Exploiting citation overlaps for Information Retrieval: Generating a boomerang effect from the network of scientific papers

A new citation search strategy is proposed for Information Retrieval (IR) based on the principle of polyrepresentation (Ingwersen, 1992, 1996). The strategy exploits logical overlaps between a range of cognitively different interpretations of the same documents in a structured manner, i.e. so-called cognitive overlaps of representations. The strategy is essentially a "cycling strategy" starting with documents retrieved by a subject search, wherefrom new documents are identified automatically by following the network of citations in scientific papers backwards and forwards in time. In contrast to earlier citation search strategies the proposed strategy does not require known relevant documents (seed documents) as a starting point, but may be based on a subject search. A pilot study is reported where the ability of the strategy to retrieve additional relevant documents is analysed. Results show that a very large amount of documents can be retrieved by the strategy, and that these may be segmented in a number of distinct "overlap levels". It is demonstrated that the combined core of the higher-level overlaps contains higher relevance density than found in the original retrieval results. Based on these results it is suggested that the documents be displayed in order of their presence in higher-level overlaps, so as to maximise the chances that as many relevant documents as possible will be presented first to a user. This revised version was published online in June 2006 with corrections to the Cover Date.     

Literature retrieval based on citation context

While the citation context of a reference may provide detailed and direct information about the nature of a citation, few studies have specifically addressed the role of this information in retrieving relevant documents from the literature primarily due to the lack of full text databases. In this paper, we design a retrieval system based on full texts in the PubMed Central database. We constructed two modules in the retrieval system. One is a reference retrieval module based on citation contexts. Another is a citation context retrieval module for searching the citation contexts of a specific paper. The results of comparisons show that the reference retrieval module performed better than Google Scholar and PubMed database in terms of finding proper references based on topic words extracted from citation context. It also performed very well on searching highly cited papers and classic papers. The citation context retrieval module visualizes the topics of citation contexts as tag clouds and classifies citation contexts based on cue words in citation contexts.     

Do citations and readership identify seminal publications?

This work presents a new approach for analysing the ability of existing research metrics to identify research which has strongly influenced future developments. More specifically, we focus on the ability of citation counts and Mendeley reader counts to distinguish between publications regarded as seminal and publications regarded as literature reviews by field experts. The main motivation behind our research is to gain a better understanding of whether and how well the existing research metrics relate to research quality. For this experiment we have created a new dataset which we call TrueImpactDataset and which contains two types of publications, seminal papers and literature reviews. Using the dataset, we conduct a set of experiments to study how citation and reader counts perform in distinguishing these publication types, following the intuition that causing a change in a field signifies research quality. Our research shows that citation counts work better than a random baseline (by a margin of 10%) in distinguishing important seminal research papers from literature reviews while Mendeley reader counts do not work better than the baseline.     

Zero impact: a large-scale study of uncitedness

This paper presents a large-scale study of the phenomenon ‘uncitedness’. A literature review indicates that uncitedness is related to at least three factors: Field, document type, and time. To explore these factors and their mutual influence further, and at much larger scale than previous studies, the paper focuses on seven subject areas (arts and humanities; social sciences; computer science; mathematics; engineering; medicine; physics and astronomy), seven document types (articles; reviews; notes; letters; conference papers; books; book chapters), and a 20-year publication window (1996–2015). Documents are searched in Scopus, and retrieved year-by-year, discipline-by-discipline, and for each individual document type (total: 29,472,184 documents; 7,508,741 uncited documents). The results show great variance in uncitedness ratios between subject areas and document types. This is probably caused by a somewhat tacitly agreed upon genre hierarchy existing in all subject areas, yet with important local traits and differences. The importance of the time-dimension is documented. Time to first citation varies a great deal between subject areas, and the uncitedness ratio is consequently shown to be quite sensitive to the length of citation windows.

     

A guide to efficient keyword, sequence and classification search strategies for biopharmaceutical drug-centric patent landscape searches - A human recombinant insulin patent landscape case study

Searching biopharmaceutical drug-related patent information is generally considered to be challenging. In particular, setting up efficient search strategies for comprehensive retrieval of high amounts of patent documents related to processes and methods of use, that achieve a reasonable level of precision, but still remain within a particular search scope. While it is generally accepted that patent information cannot be searched using standardized approaches, it is desirable to have a basic rule set for successful biopharmaceutical drug-related patent information retrieval, particularly facing a steady flow of patent expirations for prominent biologic drugs. The present human recombinant insulin case study shows an assessment of keyword, sequence and classification search strategies for establishing biopharmaceutical drug-centric patent landscapes. The search results of both crude and sophisticated keyword search strategies, as well as of a sequence search strategy, were compared in terms of the key information retrieval quality indicators; the recall and the precision. Through analyses of the relevant retrieved documents, a quality assessment of keyword choice is provided, as well as determining focused IPC and Derwent Manual classification codes and terminology from original patent and Derwent documentation abstract titles. All of which can be used for setting up more efficient search strategies and facilitated document categorization.     

Tracing the wider impacts of biomedical research: a literature search to develop a novel citation categorisation technique

There is an increasing need both to understand the translation of biomedical research into improved healthcare and to assess the range of wider impacts from health research such as improved health policies, health practices and healthcare. Conducting such assessments is complex and new methods are being sought. Our new approach involves several steps. First, we developed a qualitative citation analysis technique to apply to biomedical research in order to assess the contribution that individual papers made to further research. Second, using this method, we then proposed to trace the citations to the original research through a series of generations of citing papers. Third, we aimed eventually to assess the wider impacts of the various generations. This article describes our comprehensive literature search to inform the new technique. We searched various databases, specific bibliometrics journals and the bibliographies of key papers. After excluding irrelevant papers we reviewed those remaining for either general or specific details that could inform development of our new technique. Various characteristics of citations were identified that had been found to predict their importance to the citing paper including the citation??s location; number of citation occasions and whether the author(s) of the cited paper were named within the citing paper. We combined these objective characteristics with subjective approaches also identified from the literature search to develop a citation categorisation technique that would allow us to achieve the first of the steps above, i.e., being able routinely to assess the contribution that individual papers make to further research.     

H-Classics: characterizing the concept of citation classics through H-index

Citation classics identify those highly cited papers which are an important reference point in a research field. To identify a paper as a citation classic we have to fix a citation threshold value. Usually, this threshold value should not be the same for all research fields because each field presents its respective citation pattern. Studies of citation classics in the literature define particular criteria and methods to set citation thresholds, which are often set arbitrarily and designed ad-hoc, and do not allow the scientific community to validate and compare their results. In this paper we introduce the concept of H-Classics to overcome this problem and provide scientific community a standardization of key constructs. We present a new and systematic method to identify citation classics. This identification method of highly cited papers is based on the H-index and thank to the properties of H-index it is sensitive to the own characteristics of any research discipline and also its evolution. Therefore, the concept of H-Classics allows to systematize search procedure of citation classics for any field of research.     

Related records retrieval and pennant retrieval: an exploratory case study

The Related Records feature in the Web of Science retrieves records that share at least one item in their reference lists with the references of a seed record. This search method, known as bibliographic coupling, does not always yield topically relevant results. Our exploratory case study asks: How do retrievals of the type used in pennant diagrams compare with retrievals through Related Records? Pennants are two-dimensional visualizations of documents co-cited with a seed paper. In them, the well-known tf*idf (term frequency*inverse document frequency) formula is used to weight the co-citation counts. The weights have psychological interpretations from relevance theory; given the seed, tf predicts a co-cited document’s cognitive effects on the user, and idf predicts the user’s relative ease in relating its title to the seed’s title. We chose two seed papers from information science, one with only two references and the other with 20, and used them to retrieve 50 documents per method in WoS for each of our two seeds. We illustrate with pennant diagrams. Pennant retrieval indeed produced more relevant documents, especially for the paper with only two references, and it produced mostly different ones. Related Records performed almost as well on the paper with the longer reference list, improving remarkably as the coupling units between the seed and other papers increased. We argue that relevance rankings based on co-citation, with pennant-style weighting as an option, would be a desirable addition to WoS and similar databases.

     

The effect of document types and sizes on the scaling relationship between citations and co-authorship patterns in management journals

The aim of this paper is to explore the power-law relationship between citation-based performance (CBP) and co-authorship patterns for papers in management journals by analyzing its behavior according to the type of documents (articles and reviews) and the number of pages of documents. We analyzed 36,241 papers that received 239,172 citations. The scaling exponent of CBP for article papers was larger than for reviews. Citations to articles increased 2^1.67 or 3.18 times each time the number of article papers published in a year in management journals doubled. The citations to reviews increased 2^1.29 or 2.45 times each time the number of reviews published in a year in management journals doubled. The scaling exponent for the power-law relationship of citation-based performance according to number of pages of papers was 1.44 ± 0.05 for articles and 1.25 ± 0.05 for reviews. The citations to articles increased faster than citation to reviews. The scaling exponent for the power-law of citation-based performance to co-authored articles was higher than single-authored articles. For reviews the scaling exponent was the same for the relationship between citation based performance and the number of reviews. Citations increased faster in single authored reviews than co-authored reviews.     

Can applied science be ‘good science’? Exploring the relationship between patent citations and citation impact in nanoscience

There is a rich literature on how science and technology are related to each other. Patent citation analysis is amongst the most frequently used to tool to track the strengths of links. In this paper we explore the relationship between patent citations and citation impact in nanoscience. Our observations indicate that patent-cited papers perform better in terms of standard bibliometric indicators than comparable publications that are not linked to technology in this way. More specifically, we found that articles cited in patents are more likely to be cited also by other papers. The share of highly cited papers is the most striking result. Instead of the average of 4% of all papers, 13.8% of the papers cited once or twice in patents fall into this category and even 23.5% of the papers more frequently cited in patents receive citation rates far above the standard. Our analyses further demonstrate the presence and the relevance of bandwagon effects driving the development of science and technology.     

Exploring the analytical potential of comparing citing and cited source items

Summary Comparing properties of citing and cited source items opens a wide variety of analytical possibilities. In a study of citations among papers in the journal Scientometrics a number of analytical themes are identified. The analysis shows: the way in which a citation graph can be decomposed into different subparts; country specific citation patterns; the effects of self-citations and domestic citations; the mapping of cited author relationships using direct citation and co-citation links; and time slicing effects on impact ranking of countries and papers.     

Citation genetic genealogy: a novel insight for citation analysis in scientific literature

Citation relationships are commonly described with citation network or citation graph, but in this article, the author introduced the notion of citation genetic genealogy and apply it in citation analysis. A citing document usually only uses pieces of its cited document, so the author of this article defined these valuable pieces of a scientific document, which carry the information that have been used by its citing documents as its document genes. Besides, with the definition of symbolic information of a scientific document, the conclusion that a citing document inherited the document genes from its references can be drawn. Based on these understandings, citation genetic genealogy is constructed to describe citation relationships. With citation genetic genealogy, it is easy to map the citation relationships, like bibliographic coupling and co-citation, with familiar family relationships and illustrate the inheritance relationships in scientific literatures. Also, citation genetic genealogy may provide an interface between the citation analysis of a document set and the content analysis for each individual document inside this document set.     

In quest of new document relations: evaluating co-opinion relations between co-citations and its impact on Information retrieval effectiveness

Document relational network has been effective in retrieving and evaluating papers. Despite their effectiveness, relational measures, including co-citation, are far from ideal and need improvements. The assumption underlying the co-citation relation is the content relevance and opinion relatedness of cited and citing papers. This may imply existence of some kind of co-opinionatedness between co-cited papers which may be effective in improving the measure. Therefore, the present study tries to test the existence of this phenomenon and its role in improving information retrieval. To do so, based on CITREC, a medical test collection was developed consisting of 30 queries (seed documents) and 4823 of their co-cited papers. Using NLP techniques, the co-citances of the queries and their co-cited papers were analyzed and their similarities were computed by 4 g similarity measure. Opinion scores were extracted from co-citances using SentiWordnet. Also, nDCG values were calculated and then compared in terms of the citation proximity index (CPI) and co-citedness measures before and after being normalized by the co-opinionatedness measure. The reliability of the test collection was measured by generalizability theory. The findings suggested that a majority of the co-citations exhibited a high level of co-opinionatedness in that they were mostly similar either in their opinion strengths or in their polarities. Although anti-polar co-citations were not trivial in their number, a significantly higher number of the co-citations were co-polar, with a majority being positive. The evaluation of the normalization of the CPI and co-citedness by the co-opinionatedness indicated a generally significant improvement in retrieval effectiveness. While anti-polar similarity reduced the effectiveness of the measure, the co-polar similarity proved to be effective in improving the co-citedness. Consequently, the co-opinionatedness can be presented as a new document relation and used as a normalization factor to improve retrieval performance and research evaluation.

     

Bibliometric analysis of pentachlorophenol remediation methods during the period of 1994 to 2005

A bibliometric analysis was performed to assess the quantitative trend of published pentachlorophenol (PCP) remediation studies, including both degradation and sorption. The documents studies were retrieved from the Science Citation Index (SCI) for the period from 1994 to 2005. The trends were analyzed with the retrieved results in publication language, document type, page count, publication output, publication pattern, authorship, citation analysis and country of publication. The results indicated that degradation was the emphasis for PCP remediation. The average impact factor of the journals was higher for publishing degradation studies in comparison to that publishing sorption studies. And there was a positive correlation between CPP and IF for journals published more than two papers. The publishing countries of both degradation and sorption denoted that most of these researches were done by USA and Canada. Two to four authors was the most popular level of co-authorship.     

Sources of Google Scholar citations outside the Science Citation Index: A comparison between four science disciplines

For practical reasons, bibliographic databases can only contain a subset of the scientific literature. The ISI citation databases are designed to cover the highest impact scientific research journals as well as a few other sources chosen by the Institute for Scientific Information (ISI). Google Scholar also contains citation information, but includes a less quality controlled collection of publications from different types of web documents. We define Google Scholar unique citations as those retrieved by Google Scholar which are not in the ISI database. We took a sample of 882 articles from 39 open access ISI-indexed journals in 2001 from biology, chemistry, physics and computing and classified the type, language, publication year and accessibility of the Google Scholar unique citing sources. The majority of Google Scholar unique citations (70%) were from full-text sources and there were large disciplinary differences between types of citing documents, suggesting that a wide range of non-ISI citing sources, especially from non-journal documents, are accessible by Google Scholar. This might be considered to be an advantage of Google Scholar, since it could be useful for citation tracking in a wider range of open access scholarly documents and to give a broader type of citation impact. An important corollary from our study is that Google Scholar’s wider coverage of Open Access (OA) web documents is likely to give a boost to the impact of OA research and the OA movement.     

Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis

During Eugene Garfield’s (EG’s) lengthy career as information scientist, he published about 1500 papers. In this study, we use the impressive oeuvre of EG to introduce a new type of bibliometric networks: keyword co-occurrences networks based on the context of citations, which are referenced in a certain paper set (here: the papers published by EG). The citation context is defined by the words which are located around a specific citation. We retrieved the citation context from Microsoft Academic. To interpret and compare the results of the new network type, we generated two further networks: co-occurrence networks which are based on title and abstract keywords from (1) EG’s papers and (2) the papers citing EG’s publications. The comparison of the three networks suggests that papers of EG and citation contexts of papers citing EG are semantically more closely related to each other than to titles and abstracts of papers citing EG. This result accords with the use of citations in research evaluation that is based on the premise that citations reflect the cognitive influence of the cited on the citing publication.     

Author collaboration and impact: A note on citation rates of single and multiple authored articles

The acceptance rate of articles which are collaboratively authored tends to be higher than that for single-authored papers, thereby suggesting a generally positive relationship between collaboration and quality. The analysis of ten-year citation rates of 270 randomly selected articles in three applied fields likewise shows a similar relationship, with somewhat higher citation frequencies for multi-authored papers than for single-authored ones. The relationships persist whether self-citations are included or excluded. However, these differences are not statistically significant for articles in clinical psychology or in educational measurement. Only multi-authored articles in management science show a statistically significant higher citation rate. Other aspects of the collaborative process and effects are discussed.     

Relation of seminal nanotechnology document production to total nanotechnology document production — South Korea

This study evaluates trends in quality of nanotechnology and nanoscience papers produced by South Korean authors. The metric used to gauge quality is ratio of highly cited nanotechnology papers to total nanotechnology papers produced in sequential time frames. In the first part of this paper, citations (and publications) for nanotechnology documents published by major producing nations and major producing global institutions in four uneven time frames are examined. All nanotechnology documents in the Science Citation Index [SCI, 2006] for 1998, 1999–2000, 2001–2002, 2003 were retrieved and analyzed in March 2007. In the second part of this paper, all the nanotechnology documents produced by South Korean institutions were retrieved and examined. All nanotechnology documents produced in South Korea (each document had at least one author with a South Korea address) in each of the above time frames were retrieved and analyzed. The South Korean institutions were extracted, and their fraction of total highly cited documents was compared to their fraction of total published documents. Non-Korean institutions that co-authored papers were included as well, to offer some perspective on the value of collaboration.     

Using online databases to form subject collections for informetric analyses

The online databases of the Dialog System retrieve only 26% of documents in an exhaustively compiled collection on the subject of Bradford's Law of Scattering, with some documents being retrieved from many databases. However, when the Exhaustive Collection is more stringently defined to include only those documents more about the subject, the retrieval rate of Dialog improves to 61%, while its most productive database, LISA, alone retrieves 37%. Both of these ‘samples’ give good estimates of the size-invariant properties of the Exhaustive Collection which are typically studied in Bradford and Growth Analyses—vindicating this use of online searching. However, without additional information, online searches are of little use in determining size-related properties of subject literature collections. Whether the analysis reported here—which relies on identical interpretations of a ‘subject’—has secure foundations is briefly considered.