Lixue Zou, Xiwen Liu, Wray Buntine and Yanli Liu
Full text of a document is a rich source of information that can be used to provide meaningful topics. The purpose of this paper is to demonstrate how to use citation context (CC…
Abstract
Purpose
Full text of a document is a rich source of information that can be used to provide meaningful topics. The purpose of this paper is to demonstrate how to use citation context (CC) in the full text to identify the cited topics and citing topics efficiently and effectively by employing automatic text analysis algorithms.
Design/methodology/approach
The authors present two novel topic models, Citation-Context-LDA (CC-LDA) and Citation-Context-Reference-LDA (CCRef-LDA). CC is leveraged to extract the citing text from the full text, which makes it possible to discover topics with accuracy. CC-LDA incorporates CC, citing text, and their latent relationship, while CCRef-LDA incorporates CC, citing text, their latent relationship and reference information in CC. Collapsed Gibbs sampling is used to achieve an approximate estimation. The capacity of CC-LDA to simultaneously learn cited topics and citing topics together with their links is investigated. Moreover, a topic influence measure method based on CC-LDA is proposed and applied to create links between the two-level topics. In addition, the capacity of CCRef-LDA to discover topic influential references is also investigated.
Findings
The results indicate CC-LDA and CCRef-LDA achieve improved or comparable performance in terms of both perplexity and symmetric Kullback–Leibler (sKL) divergence. Moreover, CC-LDA is effective in discovering the cited topics and citing topics with topic influence, and CCRef-LDA is able to find the cited topic influential references.
Originality/value
The automatic method provides novel knowledge for cited topics and citing topics discovery. Topic influence learnt by our model can link two-level topics and create a semantic topic network. The method can also use topic specificity as a feature to rank references.
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Kristijian Mirkovski, Yanli Jia, Libo Liu and Kun Chen
The purpose of this paper is to explain how individuals form microblogging habits and why they continue to use microblogs from the perspective of direction social networks.
Abstract
Purpose
The purpose of this paper is to explain how individuals form microblogging habits and why they continue to use microblogs from the perspective of direction social networks.
Design/methodology/approach
Drawing on the social network theory and the social presence theory, the authors develop a theoretical framework to explain how individuals form microblogging habits and why they continue to use microblogs. To test the proposed model and examine its external validity, the authors collected data from two microblogs: Twitter and Sina Weibo.
Findings
Satisfaction and habit have a significant influence on microblogging continuance intention. Whereas, users’ microblogging habits are developed by two key factors – satisfaction and frequency of past behavior – that are further determined by social presence and social network centrality.
Research limitations/implications
Larger sample size with diverse populations is highly recommended for future studies. In addition, exploring the distinct technical functionalities of microblogs when conceptualizing habit formation would be of benefit in future studies.
Practical implications
In this study, it was found that social presence increases both the satisfaction of users and the frequency of past use behavior. Hence, microblog designers should provide users with greater freedom to modify the form and content of their interface, and enable these modifications to be visible in real time to increase the interactivity of microblogs.
Originality/value
In contrast to past studies that have largely neglected the impacts of the directed social network structure, this study aims to focus on microblogging continuance intention from the directed social network perspective. The results from two independent data sets converge on the conclusion that users’ continuance intention to use is affected by both their conscious evaluations (i.e. satisfaction) and unconscious reactions (i.e. habit).
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Catherine Compton-Lilly, Shuning Liu, Maria Padrós Cuxart, Lindsay Pettit and Yanli Timm
This conceptual paper aims to explore biases in reading textbooks that have been used to teach generations of Americans, including children in urban communities. While these texts…
Abstract
Purpose
This conceptual paper aims to explore biases in reading textbooks that have been used to teach generations of Americans, including children in urban communities. While these texts are no longer used, the images they present and the ideas embedded in these texts unfortunately contribute to who we are as a nation.
Design/methodology/approach
These texts were identified by Catherine Compton-Lilly as she trolled the historical archives of a major university.
Findings
In addition to an analysis of historic texts, more recent attempts to create culturally responsive texts often designed to serve children in urban communities are examined, and the learnings from these attempts are being explored.
Practical implications
This conceptual paper points to the need for systematic analyses of biases operating in textbooks that are currently used in schools.
Originality/value
This work reveals and explores one way in which historical bias has historically infected the early learning experiences of young children in the USA.
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Verona Ramas Joseph and Nur Kamaliah Mustaffa
The demand to reduce carbon emissions has become an increasingly important social factor due to the unprecedented impacts of climate change. However, most existing publications…
Abstract
Purpose
The demand to reduce carbon emissions has become an increasingly important social factor due to the unprecedented impacts of climate change. However, most existing publications have focused on minimizing emissions during the operational phase of buildings. At the same time, there is a lack of comprehensive research conducted on carbon emissions, specifically during the construction phase. The purpose of this paper is to identify, review and classify current practices related to carbon emissions management in construction operations to gain greater insight into how to reduce and mitigate emissions and achieve more sustainable solutions.
Design/methodology/approach
This study reviewed the published literature on carbon emissions from construction. A total of 198 bibliographic records were extracted from the Scopus collection database and analyzed using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). PRISMA is used as a basis for reporting possible trends, research methods and strategies used in published literatures. A total of 99 papers related to carbon emissions in the construction operations were further reviewed and analyzed. This review paper draws on existing research and identifies current carbon management patterns in construction projects.
Findings
Data indicated an upward trend in the number of publications in carbon emissions research during the last few years, particularly in 2015, 2017 and 2019. The most significant contributions to the domain were reported from China, Europe and the USA. This paper found that most studies conduct the Life Cycle Assessment (LCA) method to estimate carbon emissions. This paper found that the primary studies have focused on construction machinery and equipment emissions. The strategies such as establishing uniform standards for carbon emissions policies and regulations, equipment and logistic planning and low carbon design material will potentially impact carbon emissions reductions.
Practical implications
This paper provides information that will be beneficial for the construction industry to design and manage construction operations. It will also be of interest to those looking to reduce or manage construction emissions.
Originality/value
Although there is a diversity of current thinking related to the practical estimation and management of carbon emissions in construction projects, there is no consolidated set of keys of standardized carbon emissions management in practice. By assessing the existing paradigms of carbon assessment methods and tactics in the construction industry, this study contributed to the existing knowledge base by providing insights into current techniques in the construction sector for monitoring and mitigating emissions.
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Yanli Fu, Ruiming Liu, Jifeng Yang, Hao Jiao and Yuke Jin
With the aim of shedding new light on the characteristics of human capital in its relationship with organizational innovation, this paper develops a novel theoretical and…
Abstract
Purpose
With the aim of shedding new light on the characteristics of human capital in its relationship with organizational innovation, this paper develops a novel theoretical and empirical exploration of the characteristics of human capital, both executives' experience and employees' average education level, as well as the moderating effect of female ownership, on two different aspects of organizational innovation.
Design/methodology/approach
Data were obtained from the World Bank's China private manufacturing enterprise questionnaire survey. The study employs regression analysis of a logistic model using 1,598 samples, because the dependent variable of an organization's innovation index is a binary variable.
Findings
Using World Bank survey data of Chinese private manufacturing enterprises, the authors find that executives' experience has a significantly positive effect on process innovation. Female ownership strengthens the relationship between executives' experience and process innovation. Moreover, the results indicate that employees' average educational level has a significantly positive effect on product innovation. Female ownership strengthens the relationships between employees' average educational level and organizational innovation including product innovation and process innovation. This study highlights the importance of simultaneously testing the effects of human capital and gender heterogeneity on organizational innovation activities.
Originality/value
This study explores the impact of human capital on organizational innovation activities in the context of the Chinese manufacturing industry. Moreover, organizational innovation activities are divided into two aspects: product innovation and process innovation. This study separately discusses the effect of human capital on these two kinds of innovation in detail. Finally, female ownership is selected as a moderating variable, and it is demonstrated that interactions of female owners with executives' experience and employees' average educational level have a positive impact on increasing different kinds of organizational innovation. The authors identify new boundary conditions for the domain of female research that are sorely lacking in the present literature.
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Yue Yuan, Kan Liu and Yanli Wang
The purpose of this study is to analyze the topics of COVID-19 news articles for better obtaining the relationship among and the evolution of news topics, helping to manage the…
Abstract
Purpose
The purpose of this study is to analyze the topics of COVID-19 news articles for better obtaining the relationship among and the evolution of news topics, helping to manage the infodemic from a quantified perspective.
Design/methodology/approach
To analyze COVID-19 news articles explicitly, this paper proposes a prism architecture. Based on epidemic-related news on China Daily and CNN, this paper identifies the topics of the two news agencies, elucidates the relationship between and amongst these topics, tracks topic changes as the epidemic progresses and presents the results visually and compellingly.
Findings
The analysis results show that CNN has a more concentrated distribution of topics than China Daily, with the former focusing on government-related information, and the latter on medical. Besides, the pandemic has had a big impact on CNN and China Daily's reporting preference. The evolution analysis of news topics indicates that the dynamic changes of topics have a strong relationship with the pandemic process.
Originality/value
This paper offers novel perspectives to review the topics of COVID-19 news articles and provide new understandings of news articles during the initial outbreak. The analysis results expand the scope of infodemic-related studies.
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Rui Wang, Mengxuan Li, Xing Liu and Yanli Sun
This study aims to elaborate on the microencapsulation of the plant extract (PE, from Camellia sinensis leaf, clover flower and cocoa flower) and the preparation of a slow-release…
Abstract
Purpose
This study aims to elaborate on the microencapsulation of the plant extract (PE, from Camellia sinensis leaf, clover flower and cocoa flower) and the preparation of a slow-release lining fabric loading the PE microcapsule.
Design/methodology/approach
PE was microencapsulated into polyvinyl alcohol (PVA) shells through interfacial polymerization. The morphology, thermal stability, slow-release property and drug loading ratio of the PVA/PE microcapsules were characterized to ensure the availability in coating finishing. To find the optimum parameters, the composite fabrics were prepared from non-woven fabrics coated by calcium alginate hydrogel, which glued mass fractions of microcapsules and dried in different ways. To evaluate the effectiveness, a lipase enzyme activity test was conducted.
Findings
Under optimal conditions, the PVA/PE microcapsules with smooth surface have an average particle size of 14.5 um, and they are expected to reach a loading ratio of 38.5 per cent while remaining stable under 220°C. Given a microcapsule of 4 per cent (of the mass), the composite fabric has a good hand feeling, being prepared through calcium chloride coating. It is shown that the inhibition ratios of the microcapsules and composite fabrics on lipase are 31.3 and 21.0 per cent, respectively.
Research limitations/implications
The composite fabric could be prepared through the other finishing methods such as padding and printing. In addition, the release mechanism of the composite could be studied.
Practical implications
This study provided a simple and effective way to prolong the duration of PE. This way was conductive to protect environmental sensitive PEs from being destroyed in compositing processes.
Originality/value
Preparing composite fabrics for transdermal delivery system was novel and other kind of plant extracts could be used in this way.
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Yanli Lu, Yao Yao, Shuang Li, Qian Zhang and Qingjun Liu
Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in…
Abstract
Purpose
Using the remarkable olfaction ability, insects can sense trace amounts of host plant volatiles that are notorious for causing severe damage to fruits and vegetables and in consequence the industry. The purpose of the paper is to investigate the interactions between olfactory proteins, odorant-binding proteins (OBPs) and host plant volatiles through the developed olfactory biosensors. It might be helpful to develop novel pest control strategies.
Design/methodology/approach
Using the successfully expressed and purified OBPs of the oriental fruit fly Bactrocera dorsalis, a biosensor was developed by immobilizing the proteins on interdigitated electrodes through nitrocellulose membrane. Based on electrochemical impedance sensing, benzaldehyde emitted by the host plants, such as Beta vulgaris, was detected, which could be used to investigate and analyze the mechanisms of pests’ sense of chemical signals. The relative decreases of charge transfer resistances of the sensor were proportional to the odorant concentrations from 10−7 M to 10−3 M. Meanwhile, the interactions between OBPs and benzaldehyde were studied through the process of molecular docking.
Findings
The paper provides a pest OBPs-based biosensor that could sensitively detect the host odorants benzaldehyde. Meanwhile, the most related amino acids of OBPs that bind to host plant volatiles can be distinguished with molecular docking.
Originality/value
An olfactory biosensor was developed to explore interactions and mechanism between the pest OBPs and benzaldehyde, which showed promising potentials for small organic molecule sensing. Simultaneously, it might be helpful for novel pest control strategies.
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Yanli Zhai, Gege Luo and Dang Luo
The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.
Abstract
Purpose
The purpose of this paper is to construct a grey incidence model for panel data that can reflect the incidence direction and degree between indicators.
Design/methodology/approach
Firstly, this paper introduces the concept of a negative matrix and preprocesses the data of each indicator matrix to eliminate differences in dimensions and magnitudes between indicators. Then a model is constructed to measure the incidence direction and degree between indicators, and the properties of the model are studied. Finally, the model is applied to a practical problem.
Findings
The grey-directed incidence degree is 1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a positive linear relationship. This degree is −1 if and only if corresponding elements between the feature indicator matrix and the factor indicator matrix have a negative linear relationship.
Practical implications
The example shows the number of days with good air quality is negatively correlated with the annual average concentration of each pollutant index. PM2.5, PM10 and O3 are the main pollutants affecting air quality in northern Henan.
Originality/value
This paper introduces the negative matrix and constructs a model from the holistic perspective to measure the incidence direction and level between indicators. This model can effectively measure the incidence between the feature indicator and factor indicator by integrating information from the point, row, column and matrix.
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Deep learning (DL) technology is used to design a voice evaluation system to understand the impact of learning aids on DL and mobile platforms on students’ learning behavior.
Abstract
Purpose
Deep learning (DL) technology is used to design a voice evaluation system to understand the impact of learning aids on DL and mobile platforms on students’ learning behavior.
Design/methodology/approach
DL technology is used to design a speech evaluation system.
Findings
The experimental results show that the speech evaluation system designed has a high accuracy rate, the highest agreement rate with manual evaluation of pronunciation is 89.5%, and the correct speech recognition rate is 96.64%. The designed voice evaluation system and the manual voice rating system have a maximum error rate of 2%. The experimental results suggest that it is necessary to further optimize the learning aids for mobile platform. The learning aids of the mobile platform need to be further optimized to promote the improvement of student learning efficiency.
Originality/value
The results show that the speech evaluation system designed has good practical application value, and it provides a certain reference value for the future study of learning tools on DL.