首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 31 毫秒
1.
Recently, two new indicators (Equalized Mean-based Normalized Proportion Cited, EMNPC; Mean-based Normalized Proportion Cited, MNPC) were proposed which are intended for sparse scientometrics data, e.g., alternative metrics (altmetrics). The indicators compare the proportion of mentioned papers (e.g. on Facebook) of a unit (e.g., a researcher or institution) with the proportion of mentioned papers in the corresponding fields and publication years (the expected values). In this study, we propose a third indicator (Mantel-Haenszel quotient, MHq) belonging to the same indicator family. The MHq is based on the MH analysis – an established method in statistics for the comparison of proportions. We test (using citations and assessments by peers, i.e. F1000Prime recommendations) if the three indicators can distinguish between different quality levels as defined on the basis of the assessments by peers. Thus, we test their convergent validity. We find that the indicator MHq is able to distinguish between the quality levels in most cases while MNPC and EMNPC are not. Since the MHq is shown in this study to be a valid indicator, we apply it to six types of zero-inflated altmetrics data and test whether different altmetrics sources are related to quality. The results for the various altmetrics demonstrate that the relationship between altmetrics (Wikipedia, Facebook, blogs, and news data) and assessments by peers is not as strong as the relationship between citations and assessments by peers. Actually, the relationship between citations and peer assessments is about two to three times stronger than the association between altmetrics and assessments by peers.  相似文献   

2.
Altmetrics have been proposed as a way to assess the societal impact of research. Although altmetrics are already in use as impact or attention metrics in different contexts, it is still not clear whether they really capture or reflect societal impact. This study is based on altmetrics, citation counts, research output and case study data from the UK Research Excellence Framework (REF), and peers’ REF assessments of research output and societal impact. We investigated the convergent validity of altmetrics by using two REF datasets: publications submitted as research output (PRO) to the REF and publications referenced in case studies (PCS). Case studies, which are intended to demonstrate societal impact, should cite the most relevant research papers. We used the MHq’ indicator for assessing impact – an indicator which has been introduced for count data with many zeros. The results of the first part of the analysis show that news media as well as mentions on Facebook, in blogs, in Wikipedia, and in policy-related documents have higher MHq’ values for PCS than for PRO. Thus, the altmetric indicators seem to have convergent validity for these data. In the second part of the analysis, altmetrics have been correlated with REF reviewers’ average scores on PCS. The negative or close to zero correlations question the convergent validity of altmetrics in that context. We suggest that they may capture a different aspect of societal impact (which can be called unknown attention) to that seen by reviewers (who are interested in the causal link between research and action in society).  相似文献   

3.
Monte Carlo simulation is a useful but underutilized method of constructing confidence intervals for indirect effects in mediation analysis. The Monte Carlo confidence interval method has several distinct advantages over rival methods. Its performance is comparable to other widely accepted methods of interval construction, it can be used when only summary data are available, it can be used in situations where rival methods (e.g., bootstrapping and distribution of the product methods) are difficult or impossible, and it is not as computer-intensive as some other methods. In this study we discuss Monte Carlo confidence intervals for indirect effects, report the results of a simulation study comparing their performance to that of competing methods, demonstrate the method in applied examples, and discuss several software options for implementation in applied settings.  相似文献   

4.
Main path analysis is a popular method for extracting the backbone of scientific evolution from a (paper) citation network. The first and core step of main path analysis, called search path counting, is to weight citation arcs by the number of scientific influence paths from old to new papers. Search path counting shows high potential in scientific impact evaluation due to its semantic similarity to the meaning of scientific impact indicator, i.e. how many papers are influenced to what extent. In addition, the algorithmic idea of search path counting also resembles many known indirect citation impact indicators. Inspired by the above observations, this paper presents the FSPC (Forward Search Path Count) framework as an alternative scientific impact indicator based on indirect citations. Two critical assumptions are made to ensure the effectiveness of FSPC. First, knowledge decay is introduced to weight scientific influence paths in decreasing order of length. Second, path capping is introduced to mimic human literature search and citing behavior. By experiments on two well-studied datasets against two carefully created gold standard sets of papers, we have demonstrated that FSPC is able to achieve surprisingly good performance in not only recognizing high-impact papers but also identifying undercited papers.  相似文献   

5.
The SNIP (source normalized impact per paper) indicator is an indicator of the citation impact of scientific journals. The indicator, introduced by Henk Moed in 2010, is included in Elsevier's Scopus database. The SNIP indicator uses a source normalized approach to correct for differences in citation practices between scientific fields. The strength of this approach is that it does not require a field classification system in which the boundaries of fields are explicitly defined.In this paper, a number of modifications that were recently made to the SNIP indicator are explained, and the advantages of the resulting revised SNIP indicator are pointed out. It is argued that the original SNIP indicator has some counterintuitive properties, and it is shown mathematically that the revised SNIP indicator does not have these properties. Empirically, the differences between the original SNIP indicator and the revised one turn out to be relatively small, although some systematic differences can be observed. Relations with other source normalized indicators proposed in the literature are discussed as well.  相似文献   

6.
Traditional pooling-based information retrieval (IR) test collections typically have \(n= 50\)–100 topics, but it is difficult for an IR researcher to say why the topic set size should really be n. The present study provides details on principled ways to determine the number of topics for a test collection to be built, based on a specific set of statistical requirements. We employ Nagata’s three sample size design techniques, which are based on the paired t test, one-way ANOVA, and confidence intervals, respectively. These topic set size design methods require topic-by-run score matrices from past test collections for the purpose of estimating the within-system population variance for a particular evaluation measure. While the previous work of Sakai incorrectly used estimates of the total variances, here we use the correct estimates of the within-system variances, which yield slightly smaller topic set sizes than those reported previously by Sakai. Moreover, this study provides a comparison across the three methods. Our conclusions nevertheless echo those of Sakai: as different evaluation measures can have vastly different within-system variances, they require substantially different topic set sizes under the same set of statistical requirements; by analysing the tradeoff between the topic set size and the pool depth for a particular evaluation measure in advance, researchers can build statistically reliable yet highly economical test collections.  相似文献   

7.
p 指数运用于人才评价的有效性实证研究   总被引：2，自引：0，他引：2  
h指数用于高发文、高引用的学者评价是有效的,但对低发文、高引用的学者进行评价存在缺陷,且数值易于雷同,不易区分。p指数在学者研究绩效评价方面具有同h指数相一致的维度,它不仅考虑学者的被引次数(C),而且考虑学者的研究质量指标——平均被引率(C/N)。以图书情报与文献学科领域49位专家为例,对比分析专家的发文量(N)、被引次数(C)、平均被引率、专家h指标、g指数、p指数,并进行相关性分析。结论:p指数优于现有的h指数、g指数,更具有评价的合理性,应在更大范围内进一步使用。  相似文献   

8.
In this paper we use scale-independent indicators to explore the performance of the Chinese innovation system from an economic and from a science and technology point of view, and compare it with 21 other nations. Some important developments in the Chinese innovation system, hidden by rankings by conventional performance indicators, were revealed. We find that gross domestic expenditure on R&D (GERD) & gross domestic product (GDP) and GDP & POP (population) all exhibit strong ‘Matthew effects’, measured by their scaling factors. This means that the Chinese R&D intensity (GERD/GDP) and national wealth (GDP per capita) are growing significantly with the increase of the GDP. Also pairs such as citations & papers, papers & GDP, citations & GDP, and paper & GERD exhibit these ‘Matthew effects’. This observation points to the fact that in China scientific outputs and impacts are growing faster than economic growth and research investment. However, according to another scale-independent indicator, namely the adjusted relative citation impact (ARCI), China ranks on the bottom of the list, but the growth rate of the ARCI is the highest among these countries (comparing the periods 1995–1999 and 2001–2005). To sum up, we interpret these findings to mean that the scientific outputs and impacts of China show a real tendency of catching up with its economic growth. It is expected that with an increase of its GDP and R&D intensity China will show a sustained increase in indicators related to science and technology. Similarly, there are very strong ‘Matthew effects’ between the outputs of technology (patents) and economic growth and research investment. This means that the outputs of technology are expected to increase considerably with an increase of GDP and R&D expenditure. Furthermore, in the Chinese innovation system the government intramural expenditure on R&D (GOVERD) has a stronger non-linear impact on patent productivity than business enterprise expenditure on R&D (BERD). This shows that in China research institutions financed by the government play a more important role than enterprises.  相似文献   

9.
In economics the Research Papers in Economics (RePEc) network has become an essential source for the gathering and the spread of both existing and new economic research. Furthermore, it is currently the largest bibliometric database in economic sciences containing 33 different indicators for more than 30,000 economists. Based on this bibliographic information RePEc calculates well-known rankings for authors and academic institutions. We provide some cautionary remarks concerning the interpretation of some provided bibliometric measures in RePEc. Moreover, we show how individual and aggregated rankings can be biased due to the employed ranking methodology. In order to select key indicators describing and assessing research performance of scientist, we propose to apply principal component analysis in this data-rich environment. This approach allows us to assign weights to each indicator prior to aggregation. We illustrate the approach by providing a new overall ranking of economists based on RePEc data.  相似文献   

10.
Contemporary social media (SM) has strongly impacted democratic practices. The success of presidential campaigns is frequently attributed to being highly correlated with the candidates' social media performance, but there is no well-established method to measure this performance. Thus, this study aims to improve the understanding of a politician's performance on SM and its correlation with electoral results. Applying a new, recently-defined set of metrics, based on Zajonc's exposition theory and considering the interactions of users on politicians' profiles in multiple SM platforms, this research identifies statistical correlations between SM performance and the votes received in multiple elections. As case studies, this paper focuses on the most recent presidential elections in the four most populous countries in Latin America: Argentina (2019), Brazil (2018), Colombia (2018), and Mexico (2018). Data from more than 65,000 posts were collected from the SM profiles of the main candidates on Facebook, Twitter, and Instagram, starting from 300 days before the election days, and correlations with electoral results were calculated. The results demonstrated strong correlations between the defined metrics and the votes received, particularly the engagement per post, although there were differences among countries. On the other hand, we observed that there is zero or negative correlation between the number of posts and the electoral results.  相似文献   

11.
The popularity of contemporary social media (SM) has impacted democratic practices, and the success of presidential campaigns is frequently attributed to SM performance. Within this new scenario, many methodological proposals that use SM data have been put forward for predicting election results. However, the most common approach, based on the volume and sentiment analysis of mentions on Twitter, has been frequently criticized and challenged. Thus, recent surveys have indicated new directions, such as the use of data from more than one SM platform, the adoption of nonlinear machine learning (ML) models, and the validation of methodologies and experiments in different elections. In this context, the present paper proposes SoMEN, the Social Media framework for Election Nowcasting, a framework composed of a process and an ML model for nowcasting election results based on SM performance as features and with offline polls as labeled data. It also defines SoMEN-DC, an execution strategy for SoMEN that enables continuous prediction during the campaign (DC). The proposed metrics and framework were applied to some of the main recent presidential elections in Latin America: Argentina (2019), Brazil (2018), Colombia (2018), and Mexico (2018). More than 65,000 posts were collected from the SM profiles of candidates on Facebook, Twitter, and Instagram with data from 195 presidential polls. Results have demonstrated that it was possible to achieve a high level of accuracy in predicting the final vote share of the candidates and to make daily predictions, providing competitive or better results than the traditional polls. The strategies put forward in this study have attempted to address several of the current challenges in this research area and have indicated a new manner of how to face the problems. They may also be directly used for predicting future elections in similar scenarios.  相似文献   

12.
Journal metrics are employed for the assessment of scientific scholar journals from a general bibliometric perspective. In this context, the Thomson Reuters journal impact factors (JIFs) are the citation-based indicators most used. The 2-year journal impact factor (2-JIF) counts citations to one and two year old articles, while the 5-year journal impact factor (5-JIF) counts citations from one to five year old articles. Nevertheless, these indicators are not comparable among fields of science for two reasons: (i) each field has a different impact maturity time, and (ii) because of systematic differences in publication and citation behavior across disciplines. In fact, the 5-JIF firstly appeared in the Journal Citation Reports (JCR) in 2007 with the purpose of making more comparable impacts in fields in which impact matures slowly. However, there is not an optimal fixed impact maturity time valid for all the fields. In some of them two years provides a good performance whereas in others three or more years are necessary. Therefore, there is a problem when comparing a journal from a field in which impact matures slowly with a journal from a field in which impact matures rapidly. In this work, we propose the 2-year maximum journal impact factor (2M-JIF), a new impact indicator that considers the 2-year rolling citation time window of maximum impact instead of the previous 2-year time window. Finally, an empirical application comparing 2-JIF, 5-JIF, and 2M-JIF shows that the maximum rolling target window reduces the between-group variance with respect to the within-group variance in a random sample of about six hundred journals from eight different fields.  相似文献   

13.
由Hirsch提出的 h 指数是评价研究人员科研产出的新指标,也可应用于高校学术水平评价。以CNKI为数据源,以《中国科学引文数据库》2001-2010年间收录的关于植物病理的论文为样本,测算高校及各科研院所在植物病理专业研究水平的h指数,并运用 h 指数审视中国病理专业科研机构科研水平以及论文的质量和重要程度、创新性、实用性,体现其学术影响力。   相似文献   

14.
  相似文献   

15.
The effective representation of the relationship between the documents and their contents is crucial to increase classification performance of text documents in the text classification. Term weighting is a preprocess aiming to represent text documents better in Vector Space by assigning proper weights to terms. Since the calculation of the appropriate weight values directly affects performance of the text classification, in the literature, term weighting is still one of the important sub-research areas of text classification. In this study, we propose a novel term weighting (MONO) strategy which can use the non-occurrence information of terms more effectively than existing term weighting approaches in the literature. The proposed weighting strategy also performs intra-class document scaling to supply better representations of distinguishing capabilities of terms occurring in the different quantity of documents in the same quantity of class. Based on the MONO weighting strategy, two novel supervised term weighting schemes called TF-MONO and SRTF-MONO were proposed for text classification. The proposed schemes were tested with two different classifiers such as SVM and KNN on 3 different datasets named Reuters-21578, 20-Newsgroups, and WebKB. The classification performances of the proposed schemes were compared with 5 different existing term weighting schemes in the literature named TF-IDF, TF-IDF-ICF, TF-RF, TF-IDF-ICSDF, and TF-IGM. The results obtained from 7 different schemes show that SRTF-MONO generally outperformed other schemes for all three datasets. Moreover, TF-MONO has promised both Micro-F1 and Macro-F1 results compared to other five benchmark term weighting methods especially on the Reuters-21578 and 20-Newsgroups datasets.  相似文献   

16.
在对新的社区电子商务特色定位和功能模型结构进行研究的基础上,首先对社区电子商务客户服务成熟度的指标构成和各子指标对指标的综合权重进行分析,探讨客户服务成熟度中各子指标对提高消费者信心的各方面因素的作用关系,分析得出通过提升客户服务成熟度的关键因素--配套服务整合能力--提升消费者信心的多方面因素,最终提升消费者信心综合指标的独特路径,最后提出提高配套服务整合的阶段措施建议。  相似文献   

17.
Most of the proposed VLSI dictionary machines appearing in the literature were designed to fit in one chip only. If the number of acquired elements is larger than that of VLSI cells, another chip has to be designed and manufactured to take a larger dictionary into account. In this paper, we propose a new design for dictionary machines that assembles blocks of standard existing dictionary machines. Our machine is as efficient as the best machines described in the literature, with the enormous advantage of scaling up quite easily, with no degradation of its performance, by simply adding more and more standard blocks.  相似文献   

18.
Incorporating fresh members into teams is considered a pathway to team creativity. However, whether freshness improves team performance or not remains unclear, as well as the optimal involvement of fresh members for team performance. Focusing on team impact, one important dimension of team performance, this study uses a group of authors on the byline of a publication as a proxy for a scientific team and quantifies team impact by citations of a paper authored by this team, i.e., article team impact. We extend an indicator, i.e., article team freshness, to measure the extent to which a scientific team incorporates new members, by calculating the fraction of new collaboration relations established within the team. Based on more than 43 million scientific publications covering more than a half-century of research from Microsoft Academic Graph, this study provides a holistic picture of the current development of article team freshness by outlining the temporal evolution of freshness, and its disciplinary distribution. Subsequently, using a multivariable regression approach, we examine the association between article team freshness and papers’ short-term and long-term citations. The major findings are as follows: (1) article team freshness in scientific teams has been increasing in the past half-century; (2) there exists an inverted-U-shaped association between article team freshness and papers’ citations in all the disciplines and different periods; (3) article team impact is hampered by article team freshness in small-sized teams, while medium-sized and large-sized teams can benefit more from article team freshness before the fraction of new collaboration reaches its turning point. The findings of this study provide implications for the practice of team formation and team management in science.  相似文献   

19.
This paper explores a new indicator of journal citation impact, denoted as source normalized impact per paper (SNIP). It measures a journal's contextual citation impact, taking into account characteristics of its properly defined subject field, especially the frequency at which authors cite other papers in their reference lists, the rapidity of maturing of citation impact, and the extent to which a database used for the assessment covers the field's literature. It further develops Eugene Garfield's notions of a field's ‘citation potential’ defined as the average length of references lists in a field and determining the probability of being cited, and the need in fair performance assessments to correct for differences between subject fields. A journal's subject field is defined as the set of papers citing that journal. SNIP is defined as the ratio of the journal's citation count per paper and the citation potential in its subject field. It aims to allow direct comparison of sources in different subject fields. Citation potential is shown to vary not only between journal subject categories – groupings of journals sharing a research field – or disciplines (e.g., journals in mathematics, engineering and social sciences tend to have lower values than titles in life sciences), but also between journals within the same subject category. For instance, basic journals tend to show higher citation potentials than applied or clinical journals, and journals covering emerging topics higher than periodicals in classical subjects or more general journals. SNIP corrects for such differences. Its strengths and limitations are critically discussed, and suggestions are made for further research. All empirical results are derived from Elsevier's Scopus.  相似文献   

20.
The paper introduces a new journal impact measure called The Reference Return Ratio (3R). Unlike the traditional Journal Impact Factor (JIF), which is based on calculations of publications and citations, the new measure is based on calculations of bibliographic investments (references) and returns (citations). A comparative study of the two measures shows a strong relationship between the 3R and the JIF. Yet, the 3R appears to correct for citation habits, citation dynamics, and composition of document types – problems that typically are raised against the JIF. In addition, contrary to traditional impact measures, the 3R cannot be manipulated ad infinitum through journal self-citations.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号