Can Google Scholar and Mendeley help to assess the scholarly impacts of dissertations?     

Kayvan Kousha  Mike Thelwall 《Journal of Informetrics》2019,13(2):467-484

Dissertations can be the single most important scholarly outputs of junior researchers. Whilst sets of journal articles are often evaluated with the help of citation counts from the Web of Science or Scopus, these do not index dissertations and so their impact is hard to assess. In response, this article introduces a new multistage method to extract Google Scholar citation counts for large collections of dissertations from repositories indexed by Google. The method was used to extract Google Scholar citation counts for 77,884 American doctoral dissertations from 2013 to 2017 via ProQuest, with a precision of over 95%. Some ProQuest dissertations that were dual indexed with other repositories could not be retrieved with ProQuest-specific searches but could be found with Google Scholar searches of the other repositories. The Google Scholar citation counts were then compared with Mendeley reader counts, a known source of scholarly-like impact data. A fifth of the dissertations had at least one citation recorded in Google Scholar and slightly fewer had at least one Mendeley reader. Based on numerical comparisons, the Mendeley reader counts seem to be more useful for impact assessment purposes for dissertations that are less than two years old, whilst Google Scholar citations are more useful for older dissertations, especially in social sciences, arts and humanities. Google Scholar citation counts may reflect a more scholarly type of impact than that of Mendeley reader counts because dissertations attract a substantial minority of their citations from other dissertations. In summary, the new method now makes it possible for research funders, institutions and others to systematically evaluate the impact of dissertations, although additional Google Scholar queries for other online repositories are needed to ensure comprehensive coverage.  相似文献   

Exploring the forward citation patterns of patents based on the evolution of technology fields     

Su Jung Jee  Minji Kwon  Jung Moon Ha  So Young Sohn 《Journal of Informetrics》2019,13(4):100985

Forward citations of patents have been used extensively to capture the impact of technological knowledge. However, our understanding of the factors shaping patent citation patterns remains limited. One of the main limitations is the lack of scholarly attention paid to the dynamic influences arising from the evolution of technology fields. From an evolutionary perspective, technological impact is not simply determined by the static attributes of a technology itself; it is also dynamically affected by changes in the external conditions. Drawing on this viewpoint, this study suggests a model for understanding patent citation patterns by reflecting the evolution of the technology fields to which each patent belongs. Four such factors are explored: technology cycle time, potential of technological convergence, popularity of the technology field, and technological novelty. Based on the proposed model, we show how expected citation patterns can change as a result of different scenarios for technology field evolution. We conduct a case study of patents in the information technology and healthcare industries to show citation patterns of patents across heterogeneous industries as well as those within an industry. Contributions to the innovation literature and research investment decisions are discussed.  相似文献   

Measuring scientific contributions with modified fractional counting     

Gunnar Sivertsen  Ronald Rousseau  Lin Zhang 《Journal of Informetrics》2019,13(2):679-694

We develop and propose a new counting method at the aggregate level for contributions to scientific publications called modified fractional counting (MFC). We show that, compared to traditional complete-normalized fractional counting, it eliminates the extreme differences in contributions over time that otherwise occur between scientists that mainly publish alone or in small groups and those that publish with large groups of co-authors. As an extra benefit we find that scientists in different areas of research turn out to have comparable average contributions to scientific articles. We test the method on scientists at Norway’s largest universities and find that, at an aggregate level, it indeed supports comparability across different co-authorship practices as well as between areas of research. MFC is thereby useful whenever the research output from institutions with different research profiles are compared, as e.g., in the Leiden Ranking. Finally, as MFC is actually a family of indicators, depending on a sensitivity parameter, it can be adapted to the circumstances.  相似文献   

Authorship analysis of specialized vs diversified research output     

Giovanni Abramo  Ciriaco Andrea D’Angelo  Flavia Di Costa 《Journal of Informetrics》2019,13(2):564-573

The present work investigates the relations between amplitude and type of collaboration (intramural, extramural domestic or international) and output of specialized versus diversified research. By specialized or diversified research, we mean within or beyond the author’s dominant research topic. The field of observation is the scientific production over five years from about 23,500 academics. The analyses are conducted at the aggregate and disciplinary level. The results lead to the conclusion that in general, the output of diversified research is no more frequently the fruit of collaboration than is specialized research. At the level of the particular collaboration types, international collaborations weakly underlie the specialized kind of research output; on the contrary, extramural domestic and intramural collaborations are weakly associated with diversified research. While the weakness of association remains, exceptions are observed at the level of the individual disciplines.  相似文献   

How does collaboration affect researchers’ positions in co-authorship networks?     

Xiangjie Kong  Mengyi Mao  Huizhen Jiang  Shuo Yu  Liangtian Wan 《Journal of Informetrics》2019,13(3):887-900

Collaboration usually has a positive effect on researchers’ productivity: researchers have become increasingly collaborative, according to recent studies. Numerous studies have focused on enhancing research collaboration by recommendation technology and measuring the influence of researchers. However, few studies have investigated the effect of collaboration on the position of a researcher in the research social network. In this paper, we explore the relationships between collaboration and influence by social analytical methods, which are pertinent to analyzing the network structure and individual traits. We evaluate three aspects of the researchers’ influence: friendship paradox validation, social circle, and structure of a researcher's ego network. Furthermore, the ”six degrees of Bacon number” theory, generalized friendship paradox, and triadic closure theory are introduced to support our analysis. Experimental results show that collaboration can help researchers increase their influence to some extent.  相似文献   

Ranking scientific articles based on bibliometric networks with a weighting scheme     

Yu Zhang  Min Wang  Florian Gottwalt  Morteza Saberi  Elizabeth Chang 《Journal of Informetrics》2019,13(2):616-634

As the volume of scientific articles has grown rapidly over the last decades, evaluating their impact becomes critical for tracing valuable and significant research output. Many studies have proposed various ranking methods to estimate the prestige of academic papers using bibliometric methods. However, the weight of the links in bibliometric networks has been rarely considered for article ranking in existing literature. Such incomplete investigation in bibliometric methods could lead to biased ranking results. Therefore, a novel scientific article ranking algorithm, W-Rank, is introduced in this study proposing a weighting scheme. The scheme assigns weight to the links of citation network and authorship network by measuring citation relevance and author contribution. Combining the weighted bibliometric networks and a propagation algorithm, W-Rank is able to obtain article ranking results that are more reasonable than existing PageRank-based methods. Experiments are conducted on both arXiv hep-th and Microsoft Academic Graph datasets to verify the W-Rank and compare it with three renowned article ranking algorithms. Experimental results prove that the proposed weighting scheme assists the W-Rank in obtaining ranking results of higher accuracy and, in certain perspectives, outperforming the other algorithms.  相似文献   

Relevance-based entity selection for ad hoc retrieval     

Faezeh Ensan  Feras Al-Obeidat 《Information processing & management》2019,56(5):1645-1666

Recent developments have shown that entity-based models that rely on information from the knowledge graph can improve document retrieval performance. However, given the non-transitive nature of relatedness between entities on the knowledge graph, the use of semantic relatedness measures can lead to topic drift. To address this issue, we propose a relevance-based model for entity selection based on pseudo-relevance feedback, which is then used to systematically expand the input query leading to improved retrieval performance. We perform our experiments on the widely used TREC Web corpora and empirically show that our proposed approach to entity selection significantly improves ad hoc document retrieval compared to strong baselines. More concretely, the contributions of this work are as follows: (1) We introduce a graphical probability model that captures dependencies between entities within the query and documents. (2) We propose an unsupervised entity selection method based on the graphical model for query entity expansion and then for ad hoc retrieval. (3) We thoroughly evaluate our method and compare it with the state-of-the-art keyword and entity based retrieval methods. We demonstrate that the proposed retrieval model shows improved performance over all the other baselines on ClueWeb09B and ClueWeb12B, two widely used Web corpora, on the [email protected], and [email protected] metrics. We also show that the proposed method is most effective on the difficult queries. In addition, We compare our proposed entity selection with a state-of-the-art entity selection technique within the context of ad hoc retrieval using a basic query expansion method and illustrate that it provides more effective retrieval for all expansion weights and different number of expansion entities.  相似文献   

基于作者共被引分析的破坏性创新研究学术群类与脉络探析     

林春培  黄海媚  吴东儒 《科学学与科学技术管理》2016,(8):68-81

破坏性创新理论是当前国内外战略管理理论和创新理论研究的前沿与热点。运用作者共被引分析方法,对Web of Science数据库中破坏性创新相关文献进行定量分析。研究发现破坏性创新研究可分为概念模型建构、形成机理探析、影响因素识别、实现路径探讨四个学术群。概念模型建构学术群主要阐述破坏性创新的基本概念、特征及理论模型;形成机理探析学术群侧重探析破坏性创新的发生条件及形成机理;影响因素识别学术群主要研究组织开展破坏性创新的内外驱动或抑制要素;实现路径探讨学术群则从目标市场、侵蚀路径及推进策略三个方面探讨破坏性创新的开展途径;四个学术群基于不同视角探讨破坏性创新理论,但在学术贡献率、代表人物、研究地位及主要观点上存在差异。  相似文献   

《吉林农业大学学报》2002-2005年载文作者统计与分析   总被引：2，自引：0，他引：2  

赵立华  赵爱群  焦培娟 《现代情报》2007,27(2):170-172

采用文献计量学方法,对《吉林农业大学学报》2002-2005年载文作者的性别、年龄、职称等进行了统计分析,并根据普赖斯定律确定了核心作者和杰出作者人数,最后对稳定作者队伍及如何进一步办好《吉林农业大学学报》提出了相应的建议。  相似文献   

中国情报学核心作者态势评估   总被引：3，自引：0，他引：3  

樊松林 《情报科学》1991,12(3):13-23

本文通过对46名核心作者的年龄结构、发文数量、职业类别、所在地域及其文献生产的投向、主题内容、专题领域、被引频次等指标的考察分析,提出了核心作者情报学研究活动的一些特点和规律,并以讨论的方式估测了我国今后几年的核心作者态势。  相似文献