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Book part
Publication date: 12 November 2018

Adriana Perez-Encinas and Jesus Rodriguez-Pomeda

Studies in higher education tend to use different methods and methodologies, from documentary analysis to auto/biographical and observational studies. Most studies are…

Abstract

Studies in higher education tend to use different methods and methodologies, from documentary analysis to auto/biographical and observational studies. Most studies are either qualitative or qualitative. A mixed-methods approach has emerged in recent years, in which the qualitative approach generally plays an important role. The purpose of this chapter is to show the potential of a new methodology that is also appropriate for higher education research and widely used in the social sciences: probabilistic topic models. A probabilistic method can be used to analyse and categorise thousands of words. After collecting large sets of texts, content analysis is used to deeply analyse the meaning of these words. The huge number of texts published today pushes researchers to employ new techniques in their search for hidden structures built upon a set of core ideas. These methods are called topic modelling algorithms, with Latent Dirichlet Allocation being the basic probabilistic topic model. The application of these new techniques to the field of higher education is extremely useful, for two reasons: (1) studies in this area deal in some cases with a great volume of data and (2) these techniques allow one to devise models in a way that is unsupervised by humans (even when researchers operate on the resulting model); thus they are less subjective than other types of analyses and methods used for qualitative purposes. This chapter shows the foundations and recent applications of the technique in the higher education field, as well as challenges related to this new technique.

Details

Theory and Method in Higher Education Research
Type: Book
ISBN: 978-1-78769-277-0

Keywords

Book part
Publication date: 13 December 2017

Qiongwei Ye and Baojun Ma

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and…

Abstract

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Details

Internet+ and Electronic Business in China: Innovation and Applications
Type: Book
ISBN: 978-1-78743-115-7

Article
Publication date: 7 August 2017

Daniel Carnerud

The purpose of this paper is to explore and describe research presented in the International Journal of Quality & Reliability Management (IJQRM), thereby creating an…

Abstract

Purpose

The purpose of this paper is to explore and describe research presented in the International Journal of Quality & Reliability Management (IJQRM), thereby creating an increased understanding of how the areas of research have evolved through the years. An additional purpose is to show how text mining methodology can be used as a tool for exploration and description of research publications.

Design/methodology/approach

The study applies text mining methodologies to explore and describe the digital library of IJQRM from 1984 up to 2014. To structure and condense the data, k-means clustering and probabilistic topic modeling with latent Dirichlet allocation is applied. The data set consists of research paper abstracts.

Findings

The results support the suggestion of the occurrence of trends, fads and fashion in research publications. Research on quality function deployment (QFD) and reliability management are noted to be on the downturn whereas research on Six Sigma with a focus on lean, innovation, performance and improvement on the rise. Furthermore, the study confirms IJQRM as a scientific journal with quality and reliability management as primary areas of coverage, accompanied by specific topics such as total quality management, service quality, process management, ISO, QFD and Six Sigma. The study also gives an insight into how text mining can be used as a way to efficiently explore and describe large quantities of research paper abstracts.

Research limitations/implications

The study focuses on abstracts of research papers, thus topics and categories that could be identified via other journal publications, such as book reviews; general reviews; secondary articles; editorials; guest editorials; awards for excellence (notifications); introductions or summaries from conferences; notes from the publisher; and articles without an abstract, are excluded.

Originality/value

There do not seem to be any prior text mining studies that apply cluster modeling and probabilistic topic modeling to research article abstracts in the IJQRM. This study therefore offers a unique perspective on the journal’s content.

Details

International Journal of Quality & Reliability Management, vol. 34 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 5 September 2017

Azadeh Mohebi, Mehri Sedighi and Zahra Zargaran

The purpose of this paper is to introduce an approach for retrieving a set of scientific articles in the field of Information Technology (IT) from a scientific database…

Abstract

Purpose

The purpose of this paper is to introduce an approach for retrieving a set of scientific articles in the field of Information Technology (IT) from a scientific database such as Web of Science (WoS), to apply scientometrics indices and compare them with other fields.

Design/methodology/approach

The authors propose to apply a statistical classification-based approach for extracting IT-related articles. In this approach, first, a probabilistic model is introduced to model the subject IT, using keyphrase extraction techniques. Then, they retrieve IT-related articles from all Iranian papers in WoS, based on a Bayesian classification scheme. Based on the probabilistic IT model, they assign an IT membership probability for each article in the database, and then they retrieve the articles with highest probabilities.

Findings

The authors have extracted a set of IT keyphrases, with 1,497 terms through the keyphrase extraction process, for the probabilistic model. They have evaluated the proposed retrieval approach with two approaches: the query-based approach in which the articles are retrieved from WoS using a set of queries composed of limited IT keywords, and the research area-based approach which is based on retrieving the articles using WoS categorizations and research areas. The evaluation and comparison results show that the proposed approach is able to generate more accurate results while retrieving more articles related to IT.

Research limitations/implications

Although this research is limited to the IT subject, it can be generalized for any subject as well. However, for multidisciplinary topics such as IT, special attention should be given to the keyphrase extraction phase. In this research, bigram model is used; however, one can extend it to tri-gram as well.

Originality/value

This paper introduces an integrated approach for retrieving IT-related documents from a collection of scientific documents. The approach has two main phases: building a model for representing topic IT, and retrieving documents based on the model. The model, based on a set of keyphrases, extracted from a collection of IT articles. However, the extraction technique does not rely on Term Frequency-Inverse Document Frequency, since almost all of the articles in the collection share a set of same keyphrases. In addition, a probabilistic membership score is defined to retrieve the IT articles from a collection of scientific articles.

Book part
Publication date: 13 December 2017

Qiongwei Ye and Baojun Ma

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and…

Abstract

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Details

Internet+ and Electronic Business in China: Innovation and Applications
Type: Book
ISBN: 978-1-78743-115-7

Article
Publication date: 14 September 2022

Muhammad Inaam ul haq, Qianmu Li, Jun Hou and Adnan Iftekhar

A huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the…

Abstract

Purpose

A huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the research structure of social media.

Design/methodology/approach

This study employs an integrated topic modeling and text mining-based approach on 30381 Scopus index titles, abstracts, and keywords published between 2006 and 2021. It combines analytical analysis of top-cited reviews with topic modeling as means of semantic validation. The output sequences of the dynamic model are further analyzed using the statistical techniques that facilitate the extraction of topic clusters, communities, and potential inter-topic research directions.

Findings

This paper brings into vision the research structure of social media in terms of topics, temporal topic evolutions, topic trends, emerging, fading, and consistent topics of this domain. It also traces various shifts in topic themes. The hot research topics are the application of the machine or deep learning towards social media in general, alcohol consumption in different regions and its impact, Social engagement and media platforms. Moreover, the consistent topics in both models include food management in disaster, health study of diverse age groups, and emerging topics include drug violence, analysis of social media news for misinformation, and problems of Internet addiction.

Originality/value

This study extends the existing topic modeling-based studies that analyze the social media literature from a specific disciplinary viewpoint. It focuses on semantic validations of topic-modeling output and correlations among the topics and also provides a two-stage cluster analysis of the topics.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 2 January 2018

Daniel Carnerud

The purpose of this paper is to explore and describe how research on quality management (QM) has evolved historically. The study includes the complete digital archive of…

3195

Abstract

Purpose

The purpose of this paper is to explore and describe how research on quality management (QM) has evolved historically. The study includes the complete digital archive of three academic journals in the field of QM. Thereby, a unique depiction of how the general outlines of the field as well as trends in research topics have evolved through the years is presented.

Design/methodology/approach

The study applies cluster and probabilistic topic modeling to unstructured data from The International Journal of Quality & Reliability Management, The TQM Journal and Total Quality Management & Business Excellence. In addition, trend analysis using support vector machine is performed.

Findings

The study identifies six central, perpetual themes of QM research: control, costs, reliability and failure; service quality; TQM – implementation and performance; ISO – certification, standards and systems; Innovation, practices and learning and customers – research and product design. Additionally, historical surges and shifts in research focus are recognized in the study. From these trends, a decrease in interest in TQM and control of quality, costs and processes in favor of service quality, customer satisfaction, Six Sigma, Lean and innovation can be noted during the past decade. The results validate previous findings.

Originality/value

Of the identified central themes, innovation, practices and learning appears not to have been documented as a fundamental part of QM research in previous studies. Thus, this theme can be regarded as a new perspective on QM research and thereby on QM.

Details

International Journal of Quality & Reliability Management, vol. 35 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 4 May 2022

Muhammad Inaam ul haq, Qianmu Li and Jun Hou

Special education is the education segment that deals with the students facing hurdles in the traditional education system. Research data have evolved in the domain of…

Abstract

Purpose

Special education is the education segment that deals with the students facing hurdles in the traditional education system. Research data have evolved in the domain of special education due to scientific advances. The present study aims to employ text mining to extract the latent patterns from the scientific data.

Design/methodology/approach

This study examined the 12,781 Scopus-indexed titles, abstracts and keywords published from 1987 to 2021 through an integrated text-mining and topic modeling approach. It combines dynamic topic models with highly cited reviews of this domain. It facilitates the extraction of topic clusters and communities in the topic network.

Findings

This methodology discovered children’s communication and speech using gaming techniques, mental retardation, cost effect on infant birth, involvement of special education children and their families, assistive technology information for special education, syndrome epilepsy and the impact of group study on skill development peers or self as the hottest topic of research in this domain. In addition to finding research hotspots, it further explores annual topic proportion trends, topic correlations and intertopic research areas.

Originality/value

The results provide a comprehensive summary of the popularity of research topics in special education in the past 34 years, and the results can provide useful insights and implications, and it could be used as a guide for contributors in special education form a structured view of past research and plan future research directions.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 5 January 2018

Tehmina Amjad, Ali Daud and Naif Radi Aljohani

This study reviews the methods found in the literature for the ranking of authors, identifies the pros and cons of these methods, discusses and compares these methods. The…

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Abstract

Purpose

This study reviews the methods found in the literature for the ranking of authors, identifies the pros and cons of these methods, discusses and compares these methods. The purpose of this paper is to study is to find the challenges and future directions of ranking of academic objects, especially authors, for future researchers.

Design/methodology/approach

This study reviews the methods found in the literature for the ranking of authors, classifies them into subcategories by studying and analyzing their way of achieving the objectives, discusses and compares them. The data sets used in the literature and the evaluation measures applicable in the domain are also presented.

Findings

The survey identifies the challenges involved in the field of ranking of authors and future directions.

Originality/value

To the best of the knowledge, this is the first survey that studies the author ranking problem in detail and classifies them according to their key functionalities, features and way of achieving the objective according to the requirement of the problem.

Details

Library Hi Tech, vol. 36 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 9 December 2019

Noor Arshad, Abu Bakar, Saira Hanif Soroya, Iqra Safder, Sajjad Haider, Saeed-Ul Hassan, Naif Radi Aljohani, Salem Alelyani and Raheel Nawaz

The purpose of this paper is to present a novel approach for mining scientific trends using topics from Call for Papers (CFP). The work contributes a valuable input for…

270

Abstract

Purpose

The purpose of this paper is to present a novel approach for mining scientific trends using topics from Call for Papers (CFP). The work contributes a valuable input for researchers, academics, funding institutes and research administration departments by sharing the trends to set directions of research path.

Design/methodology/approach

The authors procure an innovative CFP data set to analyse scientific evolution and prestige of conferences that set scientific trends using scientific publications indexed in DBLP. Using the Field of Research code 804 from Australian Research Council, the authors identify 146 conferences (from 2006 to 2015) into different thematic areas by matching the terms extracted from publication titles with the Association for Computing Machinery Computing Classification System. Furthermore, the authors enrich the vocabulary of terms from the WordNet dictionary and Growbag data set. To measure the significance of terms, the authors adopt the following weighting schemas: probabilistic, gram, relative, accumulative and hierarchal.

Findings

The results indicate the rise of “big data analytics” from CFP topics in the last few years. Whereas the topics related to “privacy and security” show an exponential increase, the topics related to “semantic web” show a downfall in recent years. While analysing publication output in DBLP that matches CFP indexed in ERA Core A* to C rank conference, the authors identified that A* and A tier conferences not merely set publication trends, since B or C tier conferences target similar CFP.

Originality/value

Overall, the analyses presented in this research are prolific for the scientific community and research administrators to study research trends and better data management of digital libraries pertaining to the scientific literature.

Details

Library Hi Tech, vol. 40 no. 1
Type: Research Article
ISSN: 0737-8831

Keywords

1 – 10 of over 3000