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Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers.

This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords.

Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich.

This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

The publishers of International Journal of Crowd Science wish to retract the article “Quality-time-complexity universal intelligence measurement”, by Wen Ji, Jing Liu, Zhiwen Pan, Jingce Xu, Bing Liang, and Yiqiang Chen, which appeared in volume 2, issue 1, 2018. It has come to our attention that due to an error in the submission process the above article is an earlier version of the article published in International Journal of Crowd Science, volume 2, issue 2, 2018 (DOI: https://doi.org/10.1108/IJCS-04-2018-0007). The duplicate publication was the result of an inadvertent administrative error by the authors. The authors and publishers of the journal sincerely apologise to the readers.

This research aims to investigate the current patterns of social media adoption for marketing in the restoration industry and analyse the strategies used by those restoration companies that have adopted social media. Social media marketing has been proven as a cost-effective way to engage new customers, and especially useful for small businesses. The disaster “restoration industry” is the special sector of general contracting that serves both commercial and residential property owners in terms of restoring their disaster-affected property. The restoration industry is characterised by small-business domination and constant need of new customers to survive in the market. Many restoration contractors have started adopting social media for marketing. However, goals and social media marketing strategies have not yet been clearly articulated.

Data were collected through a systematic content analysis (CA) of sample restoration companies’ Facebook and Twitter posts over a 30-day study period. After a preliminary investigation of the industry, the researchers selected the Restoration Industry Association (RIA) member companies, as the research population. Sixty companies were randomly selected from the 1,165 RIA member companies, which equals to 5 per cent of the population. Reliability was tested statistically using Cohen’s Kappa.

Three levels of adoption were derived from the data: active users, non-active users and non-adopters. More than half of the sample companies were found to have adopted at least one social media channel for marketing. However, only 26 out of the 60 sample companies were active on the social media that they have adopted. Active adopters showed, on average, relatively frequent usage patterns, with 10 Facebook posts and 37 tweets in a 30-day period. Sampled restoration companies which were active social media users posted mostly announcements and educational information of Facebook and used Twitter for news and direct interaction with customers. The observed companies revealed a mix of business-relevant content and personalised content including personal greetings, sharing of photos about holidays and fun events.

Three levels of adoption were derived from the data: active users, non-active users and non-adopters. More than half of the sample companies were found to have adopted at least one social media channel for marketing. However, only 26 out of the 60 sample companies were active on the social media that they have adopted. Active adopters showed, on average, relatively frequent usage patterns, with 10 Facebook posts and 37 tweets in a 30-day period. Sampled restoration companies that were active social media users posted mostly announcements and educational information of Facebook and used Twitter for news and direct interaction with customers. The observed companies revealed a mix of business-relevant content and personalised content including personal greetings, sharing of photos about holidays and fun events.

The results showed that social media adoption has not yet penetrated the restoration industry – the adoption rate of 65 per cent is significantly lower than the 77 per cent of companies in all industries. In-depth CA of active social media users revealed patterns of engagement on Facebook and Twitter. This paper built on those patterns to emphasise strategies restoration companies can use to build interpersonal relationships and trust, which can lead to increased word-of-mouth recommendations; facilitate customer contact through a cross-linking strategy; and engage in simple methods for search engine optimisation. These strategic recommendations are grounded in existing practices and, therefore, are feasible and accessible for disaster restoration companies.

The research results showed how the construction industry, especially small businesses, has adopted social media for marketing. A snapshot of the industry’s level of social media adoption for marketing strategy can provide a useful reference point about the industry’s practices and potential future directions. This paper provides suggestions about effective social media marketing strategies. The paper also illustrates the use of CA as a promising method for research in construction management.

With the increasingly intensifying competition and the development and maturity of the modern organization, employees have no longer fully been attached to the organization. The employee‐organization relationship gets more and more attention. As spokespersons of their organizations, the leaders in all levels, to a considerable extent, have an effect on the understanding of the employee for the organization. The purpose of this paper is to explore leader and member exchange (LMX) relationships' impact on employees' organizational commitment and discuss the mediating effect of perceived organizational support (POS) during the period.

A sample consisting of 423 employees in four organizations was investigated. After testing the reliability of all questionnaires, the authors constructed a model of the mediating effect of POS between LMX relationships' impact on employees' organizational commitment and used structural equation model technology to verify it.

The results showed that: affect, loyalty and professional respect have a significant impact on affective commitment but the result of the contribution is not significant. So, work exchange (contribution) was different from social exchange (affect, loyalty and professional respect) in the influence on employee's organizational affective commitment. POS had an intermediary effect between the affect exchange and affective commitment in the organization. Leader‐membership has an important implication for the employee‐organization relationship. The exchanges of different dimensions between the leader and the member were different no matter for the affected contents of the attitude to the organization of the employee or for the affecting mechanism.

All variable data came from the same employee questionnaires, which may lead to potential problems of same source bias or common method variance. In order to test the influence of common method variance, this research carried out Harman's one‐factor test.

The organization should emphasize developing the relationship between the leaders from various levels and the members, and in particular the social exchange out of the work must not be neglected.

The present study explores LMX's influence on employees' affective commitment towards the organization from a social exchange perspective. The authors adopted multi‐dimensions LMX, which is different from prior studies (e.g. Wayne et al. and Zhou and Bao) to discuss the mechanism of LMX's impact on subordinates' attitudes to the organization.

The purpose of the research is to assess the risk of the financial market in the digital economy through the quantitative analysis model in the big data era. It is a big challenge for the government to carry out financial market risk management in the big data era.

In this study, a generalized autoregressive conditional heteroskedasticity-vector autoregression (GARCH-VaR) model is constructed to analyze the big data financial market in the digital economy. Additionally, the correlation test and stationarity test are carried out to construct the best fit model and get the corresponding VaR value.

Owing to the conditional heteroscedasticity, the index return series shows the leptokurtic and fat tail phenomenon. According to the AIC (Akaike information criterion), the fitting degree of the GARCH model is measured. The AIC value difference of the models under the three distributions is not obvious, and the differences between them can be ignored.

Using the GARCH-VaR model can better measure and predict the risk of the big data finance market and provide a reliable and quantitative basis for the current technology-driven regulation in the digital economy.

The purpose of this paper is to investigate the immiscible two-layer heat fluid flows in the presence of the electric double layer (EDL) and magnetic field. The effects of EDL, magnetic field and the viscous dissipative term on fluid velocity and temperature, as well as the important physical quantities, are examined and discussed.

The upper and lower regions in a horizontal microchannel with one layer being filled with a nanofluid and the other with a viscous Newtonian fluid. The nanofluid flow in the lower layer is described by the Buongiorno’s nanofluid model with passively controlled model at the boundaries. An appropriate set of non-dimensional quantities are used to simplify the nonlinear systems. The resulting coupled nonlinear equations are solved by using homotopy analysis method.

The present work demonstrates that increasing the EDL thickness and Hartmann number can restrain the fluid flow. The Brinkmann number has a significant role in the enhancement of heat transfer. It is also identified that the influence of EDL effects on microflow cannot be ignored.

The effects of viscous dissipation involved in the heat transfer process and the body force because of the EDL and the magnetic field are considered in the thermal energy and momentum equations for both regions. The detailed derivation procedure of the analytical solution for electrostatic potential is provided. The analytical solutions can lead to improved understanding of the complex microfluidic systems.

Yi Jing is one of the most archaic works among the Chinese classics. Various schools of thought developed their philosophies from the philosophical perspectives in this book and its influence is wide ranging and far reaching. This paper attempts to show how leaders can approach the Yi Jing beneficially by identifying the principles, values and virtues in each of the 64 scenarios, deriving insights about change and leadership. It also aims to show how the Yi Jing compares with Western management literature.

This paper provides an analysis of Qian Gua of Yi Jing as an example of how leaders can draw insights from Yi Jing about change and leadership.

Qian Gua, which is the first scenario in the Yi Jing, offers us powerful insights about change and leadership by offering: a framework of understanding change and human enterprises, considering the aspects of beginning, process, benefit and sustainability; a framework to understand the leadership development process; and leadership principles of conscientious self‐cultivation, transformational leadership through virtues and riding the tides of change.

A change and leadership model inspired by the Yi Jing should interest business leaders both in the east and the west, and help Westerners gain success in doing business in China or collaborating with the Chinese on a joint venture.

This is the first paper to draw insights about change and leadership through an analysis of Qian Gua of Yi Jing.

The purpose of this paper is to find a new method to reinforce high-density polyethylene (HDPE) with polyacrylonitrile fibers (PAN). Furthermore, the crystallinity, viscoelasticity and thermal properties of HDPE composites have also been investigated and compared.

For effective reinforcing, samples with different content fillers were prepared. HDPE composites were prepared by melt blending with double-screw extruder prior to cutting into particles and the samples for testing were made using an injection molding machine.

With the addition of 9 Wt.% PAN fibers, it was found that the tensile strength and flexural modulus got the maximum value in all HDPE composites and increased by 1.2 times than pure HDPE. The shore hardness, storage modulus and vicat softening point of the composites improved continuously with the increase in the proportion of the fibers. The thermal stability and processability of composites did not change rapidly with the addition of PAN fibers. The degree of crystallinity increased with the addition of PAN fibers. In general, the composites achieve the best comprehensive mechanical properties with the fiber content of 9 Wt.%.

The fibers improve the strength of the polyethylene and enhance its ability to resist deformation.

The modified HDPE by PAN fibers in this study have high tensile strength and resistance to deformation and can be used as an efficient material in engineering, packaging and automotive applications.

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.

This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.

By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.

This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

High reliability and high power-to-weight ratio are the technical difficulties in the development of aviation piston heavy fuel engines. This paper aims to provide a design evaluation method of the aero piston engine block, which can help R&D personnel quickly evaluate the performance of engine block, including effective bearing capacity and fatigue deformation, save a lot of experimental time and shorten the R&D cycle.

In this paper, structural efficiency is used to evaluate the reliability and durability of the engine block. Structural efficiency is a new evaluation method that lists its corresponding connotation according to different objects. In this paper, the function of the engine block in the engine is explained in detail, and three quantifiable connotations of the structural efficiency of the engine block are put forward. In the subsequent calculation, the calculation is carried out according to the three indexes, and the calculation results are used as the indexes to evaluate the performance of the engine block.

The structural efficiency evaluation method proposed in this paper can quickly and effectively evaluate the performance of the block from many aspects. Under the same boundary conditions, the two design schemes are simulated and analyzed, and the durability test is carried out. The analysis and experimental results show that Scheme 2 has good performance, which verifies the feasibility of the evaluation method.

This paper provides a method for rapid evaluation of engine block performance.