Towards a research agenda for promoting responsible research practices

This opinion piece aims to inform future research funding programs on responsible research practices (RRP) based on three specific objectives: (1) to give a sketch of the current international discussion on responsible research practices (RRPs); (2) to give an overview of current initiatives and already obtained results regarding RRP; and (3) to give an overview of potential future needs for research on RRP. In this opinion piece, we have used seven iterative methodological steps (including literature review, ranking, and sorting exercises) to create the proposed research agenda. We identified six main themes that we believe need attention in future research: (1) responsible evaluation of research and researchers, (2) the influence of open science and transparency on RRP, (3) research on responsible mentoring, supervision, and role modeling, (4) the effect of education and training on RRP, (5) checking for reproducibility, and (6) responsible and fair peer review. These themes have in common that they address aspects of research that are mostly on the level of the scientific system, more than on the level of the individual researcher. Some current initiatives are already gathering substantial empirical evidence to start filling these gaps. We believe that with sufficient support from all relevant stakeholders, more progress can be made

Network-based ranking in social systems: three challenges

Ranking algorithms are pervasive in our increasingly digitized societies, with important real-world applications including recommender systems, search engines, and influencer marketing practices. From a network science perspective, network-based ranking algorithms solve fundamental problems related to the identification of vital nodes for the stability and dynamics of a complex system. Despite the ubiquitous and successful applications of these algorithms, we argue that our understanding of their performance and their applications to real-world problems face three fundamental challenges: (i) Rankings might be biased by various factors; (2) their effectiveness might be limited to specific problems; and (3) agents' decisions driven by rankings might result in potentially vicious feedback mechanisms and unhealthy systemic consequences. Methods rooted in network science and agent-based modeling can help us to understand and overcome these challenges.Comment: Perspective article. 9 pages, 3 figure

The Open Research Web: A Preview of the Optimal and the Inevitable

The multiple online research impact metrics we are developing will allow the rich new database , the Research Web, to be navigated, analyzed, mined and evaluated in powerful new ways that were not even conceivable in the paper era – nor even in the online era, until the database and the tools became openly accessible for online use by all: by researchers, research institutions, research funders, teachers, students, and even by the general public that funds the research and for whose benefit it is being conducted: Which research is being used most? By whom? Which research is growing most quickly? In what direction? under whose influence? Which research is showing immediate short-term usefulness, which shows delayed, longer term usefulness, and which has sustained long-lasting impact? Which research and researchers are the most authoritative? Whose research is most using this authoritative research, and whose research is the authoritative research using? Which are the best pointers (“hubs”) to the authoritative research? Is there any way to predict what research will have later citation impact (based on its earlier download impact), so junior researchers can be given resources before their work has had a chance to make itself felt through citations? Can research trends and directions be predicted from the online database? Can text content be used to find and compare related research, for influence, overlap, direction? Can a layman, unfamiliar with the specialized content of a field, be guided to the most relevant and important work? These are just a sample of the new online-age questions that the Open Research Web will begin to answer

Temporal effects in trend prediction: identifying the most popular nodes in the future

Prediction is an important problem in different science domains. In this paper, we focus on trend prediction in complex networks, i.e. to identify the most popular nodes in the future. Due to the preferential attachment mechanism in real systems, nodes' recent degree and cumulative degree have been successfully applied to design trend prediction methods. Here we took into account more detailed information about the network evolution and proposed a temporal-based predictor (TBP). The TBP predicts the future trend by the node strength in the weighted network with the link weight equal to its exponential aging. Three data sets with time information are used to test the performance of the new method. We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future. The effect of the decay speed in the exponential aging on the results is discussed in detail

Utilising content marketing metrics and social networks for academic visibility

There are numerous assumptions on research evaluation in terms of quality and relevance of academic contributions. Researchers are becoming increasingly acquainted with bibliometric indicators, including; citation analysis, impact factor, h-index, webometrics and academic social networking sites. In this light, this chapter presents a review of these concepts as it considers relevant theoretical underpinnings that are related to the content marketing of scholars. Therefore, this contribution critically evaluates previous papers that revolve on the subject of academic reputation as it deliberates on the individual researchers’ personal branding. It also explains how metrics are currently being used to rank the academic standing of journals as well as higher educational institutions. In a nutshell, this chapter implies that the scholarly impact depends on a number of factors including accessibility of publications, peer review of academic work as well as social networking among scholars.peer-reviewe

Applied Evaluative Informetrics: Part 1

This manuscript is a preprint version of Part 1 (General Introduction and Synopsis) of the book Applied Evaluative Informetrics, to be published by Springer in the summer of 2017. This book presents an introduction to the field of applied evaluative informetrics, and is written for interested scholars and students from all domains of science and scholarship. It sketches the field's history, recent achievements, and its potential and limits. It explains the notion of multi-dimensional research performance, and discusses the pros and cons of 28 citation-, patent-, reputation- and altmetrics-based indicators. In addition, it presents quantitative research assessment as an evaluation science, and focuses on the role of extra-informetric factors in the development of indicators, and on the policy context of their application. It also discusses the way forward, both for users and for developers of informetric tools.Comment: The posted version is a preprint (author copy) of Part 1 (General Introduction and Synopsis) of a book entitled Applied Evaluative Bibliometrics, to be published by Springer in the summer of 201

Diffusion of social cognitive theory in information systems research: A bibliometric study

Recently, Social Cognitive theory (SCT) has been widely adapted across various disciplines in business and management as well as Information Systems (IS) research. In IS, the use of SCT remains in its early stages. Few bibliometric analyses have been published on mapping theories across previous literature. However, to date factors related to literature review mapping in relation to SCT in IS have not been much examined. This paper aims to investigate the expliotiation of SCT in IS research based on bibliometric analysis. In this study a biblimetric analysis is conducted on previous literature reviews/abstracts based on Association of Business Schools (ABS) journal rankings from Information Management field perspective. 62 articles in Information Management field have utilised SCT were published in 17 (out of 53 journals) between 1995 and 2010. The study findings has identified that the organisation/firm and actors as a unit of analysis, positivist paradigm, empirical and quantitative research as well as survey method were used significantly in combination with SCT in IS studies. This bibliometric study will provide the needed platform for a better understanding of high quality research activities. Consequently, this can be used as an indicator to measure research quality and the impact of future direction and exploitation of SCT in IS research