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Open access

Ronald Rousseau

Abstract

Purpose

New developments in the study of delayed recognition are discussed.

Design/methodology/approach

Based on these new developments a method is proposed to characterize delayed recognition as a fuzzy concept.

Findings

A benchmark value of 0.333 corresponding with linear growth is obtained. Moreover, a case is discovered in which an expert found delayed recognition several years before citation analysis could discover this phenomenon.

Research limitations

As all citation studies also this one is database dependent.

Practical implications

Delayed recognition is turned into a fuzzy concept.

Originality/value

The article presents a new way of studying delayed recognition.

Open access

Jose A. Moral-Munoz, Manuel Arroyo-Morales, Barbara F. Piper, Antonio I. Cuesta-Vargas, Lourdes Díaz-Rodríguez, William C.S. Cho, Enrique Herrera-Viedma and Manuel J. Cobo

Abstract

Purpose

The main goal of this study is to discover the scientific evolution of Cancer-Related Symptoms in Complementary and Alternative Medicine research area, analyzing the articles indexed in the Web of Science database from 1980 to 2013.

Design/Methodology/Approach

A co-word science mapping analysis is performed under a longitudinal framework (1980 to 2013). The documental corpus is divided into two subperiods, 1980–2008 and 2009–2013. Thus, the performance and impact rates, and conceptual evolution of the research field are shown.

Findings

According to the results, the co-word analysis allows us to identify 12 main thematic areas in this emerging research field: anxiety, survivors and palliative care, meditation, treatment, symptoms and cancer types, postmenopause, cancer pain, low back pain, herbal medicine, children, depression and insomnia, inflammation mediators, and lymphedema. The different research lines are identified according to the main thematic areas, centered fundamentally on anxiety and suffering prevention. The scientific community can use this information to identify where the interest is focused and make decisions in different ways.

Research limitation

Several limitations can be addressed: 1) some of the Complementary and Alternative Medicine therapies may not have been included; 2) only the documents indexed in Web of Science are analyzed; and 3) the thematic areas detected could change if another dataset was considered.

Practical implications

The results obtained in the present study could be considered as an evidence-based framework in which future studies could be built.

Originality/value

Currently, there are no studies that show the thematic evolution of this research area.

Open access

Haiyun Xu, Chao Wang, Kun Dong, Rui Luo, Zenghui Yue and Hongshen Pang

Abstract

Purpose

This study aims at identifying potential industry-university-research collaboration (IURC) partners effectively and analyzes the conditions and dynamics in the IURC process based on innovation chain theory.

Design/methodology/approach

The method utilizes multisource data, combining bibliometric and econometrics analyses to capture the core network of the existing collaboration networks and institution competitiveness in the innovation chain. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors.

Findings

Empirical analysis of the genetic engineering vaccine field shows that through the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify the more complementary capacities among organizations.

Research limitations

In this study, the overall approach is shaped by the theoretical concept of an innovation chain, a linear innovation model with specific types or stages of innovation activities in each phase of the chain, and may, thus, overlook important feedback mechanisms in the innovation process.

Practical implications

Industry-university-research institution collaborations are extremely important in promoting the dissemination of innovative knowledge, enhancing the quality of innovation products, and facilitating the transformation of scientific achievements.

Originality/value

Compared to previous studies, this study emulates the real conditions of IURC. Thus, the rule of technological innovation can be better revealed, the potential partners of IURC can be identified more readily, and the conclusion has more value.

Open access

Chaocheng He, Panhao Ma, Lusha Zhou and Jiang Wu

Abstract

Purpose

Compared with traditional course materials used in the classroom, the massive open online course (MOOC) forum that delivers unlimited learning content to students has various advantages. Yet MOOC has also received criticism recently, notably the problem of extremely low participation rates in its discussion forums. This study aims to explore the correlation between forum activity and student course grade in MOOC, and identify more accurately the forum activity levels of participants and the quality of threads in MOOC.

Design/Methodology/Approach

We crawled students’ tests, final exams, exercises, discussions performance data and total scores from a course in Chinese College MOOC from May 2014 to August 2014. And we use the data to analyze the correlation between Forum Participation and Course Performance based on nonparametric tests as well as multiple linear regressions with the software of R. The study provides definitions and algorithms of super degrees based on the supernetwork model to help find high-quality threads and active participants.

Findings

A positive correlation between forum activity and course grade is found in this study. Students who participate in the forum have better performance than those who do not. Using the definitions and algorithms of super degrees in the supernetwork, forum activity levels of participants as well as the quality of threads they employ are identified.

Research limitation

Only limited representative forum participants and threads are used to analyze the activity level and significance of the MOOC forum. Also, the study only investigates one Chinese course on information retrieval. More data and more data sources could be helpful in better understanding the MOOC forum phenomenon.

Practical implications

As super degrees can reveal more latent information and recognize high-quality threads as well as active participants, these parameters can be used to assess needs to improve forum settings and alleviate the problem of low forum participation. The proposed super degrees can be applied in social network domains for further research.

Originality/Value

Definitions and algorithms of super degrees are provided and used for forum analysis. Super degrees can be applied to find high-quality threads and active participants, which is beneficial to guide students to participate in these high-quality threads and have a better understanding of knowledge MOOC provides.

Open access

Xinyue Yang and Qinjian Yuan

Abstract

Purpose

This research attempts to examine the relationship between B2C interaction and customer loyalty in Business-to-Customer (B2C) context from a new perspective of the interactive tool.

Design/methodology/approach

The scale for B2C interactive tools is of seven dimensions: efficiency, security, fulfillment, mobility, community, cultivation, and customization. A model reflecting the influences of these attributes on customer loyalty is developed and empirically examined based on data collected from 265 B2C customers.

Findings

Results reveal that the fulfillment, mobility, community, and customization of B2C interactive tools can enhance customer loyalty directly and significantly. Efficiency and security, serving as the premise for possible purchase behavior, facilitate fulfillment. In addition, cultivation promotes the formation of customization, which directly strengthens customer loyalty.

Research limitations

Models considering individual-level indicators and combined with classic loyalty mechanisms in B2C context may lead to a deeper understanding of the tested effects of interaction on customer loyalty.

Practical implications

To strengthen B2C interaction and further cultivate loyal customers, making interactive tools more fundamental, flexible, and personalized is critical for B2C enterprises.

Originality/value

This study proposes a new perspective from interactive tools when measuring the relationship between B2C interaction and customer loyalty, and offers a useful theoretical lens and reasonable explanations for investigating customer loyalty in B2C e-commerce context.

Open access

Jie Wang, Chengzhi Zhang, Mengying Zhang and Sanhong Deng

Abstract

Purpose

This study aims to build an automatic survey generation tool, named CitationAS, based on citation content as represented by the set of citing sentences in the original articles.

Design/methodology/approach

Firstly, we apply LDA to analyse topic distribution of citation content. Secondly, in CitationAS, we use bisecting K-means, Lingo and STC to cluster retrieved citation content. Then Word2Vec, WordNet and combination of them are applied to generate cluster labels. Next, we employ TF-IDF, MMR, as well as considering sentence location information, to extract important sentences, which are used to generate surveys. Finally, we adopt manual evaluation for the generated surveys.

Findings

In experiments, we choose 20 high-frequency phrases as search terms. Results show that Lingo-Word2Vec, STC-WordNet and bisecting K-means-Word2Vec have better clustering effects. In 5 points evaluation system, survey quality scores obtained by designing methods are close to 3, indicating surveys are within acceptable limits. When considering sentence location information, survey quality will be improved. Combination of Lingo, Word2Vec, TF-IDF or MMR can acquire higher survey quality.

Research limitations

The manual evaluation method may have a certain subjectivity. We use a simple linear function to combine Word2Vec and WordNet that may not bring out their strengths. The generated surveys may not contain some newly created knowledge of some articles which may concentrate on sentences with no citing.

Practical implications

CitationAS tool can automatically generate a comprehensive, detailed and accurate survey according to user’s search terms. It can also help researchers learn about research status in a certain field.

Originality/value

CitaitonAS tool is of practicability. It merges cluster labels from semantic level to improve clustering results. The tool also considers sentence location information when calculating sentence score by TF-IDF and MMR.

Open access

Irwin Reyes, Primal Wijesekera, Joel Reardon, Amit Elazari Bar On, Abbas Razaghpanah, Narseo Vallina-Rodriguez and Serge Egelman

Abstract

We present a scalable dynamic analysis framework that allows for the automatic evaluation of the privacy behaviors of Android apps. We use our system to analyze mobile apps’ compliance with the Children’s Online Privacy Protection Act (COPPA), one of the few stringent privacy laws in the U.S. Based on our automated analysis of 5,855 of the most popular free children’s apps, we found that a majority are potentially in violation of COPPA, mainly due to their use of thirdparty SDKs. While many of these SDKs offer configuration options to respect COPPA by disabling tracking and behavioral advertising, our data suggest that a majority of apps either do not make use of these options or incorrectly propagate them across mediation SDKs. Worse, we observed that 19% of children’s apps collect identifiers or other personally identifiable information (PII) via SDKs whose terms of service outright prohibit their use in child-directed apps. Finally, we show that efforts by Google to limit tracking through the use of a resettable advertising ID have had little success: of the 3,454 apps that share the resettable ID with advertisers, 66% transmit other, non-resettable, persistent identifiers as well, negating any intended privacy-preserving properties of the advertising ID.

Open access

Reem Abdalla and Alok Mishra

Abstract

This paper carries out a comparative analysis to determine the advantages and the stages of two agent-based methodologies: Multi-agent Systems Engineering (MaSE) methodology, which is designed specifically for an agent-based and complete lifecycle approach, while also being appropriate for understanding and developing complex open systems; Agent Systems Methodology (ASEME) suggests a modular Multi-Agent System (MAS) development approach and uses the concept of intra-agent control. We also examine the strengths and weaknesses of these methodologies and the dependencies between their models and their processes. Both methodologies are applied to develop The Guardian Angle: Patient-Centered Health Information System (GA: PCHIS), which is an example of agent-based applications used to improve health care information systems.

Open access

Matthew Smith, Daniel Moser, Martin Strohmeier, Vincent Lenders and Ivan Martinovic

Abstract

Despite the Aircraft Communications, Addressing and Reporting System (ACARS) being widely deployed for over twenty years, little scrutiny has been applied to it outside of the aviation community. Whilst originally utilized by commercial airlines to track their flights and provide automated timekeeping on crew, today it serves as a multi-purpose air-ground data link for many aviation stakeholders including private jet owners, state actors and military. Such a change has caused ACARS to be used far beyond its original mandate; to date no work has been undertaken to assess the extent of this especially with regard to privacy and the various stakeholder groups which use it. In this paper, we present an analysis of ACARS usage by privacy sensitive actors-military, government and business. We conduct this using data from the VHF (both traditional ACARS, and VDL mode 2) and satellite communications subnetworks. Based on more than two million ACARS messages collected over the course of 16 months, we demonstrate that current ACARS usage systematically breaches location privacy for all examined aviation stakeholder groups, explaining the types of messages used to cause this problem.We illustrate the challenges with three case studies-one for each stakeholder group-to show how much privacy sensitive information can be constructed with a handful of ACARS messages. We contextualize our findings with opinions on the issue of privacy in ACARS from 40 aviation industry professionals. From this, we explore recommendations for how to address these issues, including use of encryption and policy measures.

Open access

Takao Murakami, Hideitsu Hino and Jun Sakuma

Abstract

A number of studies have recently been made on discrete distribution estimation in the local model, in which users obfuscate their personal data (e.g., location, response in a survey) by themselves and a data collector estimates a distribution of the original personal data from the obfuscated data. Unlike the centralized model, in which a trusted database administrator can access all users’ personal data, the local model does not suffer from the risk of data leakage. A representative privacy metric in this model is LDP (Local Differential Privacy), which controls the amount of information leakage by a parameter ∈ called privacy budget. When ∈ is small, a large amount of noise is added to the personal data, and therefore users’ privacy is strongly protected. However, when the number of users ℕ is small (e.g., a small-scale enterprise may not be able to collect large samples) or when most users adopt a small value of ∈, the estimation of the distribution becomes a very challenging task. The goal of this paper is to accurately estimate the distribution in the cases explained above. To achieve this goal, we focus on the EM (Expectation-Maximization) reconstruction method, which is a state-of-the-art statistical inference method, and propose a method to correct its estimation error (i.e., difference between the estimate and the true value) using the theory of Rilstone et al. We prove that the proposed method reduces the MSE (Mean Square Error) under some assumptions.We also evaluate the proposed method using three largescale datasets, two of which contain location data while the other contains census data. The results show that the proposed method significantly outperforms the EM reconstruction method in all of the datasets when ℕ or ∈ is small.