for digital humanities from a quantitative perspective, applying knowledge extraction and mining technology to promote innovation of humanities research paradigm and method.

The proposed STEF uses methods of information extraction, sentiment analysis and geographic information system to achieve knowledge extraction and mining. STEF integrates time, space and emotional elements to visualize the spatial and temporal evolution of emotions, which thus enriches the analytical paradigm in digital humanities.

The case study shows that STEF can effectively extract knowledge from unstructured texts in the field of Chinese Qing Dynasty novels. First, STEF introduces the knowledge extraction tools – MARKUS and DocuSky – to profile character entities and perform plots extraction. Second, STEF extracts the characters' emotional evolutionary trajectory from the temporal and spatial perspective. Finally, the study draws a spatio-temporal emotional path figure of the leading characters and integrates the corresponding plots to analyze the causes of emotion fluctuations.

The STEF is constructed based on the “spatio-temporal narrative theory” and “emotional narrative theory”. It is the first framework to integrate elements of time, space and emotion to analyze the emotional evolution trajectories of characters in novels. The execuability and operability of the framework is also verified with a case novel to suggest a new path for quantitative analysis of other novels.

The aim of this study is to examine the existing literature on service robots in order to identify prominent themes, assess the present state of service robotics research and highlight the contributions of seminal publications in the business, management and hospitality domain.

This study analysed 332 Scopus papers from 1985 to 2022 using bibliometric techniques like citation and co-citation analysis.

The study findings highlighted that there has been a consistent rise in publications related to service robots. The paper identifies three significant themes in the service robot literature: adoption of service robots in the context of customer service, anthropomorphism and integration of artificial intelligence in robotic service. Furthermore, this study highlights prominent authors, journals, institutions and countries associated with research on service robots and discusses the future research opportunities in this domain.

This study contributes to the service robots’ literature in the hospitality context by compilation of various reference materials using a comprehensive bibliometric analysis. Previous studies do not point out crucial themes in this area, nor do they provide an overview of prominent journals, institutions, authors and trends in this field. Therefore, this study attempts to fill the lacunae.