With the increasingly huge amount of data located in various databases and the need for users to access them, distributed information retrieval (DIR) has been at the core of the preoccupations of a number of researchers. Indeed, numerous DIR systems and architectures have been proposed including the broker-based architecture. Moreover, providing DIR with more flexibility and adaptability has led researchers

Although higher education institutions (HEIs) are expected to be the leaders in knowledge generation and dissemination, it is often not clear whether they are knowledge-aware, that is, have a knowledge focus. In this article, the communication with stakeholders through HEI websites is examined to determine to what extent these institutions communicate about their knowledge initiatives and projects

Authorship verification (AV) is one of the main problems of authorship analysis and digital text forensics. The classical AV problem is to decide whether or not a particular author wrote the document in question. However, if there is one and relatively short document as the author’s known document, the verification problem becomes more difficult than the classical AV and needs a generalised solution

We present a model of information that integrates two competing perspectives of information by emulating the Chinese philosophy of yin-yang. The model embraces the two key dimensions of information that exist harmoniously: information as (1) objective and veridical representations in the world (information as object) and (2) socially constructed interpretations that are a result of contextual influences

A reading list is a list of reading items recommended by an academic to assist students’ acquisition of knowledge for a specific subject. Subsequently, the libraries of higher education institutions collect and assemble reading lists according to specific courses and offer the students the reading list service. However, the reading list is created based on localised intelligence, restricted to the

Ageing or obsolescence describes the process of declining use of a particular publication over time and can affect the results of a citation analyses as the length of citation window can change rankings. Obsolescence may not only vary across fields but also across subfields or sub-disciplines. The aim of this study is to determine the sub-disciplinary differences of obsolescence on a larger scale allowing

As the huge dimensionality of textual data restrains the classification accuracy, it is essential to apply feature selection (FS) methods as dimension reduction step in text classification (TC) domain. Most of the FS methods for TC contain several number of probabilities. In this study, we proposed a new FS method named as Extensive Feature Selector (EFS), which benefits from corpus-based and class-based

Sentiment analysis (SA) aims to extract users’ opinions automatically from their posts and comments. Almost all prior works have used machine learning algorithms. Recently, SA research has shown promising performance in using the deep learning approach. However, deep learning is greedy and requires large datasets to learn, so it takes more time for data annotation. In this research, we proposed a semiautomatic

Natural disasters cause significant damage, casualties and economical losses. Twitter has been used to support prompt disaster response and management because people tend to communicate and spread information on public social media platforms during disaster events. To retrieve real-time situational awareness (SA) information from tweets, the most effective way to mine text is using natural language

This article is relevant, as in the process when the world community is experiencing crisis phenomena in the public consciousness and social forms of existence, the change of the museum as an accumulator of works of art and cultural centres acquires historical significance. The novelty of the study is determined by the fact that exhibitions can be held not only online or during the period when museums

Clickbait is a strategy that aims to attract people’s attention and direct them to specific content. Clickbait titles, created by the information that is not included in the main content or using intriguing expressions with various text-related features, have become very popular, especially in social media. This study expands the Turkish clickbait dataset that we had constructed for clickbait detection

Different views on the role of personal factors in moderating individual viewing behaviour exist. This study examined the impact of personality traits on individual viewing behaviour of facial stimulus. A total of 96 students (46 males and 50 females, age 23–28 years) were participated in this study. The Big-Five personality traits of all the participants together with data related to their eye-movements

During the last years, several infectious diseases have caused widespread nationwide epidemics that affected information seeking behaviours, people mobility, economics and research trends. Examples of these epidemics are 2003 severe acute respiratory syndrome (SARS) epidemic in mainland China and Hong Kong, 2014–2016 Ebola epidemic in Guinea and Sierra Leone, 2015–2016 Zika epidemic in Brazil, Colombia

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack

Since content audiences, including libraries and information centres, are increasingly geared to digital environments and virtual networks, the production and delivery of high-quality digital content are becoming continuously important. So far, several components have been introduced by researchers for evaluating the quality of digital content generation. However, due to the uncertainty of the importance

This article presents a new query expansion (QE) method aiming to tackle term mismatch in information retrieval (IR). Previous research showed that selecting good expansion terms which do not hurt retrieval effectiveness remains an open and challenging research question. Our method investigates how global statistics of term co-occurrence can be used effectively to enhance expansion term selection and

We argue that citations, as they have different reasons and functions, should not all be treated in the same way. Using the large, annotated dataset of about 10K citation contexts annotated by human experts, extracted from the Association for Computational Linguistics repository, we present a deep learning–based citation context classification architecture. Unlike all existing state-of-the-art feature-based

The newspaper emerged as a distinct cultural form in early 17th-century Europe. It is bound up with the early modern period of history. Historical newspapers are of utmost importance to nations and its people, and researchers from different disciplines rely on these papers to improve our understanding of the past. In pursuit of satisfying this need, Istanbul University Head Office of Library and Documentation

This study surveys the state of the art in usability and user experience strategies applied to applications that deal with large amounts of data in the field of cultural heritage, highlighting the most prominent aspects and underlining the under-explored. In these applications, large amounts of data need to be wisely presented to help final users at drawing conclusions and making decisions. While sophisticated

The purpose of this study is to identify the types of cognitive biases in the process of information retrieval. This research used a mixed-method approach for data collection. The research population consisted of 25 information retrieval specialists and 30 post-graduate students. We employed three tools for collecting data, including a checklist, log files and semi-structured interviews. The findings

The purpose of this study is to develop a text clustering–based analysis of COVID-19 research articles. Owing to the proliferation of published COVID-19 research articles, researchers need a method for reducing the number of articles they have to search through to find material relevant to their expertise. The study analyzes 83,264 abstracts from research articles related to COVID-19. The textual data

To provide junior researchers with domain-specific concepts efficiently, an automatic approach for academic profiling is needed. First, to obtain personal records of a given scholar, typical supervised approaches often utilise structured data like infobox in Wikipedia as training dataset, but it may lead to a severe mis-labelling problem when they are utilised to train a model directly. To address

An information retrieval system (IRS) is used to retrieve documents based on an information need. The IRS makes relevance judgements by attempting to match a query to a document. As IRS capabilities are indexing design dependent, the hybrid indexing method (IRS-H) is introduced. The objectives of this article are to examine IRS-H (as an alternative indexing method that performs exact phrase matching)

Previous research shows that online reviews may have different effects for search goods and experience goods. However, as a typical type of experience goods, software can be further divided into different categories based on product characteristics. Little research has been conducted regarding the different effects of online reviews for different types of software. Furthermore, to offer free samples

With the development of Web 2.0, social media dialogue has been increasingly important within the world of open access (OA), striving for more user-generated content and ease of use. In this article, we analysed the impact of OA articles published by both Chinese and the American researchers using PLOS ONE. Papers published in the same year, using citation and social media metrics, were all used to

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for

Text representation is a fundamental cornerstone that impacts the effectiveness of several text summarization methods. Transfer learning using pre-trained word embedding models has shown promising results. However, most of these representations do not consider the order and the semantic relationships between words in a sentence, and thus they do not carry the meaning of a full sentence. To overcome

Real-time messaging and opinion sharing in social media websites have made them valuable sources of different kinds of information. This source provides the opportunity for doing different kinds of analysis. Sentiment analysis as one of the most important of these analyses gains increasing interests. However, the research in this field is still facing challenges. The mainstream of the sentiment analysis

A two-round Delphi study was conducted to explore priorities for addressing online risk to individuals. A corpus of literature was created based on 69 peer-reviewed articles about privacy risk and the privacy calculus published between 2014 and 2019. A cluster analysis of the resulting text-base using Pearson’s correlation coefficient resulted in seven broad topics. After two rounds of the Delphi survey

Online platforms make it possible for physicians to share online information with the public, however, few studies have explored the underlying mechanism of physicians’ sharing of paid health information. Drawing on motivation theory, this study developed a theoretical framework to explore the effects of extrinsic motivation, enjoyment, and professional motivation on the sharing of paid information

Translation language resources, such as bilingual word lists and parallel corpora, are important factors affecting the effectiveness of cross-language information retrieval (CLIR) systems. In particular, when large domain-appropriate parallel corpora are not available, developing an effective CLIR system is particularly difficult. Furthermore, creating a large parallel corpus is costly and requires

WhatsApp is one of the most used social media tools, but little is known about its use for everyday purposes. In this study, the informational features of WhatsApp in everyday life in Madrid are analysed through 30 semi-structured interviews, resulting in an informational typology of the messages, a description of the informational purposes of WhatsApp use and descriptions of the social use of WhatsApp

Although the citations between scientific documents are deemed as a vehicle for dissemination, inheritance and development of scientific knowledge, not all citations are well-positioned to be equal. A plethora of taxonomies and machine-learning models have been implemented to tackle the task of citation function and importance classification from qualitative aspect. Inspired by the success of kernel

As the next step in the development of intelligent computing systems is the addition of human expertise and knowledge, it is a priority to build strong computable and well-documented knowledge bases. Ontologies partially respond to this challenge by providing formalisms for knowledge representation. However, one major remaining task is the population of these ontologies with concrete application. Based

The rise of social media has offered a fast and easy way for the propagation of conspiracy theories and other types of disinformation. Despite the research attention that has received, fake news detection remains an open problem and users keep sharing articles that contain false statements but which they consider real. In this article, we focus on the role of users in the propagation of conspiracy

COVID-19 has created unprecedented organisational challenges, yet no study has examined the impact on information search. A case study in a knowledge-intensive organisation was undertaken on 2.5 million search queries during the pandemic. A surge of unique users and COVID-19 search queries in March 2020 may equate to ‘peak uncertainty and activity’, demonstrating the importance of corporate search

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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%)

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

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

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

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;

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

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