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Despite the general usefulness of citations as a sort of test of the value of one’s work in the marketplace of ideas, journals and publishers tend to use alternative bases of judgment, namely committees, in selecting candidates for the conferral of journals’ best paper awards. Given that recognition—sometimes in the form of compensation and on other occasions in the form of awards—in academe is geared toward incentivizing the production of impactful research and not some less desirable goal or outcome, it is important to understand the sensitivity in the outcomes of best paper award selection processes to the types of processes used. To that end, this study compares the selection of best paper awards for journals affiliated with several of the world’s top economic associations by committees to a counterfactual process that is based on citations to published studies. Our statistical exploration indicates that in most cases and for most awards, the most cited paper was not chosen. This requires further discussion as to the core characteristics that quantitatively represent the highest impact.

The article illustrates the AIFIRM Position Paper 22 “Covid-19 and banking governance” published on the AIFIRM website (www.aifirm.it). The Position Paper contains an extensive executive summary in english.

Published version

Publication of research papers in reputed and referred journals has become mandatory for teachers, professors and research scholars. Paper must be plagiarism free and scholarly written with scientific validity and reasonable conclusion. Most of the researchers does not differentiate among research paper, article and essay. Researchers are not aware what they are aiming at. The present paper guides researchers about writing a scholarly research paper. There is a specified stepwise procedure of writing scholarly research paper. All researchers must follow that pattern. It is a 7-point strategy. The steps suggested by the author are sole experience of the author. Author is chief editor of Journal of Commerce and Trade.

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Draft paper - ADVANCE 2018

Many papers in economics that are published in peer reviewed journals are initially released in widely circulated working paper series. This raises the question about the benefit of publishing in a peer-reviewed journal in terms of citations. Specifically, we address the question: To what extent does the stamp of approval obtained by publishing in a peer-reviewed journal lead to more subsequent citations for papers that are already available in working paper series? Our data set comprises about 28.000 working papers from four major working paper series in economics. Using panel data methods, we show that the publication in a peer reviewed journal results in around twice the number of yearly citations relative to working papers that never get published in a journal. Our results hold in several robustness checks.

One way of exposing predatory journals is to submit a spoof article to see if it gets accepted. We investigate one journal, looking at how it has performed since a spoof paper it accepted came to light. We find that it has published almost 20% more papers following the acceptance of the spoof paper. The journal has a new web site, which appears to show that it did not publish its first paper until 2018. However, there is an old web site that lists 321 papers dating back to 2012. The editors said that this is due to a new workflow system, which meant that previously published papers could not be listed on the new web site. Moreover, the number of papers could be not accommodated, as a high configuration server would be required to provide a responsive web site. We found some plagiarism, which looks quite serious. We conclude that the spoof paper had little effect on the journal, which continues to operate, seven years after the spoof paper was accepted.

In the era of globalization today, Green technology acceptance has become a crucial sector not just for the environment, but also for humans and towards the economy. In this paper, the researcher will do the overview of Green Technology Acceptance as overall, means in many areas such as green transportation, green chemistry, green buildings, green procurements and few more. So, for this purpose the researcher choose to use the Scopus database to review on the past published studies on green technology fields. For this purpose, the Qualitative review has been done by the systematic review through the PRISMA Framework (Preferred Reporting Items for Systematic Review and Meta-Analysis). There are around 46 papers that had been selected in finals for this systematic literature review analysis. After follow the PRISMA Model to filter out the paper that suitable for this study, researcher is using the Microsoft Excels to do the descriptive analysis on year base publication, journal base, most cited by, theory utilised and subject areas. Besides that, researcher also focus on the methodology classification that had been use in the past studies. There are three main classifications which is Quantitative, Qualitative and Mixed Methods. There are around 26 paper used quantitative analysis method, 17 papers utilised qualitative method and 3 papers using mixed method. Mostly all this past study not including the latest branches of Green Technology such as green economies, green building and many more. As overall, researcher successfully using the PRISMA model to identified the suitable paper that being used in this papers.

In China, master's students in humanities and social sciences (HSS) are becoming the main target of Chinese-language predatory journals. Existing research has not paid enough attention to why these students publish papers in Chinese-language predatory journals. This research interviewed 30 HSS master's students with different majors using semi-structured interviews and Grounded Theory to analyze the data; it found that research discrimination, research context, self-awareness, and individual demand are the main reasons why students publish papers in Chinese-language predatory journals. This study provides the following suggestions in an effort to solve the problem of Chinese-language predatory journals. First, the Chinese government should draw up a blacklist of Chinese-language predatory journals. Second, the research evaluation departments of Chinese universities and research institutions should evaluate the research results of HSS master's students based on this list. Third, Chinese universities or scientific research institutions should strengthen the training of HSS master tutors and increase their awareness of Chinese-language predatory journals. And finally, Chinese HSS master's students should be taught about the hazards of Chinese-language predatory journals in research integrity and ethics courses, and refuse to publish papers in Chinese-language predatory journals.

This project contains the citations found in Google Scholar, Web of Science, and Scopus, to the sample of 2,515 highly-cited documents displayed in the 2017 edition of Google Scholar's Classic Papers. Additionally, it contains the tables resulting from the analysis carried out in the paper "Google Scholar, Web of Science, and Scopus: a systematic comparison of citations in 252 subject categories"

This project includes data from the three studies reported in my paper on Foundational Tests of the Need-Support Model, as well as the paper and methodology file accepted for publication in Personality and Social Psychology Bulletin on November 14, 2016.

The increasing presence of e-books (electronic books) has become a major focus in countries around the world. In the United States, e-books represented 28% of the total book sales for 2012. In Japan, the conversion from paper books to e-books is expected to accelerate by the prevalent use of smartphones and tablet PCs. It is therefore important to quantitatively evaluate the environmental load of paper books and e-books for a sustainable society. In this study, paper books are compared to e-books read on different electronic devices (e-ink tablets, tablets, cell phones, smartphones, laptop computers, desktop computers and portable music players) through a case study on a 224-page book. The study is based on key primary data such as use time and reading speed for each device and aims to minimize assumptions made in other studies. GHG emissions for paper books are 1.24 kg-CO2e/book, and are reduced to 1.11 kg-CO2e/book when the effect of paper recycling is taken into consideration. The results for e-books under average use-time conditions range from 0.25 to 0.91 kg-CO2e/book with the e-ink tablet having the lowest emissions. When the average use time of each e-book device is applied, the paper book has a higher impact than all the e-books. However, sensitivity analysis shows that the impact of paper books can be lower than that of e-books for larger screen devices such as tablets, laptops and desktops when the reuse of books is considered or the e-book reading device is hardly used during its life cycle.

This study investigates a potential relationship between highly-cited scholarly papers and the number of citations received by other papers with which they share a journal issue. Citations received by 3675 articles across 484 issues published in three top information science journals are analyzed based on the condition of whether an article was published in an issue that includes a “highly-cited” paper (two standard deviations above mean number by year). The findings indicate a statistically significant effect of highly-cited papers and citations to other papers in the same journal issue. This finding is relevant to authors and publishers when considering the structure of publications with an “issue” format.

Predicting the impact of academic papers can help scholars quickly identify the high-quality papers in the field. How to develop efficient predictive model for evaluating potential papers has attracted increasing attention in academia. Many studies have shown that early citations contribute to improving the performance of predicting the long-term impact of a paper. Besides early citations, some bibliometric features and altmetric features have also been explored for predicting the impact of academic papers. Furthermore, paper metadata text such as title, abstract and keyword contains valuable information which has effect on its citation count. However, present studies ignore the semantic information contained in the metadata text. In this paper, we propose a novel citation prediction model based on paper metadata text to predict the long-term citation count, and the core of our model is to obtain the semantic information from the metadata text. We use deep learning techniques to encode the metadata text, and then further extract high-level semantic features for learning the citation prediction task. We also integrate early citations for improving the prediction performance of the model. We show that our proposed model outperforms the state-of-the-art models in predicting the long-term citation count of the papers, and metadata semantic features are effective for improving the accuracy of the citation prediction models.

Bibliometrics is a statistical analysis of written publications such as books or articles. A bibliographic citationis a reference to a book, article, web page, or other published item. Thus citations are useful for identifying the progress ofthe particular work and measuring the quality of the research article. The cited papers are downloaded using the crawler. Fromthe downloaded article, identify article relation by analyzing the citation context of the article. So first extract the citation context from the article. Citation context are classifies based on cue phrases of Simon tufel. Next, identify the relation of unlabeled article by word embedding. After labeling all articles identifythe perspective behind the citation of the article. In this project, citation relation is identified based on cue phrases of Simon tufel finally article impact is quantified based on the citation network formed from citation analysis. Index Terms: bibliometrics, citation, word embedding, article

This is the dataset used in our HICSS 2021 paper titled "How Can I Share My Work? A Review of the Open Access Policies of IS Journals". It consists of 20 information systems (IS) journals, and their policies for practicing open access when publishing in their journals.

Data archive for frequently cited papers

Many papers in economics that are published in peer reviewed journals are initially released in widely circulated working paper series. This raises the question about the benefit of publishing in a peer-reviewed journal in terms of citations. Specifically, we address the question: to what extent does the stamp of approval obtained by publishing in a peer-reviewed journal lead to more subsequent citations for papers that are already available in working paper series? Our data set comprises about 28,000 working papers from four major working paper series in economics. Using panel data methods, we show that the publication in a peer reviewed journal results in around twice the number of yearly citations relative to working papers that never get published in a journal. Our results hold in several robustness checks.

Citation prediction of scholarly papers is of great significance in guiding funding allocations, recruitment decisions, and rewards. However, little is known about how citation patterns evolve over time. By exploring the inherent involution property in scholarly paper citation, we introduce the Paper Potential Index (PPI) model based on four factors: inherent quality of scholarly paper, scholarly paper impact decaying over time, early citations, and early citers' impact. In addition, by analyzing factors that drive citation growth, we propose a multi-feature model for impact prediction. Experimental results demonstrate that the two models improve the accuracy in predicting scholarly paper citations. Compared to the multi-feature model, the PPI model yields superior predictive performance in terms of range-normalized RMSE. The PPI model better interprets the changes in citation, without the need to adjust parameters. Compared to the PPI model, the multi-feature model performs better prediction in terms of Mean Absolute Percentage Error and Accuracy; however, their predictive performance is more dependent on the parameter adjustment Refereed/Peer-reviewed

The 2021 Feature Papers Special Issue is a list of high-quality research output that shows the width and the breadth of the journal Risks [...]

In recent years, some scholarly journals have indicated that they accept rewritten or extended version of a conference paper as long as new content are added to the journal article manuscript and that the original conference paper is included in the references. The extended publishing of conference papers now becomes topic worthy of investigation. This study analyzed the extended works of the conference papers from three major conferences in the fields of information management, i.e., Association for Computing Machinery (ACM)’s ACM Conference on Electronic Commerce (ACM EC), ACM Conference on Knowledge Discovery and Data Mining (ACM KDD), and ACM International Conference on Information and Knowledge Management (ACM CIKM). Papers from the 2011 meetings were used as the sample to understand to what extent conference papers have been extended into journal articles and other forms and the lag between conference and journal publishing. It also examined the differences between the conference papers and their extended versions (i.e., journal papers) by comparing the changes in authorship, references, article length, tables, and figures. It reveals the current practices of extending conference papers for journal publishing in the information management fields and may help us understand the contemporary scholarly publishing behavior. (Article content in Chinese with English extended abstract)

Citations are often used as a metric of the impact of scientific publications. Here, we examine how the number of downloads from Sci-Hub as well as various characteristics of publications and their authors predicts future citations. Using data from 12 leading journals in economics, consumer research, neuroscience, and multidisciplinary research, we found that articles downloaded from Sci-Hub were cited 1.72 times more than papers not downloaded from Sci-Hub and that the number of downloads from Sci-Hub was a robust predictor of future citations. Among other characteristics of publications, the number of figures in a manuscript consistently predicts its future citations. The results suggest that limited access to publications may limit some scientific research from achieving its full impact. Refereed/Peer-reviewed

International audience; This paper addresses the problem of building recommender systems for scientific papers based on the linguistic and contextual analysis of citation contexts. We explain the importance of taking into consideration citation contexts and the different methodologies that exist as well as the ways that citations impact recommender systems. We also discuss the limits of using citation contexts to generate recommendations.

Does it pay off in terms of citations to issue an article as a working paper before it is published in a refereed journal? We show empirically that the answer is yes, using 3167 articles published ...

Do you have useful datasets and methods? Consider publishing them as “mini-papers” prior to formal publication in a journal.

This extended abstract summarizes our paper with the same title published at the main track of the International Conference of Software Engineering (ICSE) 2021.

This is a summary of a paper (with the same title) that we published at the ACM/IEEE 24th International Conference on Model-Driven Engineering Languages and Systems (MODELS 2021) describing a study centered on a visual programming IDE for large-scale automation software development and maintenance.

Purpose To uncover the evaluation information on the academic contribution of research papers cited by peers based on the content cited by citing papers, and to provide an evidence-based tool for evaluating the academic value of cited papers. Design/methodology/approach CiteOpinion uses a deep learning model to automatically extract citing sentences from representative citing papers; it starts with an analysis on the citing sentences, then it identifies major academic contribution points of the cited paper, positive/negative evaluations from citing authors and the changes in the subjects of subsequent citing authors by means of Recognizing Categories of Moves (problems, methods, conclusions, etc.), and sentiment analysis and topic clustering. Findings Citing sentences in a citing paper contain substantial evidences useful for academic evaluation. They can also be used to objectively and authentically reveal the nature and degree of contribution of the cited paper reflected by citation, beyond simple citation statistics. Practical implications The evidence-based evaluation tool CiteOpinion can provide an objective and in-depth academic value evaluation basis for the representative papers of scientific researchers, research teams, and institutions. Originality/value No other similar practical tool is found in papers retrieved. Research limitations There are difficulties in acquiring full text of citing papers. There is a need to refine the calculation based on the sentiment scores of citing sentences. Currently, the tool is only used for academic contribution evaluation, while its value in policy studies, technical application, and promotion of science is not yet tested.

Purpose As researchers are writing a draft paper with incomplete structure or text, one of burdensome tasks is to deliberate about which references should be cited for one sentence or paragraph of this draft. In view of the rapid increase in the number of research papers, researchers desire to figure out a better way to do citation recommendations in developing their draft papers. The purpose of this paper is to propose citation recommendation algorithms that enable the acquisition of relevant citations for research papers that are still at the drafting stage. This study attempts to help researchers to select appropriate references among the vast amount of available papers and make draft papers complete in reference citation. Design/methodology/approach This study adopts a model for recommending citations for incomplete drafts. Four algorithms are proposed in this study. The first and second algorithms are unsupervised models, applying term frequency-inverse document frequency and WordNet technologies, respectively. The third and fourth algorithms are based on the second algorithm to integrate different weight adjustment strategies to improve performance. Findings The proposed recommendation method adopts three techniques, including using WordNet to transform vector and setting adjustment weights according to structural factors and the information completeness degree, to generate citation recommendation for incomplete drafts. The experiments show that all these three techniques can significantly improve the recommendation accuracy. Originality/value None of the methods employed in previous studies can recommend articles as references for incomplete drafts. This paper addresses the situation that a draft paper can be incomplete either in structure or text or both. Recommended references, however, can be still generated and inserted into any desired sentence of the draft paper.

The present research reveals that academic papers published at year-end on average receive systematically fewer citations than papers published at other times in the year. Using more than 200,000 papers in economics published between 1956 and 2010, the results of our analysis show that papers published between October and December on average get as much as 18.5% fewer citations than those published in the other months in the year. We refer to this phenomenon as the citation trap as there is no evidence that papers published at different times in the year differ in their academic quality. We propose that the current effect could arise because of the time window options in most online academic search engines: the specific setting of those options leads papers published at year-end to appear in the engines’ search results for a systematically shorter period of time as compared to papers published at other months in the year. Our analysis reveals evidence that is consistent with the proposed mechanism and that rules out several alternative explanations. Implications of the current research for academia and possible solutions to mitigate the citation trap are discussed.

We explore a dual score system that simultaneously evaluates the relative importance of authors and their papers from a given author-paper-citation heterogeneous network. An observed, or actual citation score for each paper is known at the paper–paper citation matrix level. From an author score obtained from an author–author citation matrix, it is possible to derive separately, an expected score for each paper. The ratio of observed to expected scores is an author based relative paper score for each paper. If the aggregation is journal based, then based on journal scores, one can derive in the same manner, expected, observed and relative paper citation scores. It follows that field based aggregation will lead to a similar family of field based paper scores.

A couple of years ago my colleague (and former PhD student) Jan Anne Annema told me that he checked why people cited our paper on experiences with the use of Cost–Benefit Analysis (CBA) in the Neth...

Special Feature that lists the names of people involved in the review of technical papers for the IEEE Transactions on Industry Applications and Industry Applications Magazine.

Context: According to the search reported in this paper, as of this writing (May 2015), a very large number of papers (more than 70,000) have been published in the area of Software Engineering (SE) since its inception in 1968. Citations are crucial in any research area to position the work and to build on the work of others. Identification and characterization of highly-cited papers are common and are regularly reported in various disciplines. Objective: The objective of this study is to identify the papers in the area of SE that have influenced others the most as measured by citation count. Studying highly-cited SE papers helps researchers to see the type of approaches and research methods presented and applied in such papers, so as to be able to learn from them to write higher quality papers which will likely receive high citations. Method: To achieve the above objective, we conducted a study, comprised of five research questions, to identify and classify the top-100 highly-cited SE papers in terms of two metrics: total number of citations and average annual number of citations. Results: By total number of citations, the top paper is "A metrics suite for object-oriented design", cited 1,817 times and published in 1994. By average annual number of citations, the top paper is "QoS-aware middleware for Web services composition", cited 154.2 times on average annually and published in 2004. Conclusion: It is concluded that it is important to identify the highly-cited SE papers and also to characterize the overall citation landscape in the SE field. We hope that this paper will encourage further discussions in the SE community towards further analysis and formal characterization of the highly-cited SE papers., Vahid Garousi was partially supported by several internal grants provided by the Hacettepe University. The authors would like to thank the anonymous reviewers for their insightful comments.

This special issue of the Kiva is published in honor of Margaret Lyneis, who passed away in 2016 at the age of 78, after a long and influential career as a teacher and scholar. These papers develop...

Bibliography is important in a research paper because you give credit where credit is due. This is where you give your readers your sources for your citations used in your paper whether it is in health, marketing or history. The purpose of a bibliography is to lead your readers to your list of sources and you will help your readers in finding them too.Use the help of our master thesis writing service and get educated! If you have used the mla format throughout your paper, you should also use mla bibliography format for your bibliography. Never use different formats per paper. So the mla bibliography format is basically all the authors used in your paper. They should be enumerated alphabetically by last name and this should begin on a separate sheet of paper at the end of your paper. The first line of your bibliography is flushed with the left margin and the next lines indented about half an inch. Double spaces should be used for the entire list wit no extra spaces in between the entries. There will always be sources that are relevant to your paper but you did not have the chance to use them. So you can also include them in your bibliography as cited in the mla bibliography format. In the bibliography portion, you can include these sources at the works consulted list following the works cited list and present their information in the same way.Read about how to write an abstract for an economics paper on our blog! Although you have to note that there is a different mla bibliography format for electronic documents. Some say it can be tricky at times. But once you have a template based on the mla bibliography format, you will not lose your way. The reason why some find it so tricky is because online sources change often and it is updated frequently. So there can be a time when you lose your source because it has already been updated. So what you can do is, you can include the title of the site where you found it, date of electronic publication or the latest update, name of the institution that has sponsored the site. The dates of publication for electronic document should be listed down with the day of the month first, followed by the month and then the year. You should take note to never put a period between the date of access and the web address. In any bibliography, whether electronic or otherwise, you should always put as much information as possible. If there is missing information, move on to the next information. So if there is no author name given, alphabetize the work using the first word of the title. Useful resources: Best Essay Writing Service: Reddit Enumeration EGR Speaking Club

The formulation of good academic paper titles in English is challenging for intermediate English authors (particularly students). This is because such authors are not aware of the type of titles that are generally in use. We aim to realize a support system for formulating more effective English titles for intermediate English and beginner authors. This study develops an extractive title generation system that formulates titles from keywords extracted from an abstract. Moreover, we realize a title evaluation model that can evaluate the appropriateness of paper titles. We train the model with titles of top-conference papers by using BERT. This paper describes the training data, implementation, and experimental results. The results show that our evaluation model can identify top-conference titles more effectively than intermediate English and beginner students., 6 pages, 3 figures, 4 tables, 2 algorithms

The documentcontains the supplementary materials for the paper "AntiCopyPaster: Extracting Code Duplicates As Soon As They Are Introduced in the IDE": the full list of the used metrics, the full list of the used projects, along with the list of the used models

The Editors-in-Chief of the Environmental Science journals introduce the Best Papers of 2020.

Publishing an informative, useful, and attractive journal has been a difficult task throughout the history of scientific communications. Print publishing has had its own hardships that kept editors and publishers busy with time-consuming technological processes, requiring specific skills and abundant financial investments. With the advent of digital media and Open Access, scholarly activities and knowledge transfer have accelerated and facilitated globally affordable online publishing practices.

From the past half of a century, identification of the relevant documents is deemed an active area of research due to the rapid increase of data on the web. The traditional models to retrieve relevant documents are based on bibliographic information such as Bibliographic coupling, Co-citations, and Direct citations. However, in the recent past, the scientific community has started to employ textual features to improve existing models’ accuracy. In our previous study, we found that analysis of citations at a deep level (i.e., content level) can play a paramount role in finding more relevant documents than surface level (i.e., just bibliography details). We found that cited and citing papers have a high degree of relevancy when in-text citations frequency of the cited paper is more than five times in the citing paper’s text. This paper is an extension of our previous study in terms of its evaluation of a comprehensive dataset. Moreover, the study results are also compared with other state-of-the-art approaches i.e., content, metadata, and bibliography. For evaluation, a user study is conducted on selected papers from 1,200 documents (comprise about 16,000 references) of an online journal, Journal of Computer Science (J.UCS). The evaluation results indicate that in-text citation frequency has attained higher precision in finding relevant papers than other state-of-the-art techniques such as content, bibliographic coupling, and metadata-based techniques. The use of in-text citation may help in enhancing the quality of existing information systems and digital libraries. Further, more sophisticated measure may be redefined be considering the use of in-text citations.

Plants is instituting the Best Paper Awards to recognize the outstanding papers published in the journal [...]

Buildings is introducing the Best Paper Award to recognize outstanding papers published in the journal [...]

Buildings is instituting the Best Paper Award to recognize outstanding papers published in the journal [...]

The paper resources of university libraries are increasing every year, and the collection space is obviously insufficient. In this paper, by analyzing the half-life of literature citation and the half-life of literature citation of various books, the XGBoost algorithm is used to analyze the evaluation system of book publication year, book category, reader activity, author popularity, book price, publisher popularity, and country popularity as indicators .Besides, it combined with the multi-attribute decision-making model and the improved RFM model-BRFM model, established a book-reader association model, and formulated a set of book removal standards.

This package includes interview questionnaire, focus groups questionnaire, and member checking summary used in this paper submitted to TSE.

Purpose The purpose of this paper is to investigate open access practices (OAPs): a roadmap to research paper publications in academic institutions. The rationale that necessitates this scenario was the dwindling nature of the inability of researchers and lecturers/academics in African academic institutions to access related materials in their subject areas, while also advancing effort to publish their research papers in open access. Design/methodology/approach This paper applied a qualitative research approach, in which literature was harvested from Web of Science for developing and writing the research paper. Findings This paper establishes that OAP, when embraced, could advance and transform research paper publication in higher education institutions because its practices are globally welcome. The authors reiterate that considering the benefits accrued to OAPs, knowledge gap in terms of literature and methodological approach still exists in academic institutions in Africa; hence, the authors promote OAPs as a roadmap for research paper publications in academic institutions. It is expected that by OAPs, researchers would no longer struggle to harvest literature, of theses, dissertations and other research papers, deposited in institutional repositories required for deepening their research activities because those literature studies or those documents have to be paid for through subscription fees of published papers and publishing in open access by journals. This is what most academics have experienced because, most times, the literature which academics harvest from the internet and different institutional repositories and databases is already paid for by the different institutions that housed the literature where it is domiciled. For instance, most academic library institutions in the world pay for subscription fees of research papers and documents. This is to advance and facilitate deepened research activities in their institutions, when researchers, academics and students want to harvest materials through their university library websites. Originality/value This paper, which considers OAP as a roadmap to research paper publications in academic institutions in Africa, is insightful and unique considering the wave of OAP globally.