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This work studies automated user classification on Twitter in the public health domain, a task that is essential to many public health-related research works on social media but has not been addressed. The purpose of this paper is to obtain empirical knowledge on how to optimise the classifier performance on this task.

A sample of 3,100 Twitter users who tweeted about different health conditions were manually coded into six most common stakeholders. The authors propose new, simple features extracted from the short Twitter profiles of these users, and compare a large set of classification models (including state-of-the-art) that use more complex features and with different algorithms on this data set.

The authors show that user classification in the public health domain is a very challenging task, as the best result the authors can obtain on this data set is only 59 per cent in terms of F1 score. Compared to state-of-the-art, the methods can obtain significantly better (10 percentage points in F1 on a “best-against-best” basis) results when using only a small set of 40 features extracted from the short Twitter user profile texts.

The work is the first to study the different types of users that engage in health-related communication on social media, applicable to a broad range of health conditions rather than specific ones studied in the previous work. The methods are implemented as open source tools, and together with data, are the first of this kind. The authors believe these will encourage future research to further improve this important task.

The purpose of this work is to study how different stakeholders of a football club engage with interactions online through Twitter. It analyses the football club’s Twitter network to discover influential actors and the topic of interest in their online communication.

The authors analysed the social networks derived from over two million tweets collected during football matches played by Manchester United. The authors applied social network analysis to discover influencers and sub-communities and performed content analysis on the most popular tweets of the prominent influencers.

Sub-communities can be formed around current affairs that are irrelevant to football, perhaps due to opportunistic attempts of using the large networks and massive attention during football matches to disseminate information. Furthermore, the popularity of tweets featuring different topics depends on the types of influencers involved.

The methods can help football clubs develop a deeper understanding of their online social communities. The findings can also inform football clubs on how to optimise their communication strategies by using various influencers.

Compared to previous research, the authors discovered a wide range of influencers and denser networks characterised by a smaller number of large clusters. Interestingly, this study also found that bots appeared to become influential within the network.

This study aims to present that the chemo-responsive shape recovery of thermoplastic polyurethane (TPU) is tunable by solvents with different solubility parameters, and it is generic for chemo-responsive shape-memory polymer and its composites.

Two kinds of commercial TPU samples with different thicknesses were prepared by panel vulcanizer and injection molding (an industrial manner) to investigate their chemo-responsive shape memory properties in acetic ether and acetone.

Results showed that all of TPU films with different thicknesses can fully recover their original shapes weather they recover in acetic ether or acetone. But the recovery time of TPU films in acetone is greatly reduced, especially for the twisting samples. The residual strains of recovery TPU samples after extension reduce obviously.

The great decrement of recovery time is related to two factors. One is due to the bigger solubility parameter of acetone with higher dipole moment compared with those of acetic ether, and the other is the remained internal stress of TPU films after preparation. The internal stress is identified to have an effect on the shape-memory properties by comparing the recovery process of samples with/without annealing. The reduced residual strains of recovery TPU samples after extension is due to the increasing mobility of polymer segments after molecules of acetic ether penetrates into the polymeric chains.

This is a universal strategy to control the recovery process of shape-memory materials or composites. The underlying mechanism is generic and should be applicable to chemo-responsive shape-memory polymers or their composites.

The speed of internationalization is an important research topic in the process of internationalization. This paper aims to answer two questions: first, what is the relationship between the speed of internationalization of Chinese multinational firms and their performance? Second, how do potential slack and knowledge assets of firms affect this relationship?

The authors choose Chinese A-share listed manufacturing firms from 2009–2018 as the research sample and use the fixed-effect regression model to test the proposed hypotheses.

Firstly, there is an inverted U-shaped relationship between the speed of internationalization and firm performance (SI-P). Secondly, the potential slack and knowledge assets of firms moderate the inverted U-shaped relationship. Firms with a higher level of potential slack or knowledge assets have a flatter inverted U-shaped relationship between SI-P.

First, the authors develop and extend Penrose’s theory of firm growth to the research topic of speed of internationalization. Second, this paper incorporates the time dimension into the research on the internationalization process and locates the research context in emerging market firms (EMFs). This is a step forward in clarifying the complex relationship of SI-P. Third, the authors show that the SI-P relationship of EMFs is inverted U-shaped and integrate previous studies, which argue that rapid internationalization positively or negatively affects firm performance. Fourth, starting from inside the firm, the authors provide more contextual factors for better understanding and analysis of the SI-P relationship.

This paper expects to analyze the connection between occupational stigma and job meaningfulness among Chinese takeaway riders, the mediating role of occupational identity and relative deprivation, and the moderating effect of job stress based on resource conservation theory.

The sample was derived from 371 takeaway riders across China. PLS-SEM was mainly utilized for the data analysis.

The findings of the study indicated a significant negative correlation between occupational stigma and job meaningfulness. Furthermore, it is worth noting that relative deprivation and occupational identity served as mediators and masks, respectively, in the relationship between occupational stigma and job meaningfulness. Furthermore, job stress amplifies the association between occupational stigma and occupational identity. Additionally, job stress diminishes the connection between occupational stigma and relative deprivation.

This study proposes a positive correlation between occupational stigma and occupational identity in the Chinese context. It also enriches the empirical research based on resource conservation theory. Furthermore, it holds practical implications for takeaway riders in China, offering insights to bolster their job meaningfulness.

This research aims to investigate the impact of the collaborative governance mechanism on the implementation of rural governance information systems in developing countries. By integrating institutional logic theory, affordance theory and social identity theory, the authors propose modeling grassroots officials' affordance perception process and exploring the importance of multi-identities’ information technology (IT) goals in affordance perception.

Through an exploratory case study, the authors identified three affordances of rural governance information systems and investigated the mechanisms influencing the perception of these affordances among grassroots officials. Next, the authors established a research model and collected 490 valid questionnaires from grassroots officials in China and analyzed the data using structural equation modeling (SEM).

The authors' study challenges previous assumptions by integrating institutional logic, affordance and social identity theories. The authors establish a perceived affordance path for rural governance information systems, recognize substitute effects among technological affordances and extend the theory to explain social factors influencing IT perception. The authors' findings suggest providing technical training for grassroots officials to enhance IT capabilities, and governments should prioritize essential functionalities in rural governance information systems to optimize resources. Training on collaborative governance mechanisms can improve IT affordance perception, enhancing digital platform utilization in governance processes.

The study was conducted mainly in China, and therefore, the findings may not be universal to other developing countries. Researchers are therefore encouraged to test the proposal in locations with different rural cultures.

The paper includes implications for the development of IT perception in rural governance, the development of affordance perception theory and studying the relationship between IT goals and affordance perception.

Overall, this paper addresses the need to understand how grassroots officials perceive IT affordances in rural governance and study the relationship between multi-identities’ goals and affordance perception.

The purpose of this paper is twofold: first, determining which factors critically influence asymmetrical trust behaviors in construction projects within the Chinese context; second, proposing corresponding measures to deal with the asymmetrical behaviors of both the owner and the contractor promoting cooperative relationships among participants in construction organizations.

A theoretical model was developed and a questionnaire survey was conducted with 183 professionals. The data collected were analyzed by the structural equation modeling (SEM) technique.

The results identified six critical factors influencing trust asymmetry behavior in construction projects. The power imbalance, information asymmetry and cognitive difference have a positive influence on both upward-trust behavior and downward-trust behavior in the construction organization, while the competence, performance capacity and relationship satisfaction have negative effects.

This paper based on the assumption that trust asymmetry behavior has a negative impact on project performance, which should be further studied. Besides, future research may carry out a comparative analysis among the trusting relationships and behavior of different participants dynamically.

This paper contributes to the literature in three aspects. First, the factors influencing trust behavior in project organization have been identified for the first time. Second, a comprehensive view of trust asymmetry behavior has been theorized by SEM method. Third, the result bridges the existing gap caused by the lack of empirical evidence to understand the genetic mechanisms of trust asymmetry behavior in the construction industry.

With the rapid development of the economy, carbon emissions have also risen sharply. This study explores the relationship between the two by combining the literature of relevant fields and maps the analytical framework from the knowledge base to the research frontier model using CiteSpace.

Using CiteSpace and data statistical tools, we conducted a bibliometric and visual analysis of nearly ten thousand research papers on carbon emissions and economic development published in the Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) databases from 1991 to 2021.

It shows that research on economic development and carbon emissions is developing steadily and involves a wide range of fields. Notably, keywords such as “carbon emissions,” “economic growth,” and “energy consumption” had high frequency, centrality, and persistence. “carbon emissions,” “economic growth,” and “energy consumption” had high frequency, centrality, and persistence. Research institutions in the USA and China have made great contributions to research on economic development and carbon emissions. The authors should continue to enrich and improve research on related subjects and concerns to reasonably plan the path of carbon emission reduction and economic development.

The study analyzes the evolution of the relationship between carbon emissions and economic growth to provide scholars a more comprehensive and in-depth understanding of the relationship from an international perspective.

Template matching is one of the most suitable choices for full six degrees of freedom pose estimation in many practical industrial applications. However, the increasing number of templates while dealing with a wide range of viewpoint changes results in a long runtime, which may not meet the real-time requirements. This paper aims to improve matching efficiency while maintaining sample resolution and matching accuracy.

A multi-pyramid-based hierarchical template matching strategy is proposed. Three pyramids are established at the sphere subdivision, radius and in-plane rotation levels during the offline template render stage. Then, a hierarchical template matching is performed from the highest to the lowest level in each pyramid, narrowing the global search space and expanding the local search space. The initial search parameters at the top level can be determined by the preprocessing of the YOLOv3 object detection network to further improve real-time performance.

Experimental results show that this matching strategy takes only 100 ms under 100k templates without loss of accuracy, promising for real industrial applications. The authors further validated the approach by applying it to a real robot grasping task.

The matching framework in this paper improves the template matching efficiency by two orders of magnitude and is validated using a common template definition and viewpoint sampling methods. In addition, it can be easily adapted to other template definitions and viewpoint sampling methods.

This paper aims to extract the comment targets in Chinese online shopping platform.

The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.

The extracting comment target method the authors proposed in this paper is effective.

First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.

Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.

The extracting comment target method the authors proposed in this paper is effective.