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Proposing an information value chain to improve information services to disabled library patrons using assistive technologies J. Inf. Sci. (IF 2.41) Pub Date : 2021-01-12 Devendra Potnis; Kevin Mallary
Information services offered by academic libraries increasingly rely on assistive technologies (AT) to facilitate disabled patrons’ retrieval and use of information for learning and teaching. However, disabled patrons’ access to AT might not always lead to their use, resulting in the underutilization of information services offered by academic libraries. We adopt an inward-looking, service innovation
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Embodying algorithms, enactive artificial intelligence and the extended cognition: You can see as much as you know about algorithm J. Inf. Sci. (IF 2.41) Pub Date : 2021-01-12 Donghee Shin
The recent proliferation of artificial intelligence (AI) gives rise to questions on how users interact with AI services and how algorithms embody the values of users. Despite the surging popularity of AI, how users evaluate algorithms, how people perceive algorithmic decisions, and how they relate to algorithmic functions remain largely unexplored. Invoking the idea of embodied cognition, we characterize
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A study of Turkish emotion classification with pretrained language models J. Inf. Sci. (IF 2.41) Pub Date : 2021-01-12 Alaettin Uçan; Murat Dörterler; Ebru Akçapınar Sezer
Emotion classification is a research field that aims to detect the emotions in a text using machine learning methods. In traditional machine learning (TML) methods, feature engineering processes cause the loss of some meaningful information, and classification performance is negatively affected. In addition, the success of modelling using deep learning (DL) approaches depends on the sample size. More
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An exploratory study of the all-author bibliographic coupling analysis: Taking scientometrics for example J. Inf. Sci. (IF 2.41) Pub Date : 2021-01-03 Song Yanhui; Wu Lijuan; Chen Shiji
All-author bibliographic coupling analyses (AABCA) take all authors of the article into account when constructing author coupling relationships. Taking scientometrics as an example, this article takes the papers from 2010 to 2019 as data sample and divides them into two periods (limited to 5 years) to discuss the performance of AABCA in discovering potential academic communities and intellectual structure
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Information security: Legal regulations in Azerbaijan and abroad J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-28 Amir I Aliyev; Aytakin N Ibrahimova; Gulnaz A Rzayeva
The article is devoted to information security issues in the world and in Azerbaijan, in particular. The article compares laws and regulations of Azerbaijan and other countries in the cybersecurity policy between them. The article reveals the features of the organisational and legal regulation of the information security system as an integral part of state security. A number of aspects of ensuring
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Using community information for natural disaster alerts J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-22 Chun Chieh Chen; Hei-Chia Wang
Recently, the ceaseless rise in the global average temperature has led to extreme climates in which natural disasters, such as droughts, hurricanes, earthquakes and floods, are becoming increasingly serious. Recent research has found that social media typically reflects disasters earlier than official communication channels. In this study, the idea of collecting information on flood disasters caused
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Investigating Reddit to detect subreddit and author stereotypes and to evaluate author assortativity J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-20 Francesco Cauteruccio; Enrico Corradini; Giorgio Terracina; Domenico Ursino; Luca Virgili
In recent years, Reddit has attracted the interest of many researchers due to its popularity all over the world. In this article, we aim at providing a contribution to the knowledge of this social network by investigating three of its aspects, interesting from the scientific viewpoint, and, at the same time, by analysing a large number of applications. In particular, we first propose a definition and
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Influence and performance of user similarity metrics in followee prediction J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-03 Antonela Tommasel; Daniela Godoy
Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. Hence, understanding how users select whom to follow becomes crucial for designing accurate and personalised recommendation strategies. This work aims at shedding some light on how homophily drives the formation of user relationships by studying the influence of diverse recommendation
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Testing the validity of Wikipedia categories for subject matter labelling of open-domain corpus data J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-03 Ahmad Aghaebrahimian; Andy Stauder; Michael Ustaszewski
The Wikipedia category system was designed to enable browsing and navigation of Wikipedia. It is also a useful resource for knowledge organisation and document indexing, especially using automatic approaches. However, it has received little attention as a resource for manual indexing. In this article, a hierarchical taxonomy of three-level depth is extracted from the Wikipedia category system. The
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Exploiting user network topology and comment semantic for accurate rumour stance recognition on social media J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-03 Yongcong Luo; Jing Ma; Chai Kiat Yeo
Online social media (OSM) has become a hotbed for the rapid dissemination of disinformation or fake news. In order to recognise fake news and guide users of OSM, we focus on the stance recognition of comments, posted on OSM on the fake news-related users. In this article, we propose a framework for recognition of rumour stances (we set four categories –‘agree’, ‘disagree’, ‘neutral’ and ‘query’), combining
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Deep Persian sentiment analysis: Cross-lingual training for low-resource languages J. Inf. Sci. (IF 2.41) Pub Date : 2020-12-02 Rouzbeh Ghasemi; Seyed Arad Ashrafi Asli; Saeedeh Momtazi
With the advent of deep neural models in natural language processing tasks, having a large amount of training data plays an essential role in achieving accurate models. Creating valid training data, however, is a challenging issue in many low-resource languages. This problem results in a significant difference between the accuracy of available natural language processing tools for low-resource languages
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A spike in the scientific output on social sciences in Vietnam for recent three years: Evidence from bibliometric analysis in Scopus database (2000–2019) J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-30 Binh Pham-Duc; Trung Tran; Thao-Phuong-Thi Trinh; Tien-Trung Nguyen; Ngoc-Trang Nguyen; Hien-Thu-Thi Le
Bibliometric analysis of 3105 publications retrieved from the Scopus database was conducted to evaluate bibliographic content of scientific output on social sciences in Vietnam, for the 2000–2019 period. Our main findings show that the number of publications on social sciences from Vietnam has increased significantly over the last two decades, and there was a spike in the scientific output for the
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Topic attention encoder: A self-supervised approach for short text clustering J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-30 Jian Jin; Haiyuan Zhao; Ping Ji
Short text clustering is a challenging and important task in many practical applications. However, many Bag-of-Word–based methods for short text clustering are often limited by the sparsity of text representation, while many sentence embedding–based methods fail to capture the document structure dependencies within a text corpus. In considerations of the shortcomings of many existing studies, a topic
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Investigating information seeking in physical and online environments with escape room and web search J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-26 Dongho Choi; Chirag Shah; Vivek Singh
Searching and interacting with information is one of the most fundamental behaviours of human beings – something that takes place in both online and physical environments. Yet, most studies of information interaction have focused on only one of these sides. This work aims to connect them by investigating one’s information interaction behaviours in different physical and online contexts as well as different
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Dynamical entropic analysis of scientific concepts J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-22 Artem Chumachenko; Boris Kreminskyi; Iurii Mosenkis; Alexander Yakimenko
In the present era of information, the problem of effective knowledge retrieval from a collection of scientific documents becomes especially important for continuous scientific progress. The information available in scientific publications traditionally consists of bibliometric metadata and its semantic component such as title, abstract and text. While the former having a machine-readable format usually
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Research practices of LIS professionals in Pakistan: A study of attitudes, involvement and competencies J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-17 Arslan Sheikh; Amara Malik; Khalid Mahmood
This study analyses the attitudes, involvement and competencies of Pakistani Library Information Science (LIS) professionals towards research. An online survey was carried out by using a questionnaire to collect data from LIS professionals working in various types of libraries in Pakistan. The findings reveal that the overall attitude of the Pakistani LIS professionals towards research is positive
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TIPS: Time-aware Personalised Semantic-based query auto-completion J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-08 Saedeh Tahery; Saeed Farzi
With the rapid growth of the Internet, search engines play vital roles in meeting the users’ information needs. However, formulating information needs to simple queries for canonical users is a problem yet. Therefore, query auto-completion, which is one of the most important characteristics of the search engines, is leveraged to provide a ranked list of queries matching the user’s entered prefix. Although
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Measuring visibility of disciplines on Chinese academic web J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-03 Bo Yang; Ying Sun; Shan Huang
This study proposes a hierarchy affiliation model (department–school–university) to build network between web entities taking into account the domain names, the topological structure of academic network and the disciplinary characteristics of schools and universities synthetically. The study of the Chinese academic web based on the model shows that at the school level, 68 of 95 disciplines (71.6%)
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On the relationship between supervisor–supervisee gender difference and scientific impact of doctoral dissertations: Evidence from Humanities and Social Sciences in China J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-03 Yi Bu; Hanlin Li; Chunli Wei; Meijun Liu; Jiang Li
This article explores the relationships between supervisor–supervisee gender difference and the scientific impact of doctoral dissertations. We use the China Doctoral Dissertations Full-text Database and pay special attention to the fields of Humanities and Social Sciences in China in our empirical study. By establishing regression models, we find that the ranks of the scientific impact regarding doctoral
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Link prediction in supernetwork: Risk perception of emergencies J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-01 Ning Ma; Yijun Liu; Liangliang Li
After an emergency incident occurs, how to identify risks, predict trends and scientifically cope before the crisis erupts is the basic starting point of this study. In this study, a supernetwork model of the risk perception in emergencies is innovatively constructed from the perspective of the governance of risks. This supernetwork model includes three subnetworks: the similar relationship subnetwork
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Understanding social media discontinuance from social cognitive perspective: Evidence from Facebook users J. Inf. Sci. (IF 2.41) Pub Date : 2020-11-01 Shaoxiong Fu; Hongxiu Li
Based on social cognitive theory, this study proposes a research framework to investigate two different social media discontinuance behaviours: reduced usage and abandoned usage. Specifically, perceived technology overload, information overload and social overload are the environmental factors that induce negative personal states, including dissatisfaction and social media fatigue, which lead to negative
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A new similarity measure for vector space models in text classification and information retrieval J. Inf. Sci. (IF 2.41) Pub Date : 2020-10-27 Mete Eminagaoglu
There are various models, methodologies and algorithms that can be used today for document classification, information retrieval and other text mining applications and systems. One of them is the vector space–based models, where distance metrics or similarity measures lie at the core of such models. Vector space–based model is one of the fast and simple alternatives for the processing of textual data;
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Text and metadata extraction from scanned Arabic documents using support vector machines J. Inf. Sci. (IF 2.41) Pub Date : 2020-10-15 Wenda Qin; Randa Elanwar; Margrit Betke
Text information in scanned documents becomes accessible only when extracted and interpreted by a text recognizer. For a recognizer to work successfully, it must have detailed location information about the regions of the document images that it is asked to analyse. It will need focus on page regions with text skipping non-text regions that include illustrations or photographs. However, text recognizers
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Analysis of direct citation, co-citation and bibliographic coupling in scientific topic identification J. Inf. Sci. (IF 2.41) Pub Date : 2020-10-07 Rajmund Kleminski; Przemysiaw Kazienko; Tomasz Kajdanowicz
In our study, we examine the impact of citation network structures on the ability to discern valuable research topics in Computer Science literature. We use the bibliographic information available in the DBLP database to extract candidate phrases from scientific paper abstracts. Following that, we construct citation networks based on direct citation, co-citation and bibliographic coupling relationships
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Mining information from sentences through Semantic Web data and Information Extraction tasks J. Inf. Sci. (IF 2.41) Pub Date : 2020-10-04 Jose L. Martinez-Rodriguez; Ivan Lopez-Arevalo; Ana B. Rios-Alvarado
The Semantic Web provides guidelines for the representation of information about real-world objects (entities) and their relations (properties). This is helpful for the dissemination and consumption of information by people and applications. However, the information is mainly contained within natural language sentences, which do not have a structure or linguistic descriptions ready to be directly processed
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Do researchers use open research data? Exploring the relationships between usage trends and metadata quality across scientific disciplines from the Figshare case J. Inf. Sci. (IF 2.41) Pub Date : 2020-10-04 Alfonso Quarati; Juliana E Raffaghelli
Open research data (ORD) have been considered a driver of scientific transparency. However, data friction, as the phenomenon of data underutilisation for several causes, has also been pointed out. A factor often called into question for ORD low usage is the quality of the ORD and associated metadata. This work aims to illustrate the use of ORD, published by the Figshare scientific repository, concerning
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Prediction of online topics’ popularity patterns J. Inf. Sci. (IF 2.41) Pub Date : 2020-09-21 Hengmin Zhu; Yanshuang Mei; Jing Wei; Chao Shen
Popularity prediction of online contents is always a tool of emergency management, business decision-making, and public opinion monitoring. Most previous work has made efforts to predict the volumes or levels of popularity, but patterns of popularity evolution are remaining largely unexplored. Actually, topic popularity patterns can offer more detailed information for event detection and early warning
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A semi-hierarchical clustering method for constructing knowledge trees from stackoverflow J. Inf. Sci. (IF 2.41) Pub Date : 2020-09-21 Chun-Hsiung Tseng; Jia-Rou Lin
To help students learn how to programme, we have to give them a clear knowledge map and sufficient materials. Question-based websites, such as stackoverflow, are excellent information sources for this goal. However, for beginners, the process can be a little tricky since they may not know how to ask correct questions if they do not have sufficient background knowledge, and a knowledge tree is usually
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Factors influencing researchers’ journal selection decisions J. Inf. Sci. (IF 2.41) Pub Date : 2020-09-16 Jennifer Rowley; Laura Sbaffi; Martin Sugden; Anna Gilbert
The scholarly publication landscape continues to grow in complexity, presenting researchers with ever-increasing dilemmas regarding journal choice. However, research into the decision-making processes associated with journal choice is limited. This article contributes by reporting on an international survey of researchers in various disciplines and with varying levels of experience. The study examines
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Optimal policy learning for COVID-19 prevention using reinforcement learning J. Inf. Sci. (IF 2.41) Pub Date : 2020-09-16 M Irfan Uddin; Syed Atif Ali Shah; Mahmoud Ahmad Al-Khasawneh; Ala Abdulsalam Alarood; Eesa Alsolami
COVID-19 has changed the lifestyle of many people due to its rapid human-to-human transmission. The spread started at the end of January 2020, and different countries used different approaches in terms of testing, sanitization, lock down and quarantine centres to control the spread of the virus. People are getting back to working and routine life activities with new normal standards of testing, sanitization
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Discovering informative features in large-scale landmark image collection J. Inf. Sci. (IF 2.41) Pub Date : 2020-09-01 Ala’a Alzou’bi; Keng Hoon Gan
One of the key problems in image retrieval systems is the presence of irrelevant and noisy image content. Such content can cause significant confusion for the system. Therefore, there is a need to represent images with only informative features in order to improve the retrieval performance of the system or any subsequent process. In this article, we propose a method to identify the informative features
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An overview of literature on COVID-19, MERS and SARS: Using text mining and latent Dirichlet allocation J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-31 Xian Cheng; Qiang Cao; Stephen Shaoyi Liao
The unprecedented outbreak of COVID-19 is one of the most serious global threats to public health in this century. During this crisis, specialists in information science could play key roles to support the efforts of scientists in the health and medical community for combatting COVID-19. In this article, we demonstrate that information specialists can support health and medical community by applying
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Quantifying and analysing the stages of online information dissemination in different enterprise emergencies: The idea of system cybernetics J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-30 Yongtian Yu; Guang Yu; Xiangbin Yan; Xiao Yu
Previous research on information dissemination in emergencies focus on prediction of the volume via abundant models. However, most of these models did not specify different stages of emergencies, and hence making it difficult for public relations (PR) practitioner to make decisions based on needs of each stage in today’s rapid changing media environments. In this study, we introduce the idea of system
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A multi-strategy approach for the merging of multiple taxonomies J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-30 Mao Chen; Chao Wu; Zongkai Yang; Sanya Liu; Zengzhao Chen; Xiuling He
Taxonomy merging is an important work to provide a uniform schema for several heterogeneous taxonomies. Previous studies primarily focus on merging two taxonomies in a specific domain, while the merging of multiple taxonomies has been neglected. This article proposes a taxonomy merging approach to automatically merge multiple source taxonomies into a target taxonomy in an asymmetric manner. The approach
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Exploring research trends in big data across disciplines: A text mining analysis J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-24 Ehsan Mohammadi; Amir Karami
Using big data has been a prevailing research trend in various academic fields. However, no studies have explored the scope and structure of big data across disciplines. In this article, we applied topic modeling and word co-occurrence analysis methods to identify key topics from more than 36,000 big data publications across all academic disciplines between 2012 and 2017. The results revealed several
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Reusing digital collections from GLAM institutions J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-24 Gustavo Candela; María Dolores Sáez; MPilar Escobar Esteban; Manuel Marco-Such
For some decades now, Galleries, Libraries, Archives and Museums (GLAM) institutions have published and provided access to information resources in digital format. Recently, innovative approaches have appeared such as the concept of Labs within GLAM institutions that facilitates the adoption of innovative and creative tools for content delivery and user engagement. In addition, new methods have been
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Exploring direct citations between citing publications J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-21 Yong Huang; Yi Bu; Ying Ding; Wei Lu
This article defines and explores the direct citations between citing publications (DCCPs) of a publication. We construct an ego-centred citation network for each paper that contains all of its citing papers and itself, as well as the citation relationships among them. By utilising a large-scale scholarly dataset from the computer science field in the Microsoft Academic Graph (MAG-CS) dataset, we find
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On the measurement of scientific leadership J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-21 Nadia Simoes; Nuno Crespo
The hα index was recently proposed to measure the degree of scientific leadership. While the concept is useful and interesting, namely, as a complement to the traditional performance analysis, the metric suffers from important shortcomings. We argue that scientific leadership should be evaluated: (1) taking into account information of the moment the paper is produced/published, and (2) in the specific
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A method of semi-automated ontology population from multiple semi-structured data sources J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-21 Irina Leshcheva; Alena Begler
Organisations use data in different formats: Word documents, Excel spreadsheets, databases, HTML pages and so on. It is not easy to make decisions with such data due to the lack of integration between the different sources and built-in decision-making rules. Decisions can be reached with knowledge bases, which, unlike databases, make it possible to store not only objects, facts and attributes but also
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Negotiating change: Transition as a central concept for information literacy J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-18 Alison Hicks
Transition forms a dynamic concept that has been underexplored within information literacy research and practice. This article uses the grounded theory of mitigating risk, which was produced through doctoral research into the information literacy practices of language-learners, as a lens for a more detailed examination of transition and its role within information literacy. This framing demonstrates
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Does the mobility of scientists disrupt their collaboration stability? J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-09 Zhenyue Zhao; Yi Bu; Jiang Li
To explore to what extent the mobility of scientists disrupts the stability of their research collaboration, we designed a measure − Collaboration Stability After Moving (CSAM) − for scientists, retrieved 4343 US-related scientists’ curricula vitae (CVs) from the Open Researcher and Contributor ID (ORCID) website and publication records in the Web of Science database and applied a linear regression
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Evaluating the quality of linked open data in digital libraries J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-03 Gustavo Candela; Pilar Escobar; Rafael C Carrasco; Manuel Marco-Such
Cultural heritage institutions have recently started to share their metadata as Linked Open Data (LOD) in order to disseminate and enrich them. The publication of large bibliographic data sets as LOD is a challenge that requires the design and implementation of custom methods for the transformation, management, querying and enrichment of the data. In this report, the methodology defined by previous
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A content-based technique for linking dual language news articles in an archive J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-03 Muzammil Khan; Arif Ur Rahman; Arshad Ahmad; Sarwar Shah Khan
To retrieve a specific news article from a vast archive containing multilingual news articles against a user query or based on similarity among news articles is a challenging task. The task becomes even further complicated when the archive contains articles from a low resourced and morphologically complex language like Urdu, along with English new articles. The article proposes a content-based (lexical)
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The distinctiveness of author interdisciplinarity: A long-neglected issue in research on interdisciplinarity J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-03 Wenyu Zhang; Shunshun Shi; Xiaoling Huang; Shuai Zhang; Peijia Yao; Yilei Qiu
In the research on interdisciplinarity (RID), measures for evaluating the interdisciplinarity of scientific entities (e.g., papers, authors, journals or research areas) have been proposed for a long time. The author interdisciplinarity is very different from the other types of interdisciplinarity because of the complex interpersonal relationships between the connected authors. However, previous work
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REDI: Towards knowledge graph-powered scholarly information management and research networking J. Inf. Sci. (IF 2.41) Pub Date : 2020-08-03 José Ortiz Vivar; José Segarra; Boris Villazón-Terrazas; Víctor Saquicela
Academic data management has become an increasingly challenging task as research evolves over time. Essential tasks such as information retrieval and research networking have turned into extremely difficult operations due to an ever-growing number of researchers and scientific articles. Numerous initiatives have emerged in the IT environments to address this issue, especially focused on web technologies
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Identification of rumour stances by considering network topology and social media comments J. Inf. Sci. (IF 2.41) Pub Date : 2020-07-29 Yongcong Luo; Jing Ma; Chai Kiat Yeo
Online social media (OSM) has become a hotbed for the rapid dissemination of disinformation or faked news. In order to track and limit the spread of faked news, we study stance identification of comments posted on OSM, where the stance can denote the comment’s semantics. In this article, we propose a framework for identification of rumour stances, combining network topology and OSM comments. We construct
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How do academia and society react to erroneous or deceitful claims? The case of retracted articles’ recognition J. Inf. Sci. (IF 2.41) Pub Date : 2020-07-29 Hajar Sotudeh; Nilofar Barahmand; Zahra Yousefi; Maryam Yaghtin
Researchers give credit to peer-reviewed, and thus, credible publications through citations. Despite a rigorous reviewing process, certain articles undergo retraction due to disclosure of their ethical or scientific deficiencies. It is, therefore, important to understand how society and academia react to the erroneous or deceitful claims and purge the science of their unreliable results. Applying a
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Understanding the evolution of a scientific field by clustering and visualizing knowledge graphs J. Inf. Sci. (IF 2.41) Pub Date : 2020-07-09 Mauro Dalle Lucca Tosi; Julio Cesar dos Reis
The process of tracking the evolution of a scientific field is arduous. It allows researchers to understand trends in areas of science and predict how they may evolve. Nowadays, most of the automated mechanisms developed to assist researchers in this process do not consider the content of articles to identify changes in its structure, only the articles metadata. These methods are not suited to easily
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Does the use of open, non-anonymous peer review in scholarly publishing introduce bias? Evidence from the F1000Research post-publication open peer review publishing model J. Inf. Sci. (IF 2.41) Pub Date : 2020-07-05 Mike Thelwall; Liz Allen; Eleanor-Rose Papas; Zena Nyakoojo; Verena Weigert
As part of moves towards open knowledge practices, making peer review open is cited as a way to enable fuller scrutiny and transparency of assessments around research. There are now many flavours of open peer review in use across scholarly publishing, including where reviews are fully attributable and the reviewer is named. This study examines whether there is any evidence of bias in two areas of common
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Twenty-six years of LIS research focus and hot spots, 1990–2016: A co-word analysis J. Inf. Sci. (IF 2.41) Pub Date : 2020-07-02 Reza Mokhtarpour; Ali Akbar Khasseh
The purpose of this research is to map and analyse the conceptual and thematic structure of library and information science (LIS) research from the perspective of the co-word analysis. The bibliographical records consist of all the research papers published in the LIS core journals between 1990 and 2016 and indexed in Web of Science. ‘CiteSpace’ was used to visualise the co-word network of LIS studies
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A domain knowledge graph construction method based on Wikipedia J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-29 Haoze Yu; Haisheng Li; Dianhui Mao; Qiang Cai
In order to achieve real-time updating of the domain knowledge graph and improve the relationship extraction ability in the construction process, a domain knowledge graph construction method is proposed. Based on the structured knowledge in Wikipedia’s classification system, we acquire concepts and instances contained in subject areas. A relationship extraction algorithm based on co-word analysis is
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Modelling users’ perceptions of video information seeking, learning through added value and use of curated digital collections J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-24 Dan Albertson; Melissa P Johnston
Information seeking research has provided models of users in the search for information across many different contexts and situations. Digital content curation has emerged as a means for managing information and facilitating user learning by adding ‘value’ to digital content in different ways, enhancing the user experience. Using digital video and K–12 education as the context, this study examined
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A topic analysis method based on a three-dimensional strategic diagram J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-24 Jia Feng; Xiaomin Mu; Wei Wang; Ying Xu
With the tremendous growth of scientific literature in recent years, methods of detecting and analysing research topics have become more and more important. This study proposes a topic analysis method combining latent Dirichlet allocation (LDA) and a three-dimensional strategic diagram. This study constructs the three-dimensional strategic diagram by three dimensions of centrality, density and novelty
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NaLa-Search: A multimodal, interaction-based architecture for faceted search on linked open data J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-24 José Luis Sánchez-Cervantes; Giner Alor-Hernández; Mario Andrés Paredes-Valverde; Lisbeth Rodríguez-Mazahua; Rafael Valencia-García
Mobile devices are the technological basis of computational intelligent systems, yet traditional mobile application interfaces tend to rely only on the touch modality. That said, such interfaces could improve human–computer interaction by combining diverse interaction modalities, such as visual, auditory and touch. Also, a lot of information on the Web is published under the Linked Data principles
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The impact of semantic annotation techniques on content-based video lecture recommendation J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-22 Laura Lima Dias; Eduardo Barrére; Jairo Francisco de Souza
Increasing videos available in educational content repositories makes searching difficult, and recommendation systems have been used to help students and teachers receive a content of interest. Speech is an important carrier of information in video lectures and is used by content-based video recommendation systems. Although automatic speech recognition (ASR) transcripts have been used in modern video
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The effects of globalisation techniques on feature selection for text classification J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-18 Bekir Parlak; Alper Kursat Uysal
Text classification (TC) is very important and critical task in the 21th century as there exist high volume of electronic data on the Internet. In TC, textual data are characterised by a huge number of highly sparse features/terms. A typical TC consists of many steps and one of the most important steps is undoubtedly feature selection (FS). In this study, we have comprehensively investigated the effects
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Sentiment analysis of tweets through Altmetrics: A machine learning approach J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-15 Saeed-Ul Hassan; Aneela Saleem; Saira Hanif Soroya; Iqra Safder; Sehrish Iqbal; Saqib Jamil; Faisal Bukhari; Naif Radi Aljohani; Raheel Nawaz
The purpose of the study is to (a) contribute to annotating an Altmetrics dataset across five disciplines, (b) undertake sentiment analysis using various machine learning and natural language processing–based algorithms, (c) identify the best-performing model and (d) provide a Python library for sentiment analysis of an Altmetrics dataset. First, the researchers gave a set of guidelines to two human
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Using social media during job search: The case of 16–24 year olds in Scotland J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-11 John A Mowbray; Hazel Hall
Social media are powerful networking platforms that provide users with significant information opportunities. Despite this, little is known about their impact on job search behaviour. Here, interview (participants = 7), focus group (participants = 6) and survey (n = 558) data supplied by young jobseekers in Scotland were analysed to investigate the role of social media in job search. The findings show
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From words to connections: Word use similarity as an honest signal conducive to employees’ digital communication J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-09 Andrea Fronzetti Colladon; Johanne Saint-Charles; Pierre Mongeau
Bringing together considerations from three research trends (honest signals of collaboration, socio-semantic networks and homophily theory), we hypothesise that word use similarity and having similar social network positions are linked with the level of employees’ digital interaction. To verify our hypothesis, we analyse the communication of close to 1600 employees, interacting on the intranet communication
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Supporting information use and task accomplishment: What system features do users like and expect? J. Inf. Sci. (IF 2.41) Pub Date : 2020-06-08 Jingjing Liu; Yuan Li
Information systems have been improving in helping users find information. However, they have been less attended to regarding helping searchers in using located information. This research attempts to address the issue of information use by investigating what information systems and features searchers think are helpful in using located information to accomplish information tasks. In all, 32 college
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