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Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

ABSTRACT: Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co-occurs in multiple articles constitutes the weight of the link connecting the pair. The network constructed in this manner represents cumulative knowledge of a domain and helps to uncover meaningful knowledge components and insights based on the patterns and strength of links between keywords that appear in the literature. In this work, we propose a KCN-based approach that can be implemented prior to undertaking a systematic review to guide and accelerate the review process. The novelty of this method lies in the new metrics used for statistical analysis of a KCN that differ from those typically used for KCN analysis. The approach is demonstrated through its application to nano-related Environmental, Health, and Safety (EHS) risk literature. The KCN approach identified the knowledge components, knowledge structure, and research trends that match with those discovered through a traditional systematic review of the nanoEHS field. Because KCN-based analyses can be conducted more quickly to explore a vast amount of literature, this method can provide a knowledge map and insights prior to undertaking a rigorous traditional systematic review. This two-step approach can significantly reduce the effort and time required for a traditional systematic literature review. The proposed KCN-based pre-systematic review method is universal. It can be applied to any scientific field of study to prepare a knowledge map.

SUBMITTER: Radhakrishnan S

PROVIDER: S-EPMC5362196 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

Radhakrishnan Srinivasan S Erbis Serkan S Isaacs Jacqueline A JA Kamarthi Sagar S

PloS one 20170322 3

Systematic reviews of scientific literature are important for mapping the existing state of research and highlighting further growth channels in a field of study, but systematic reviews are inherently tedious, time consuming, and manual in nature. In recent years, keyword co-occurrence networks (KCNs) are exploited for knowledge mapping. In a KCN, each keyword is represented as a node and each co-occurrence of a pair of words is represented as a link. The number of times that a pair of words co- ...[more]

PMID: 28328983

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Project description:Objective To explore the evolvement and new trends in the use of Shuanghuanglian injection (SHLI). Methods China National Knowledge Infrastructure (CNKI), PubMed, and Embase were extensively searched using the search terms “Shuanghuanglian injection” and “Shuanghuanglian fenzhen” to retrieve articles relevant to SHLI (1992–2020). Retrieved articles were further investigated by two authors to exclude those unrelated to SHLI. The bibliographical references of the included articles were exported as raw data and then treated using the CiteSpace tool to visualize the mapping of the SHLI research domain. Essential clusters and highly frequent keywords were quantified for further analysis. The clusters were automatically labeled by the algorithm of tf∗idf for objective analysis. Basic bibliometric features, including article types and yearly trend in article numbers were also determined and discussed. Results The modules of the keywords of interest presented clear boundaries with a high modularity score (Q = 0.73). High-confidence clusters were identified, including bioactivity fingerprint (S = 0.99), equal pupils (S = 0.91), drug preparation department (S = 0.87), difficulty in respiration (S = 0.85), peristalsis (0.88), and Danshen powder injection (S = 0.94). The characteristic keywords in terms of frequency and burstiness were Shuanghuanglian powder for injection (F = 235, B = 5.22), SHLI (F = 112, B = 11.39), and adverse drug reactions (ADRs; F = 104, B = 7.35). Conclusion In the field of SHLI study, there are five major topic categories: bioactivity fingerprint; ADR mechanism and cause detection; proper preparation; clinical evidence accumulation; and efficacy in diseases with no effective treatment and combination usage. The trend for using modern methodologies from a science-based perspective to study SHLI will continue to exist. The causes of multi-factorial ADRs may be an important topic for future studies.

Project description:BackgroundPolicy makers and others often require synthesis of knowledge in an area within six months or less. Traditional systematic reviews typically take at least 12 months to conduct. Rapid reviews streamline traditional systematic review methods in order to synthesize evidence within a shortened timeframe. There is great variation in the process of conducting rapid reviews. This review sought to examine methods used for rapid reviews, as well as implications of methodological streamlining in terms of rigour, bias, and results.MethodsA comprehensive search strategy--including five electronic databases, grey literature, hand searching of relevant journals, and contacting key informants--was undertaken. All titles and abstracts (n = 1,989) were reviewed independently by two reviewers. Relevance criteria included articles published between 1995 and 2009 about conducting rapid reviews or addressing comparisons of rapid reviews versus traditional reviews. Full articles were retrieved for any titles deemed relevant by either reviewer (n = 70). Data were extracted from all relevant methodological articles (n = 45) and from exemplars of rapid review methods (n = 25).ResultsRapid reviews varied from three weeks to six months; various methods for speeding up the process were employed. Some limited searching by years, databases, language, and sources beyond electronic searches. Several employed one reviewer for title and abstract reviewing, full text review, methodological quality assessment, and/or data extraction phases. Within rapid review studies, accelerating the data extraction process may lead to missing some relevant information. Biases may be introduced due to shortened timeframes for literature searching, article retrieval, and appraisal.ConclusionsThis review examined the continuum between diverse rapid review methods and traditional systematic reviews. It also examines potential implications of streamlined review methods. More of these rapid reviews need to be published in the peer-reviewed literature with an emphasis on articulating methods employed. While one consistent methodological approach may not be optimal or appropriate, it is important that researchers undertaking reviews within the rapid to systematic continuum provide detailed descriptions of methods used and discuss the implications of their chosen methods in terms of potential bias introduced. Further research comparing full systematic reviews with rapid reviews will enhance understanding of the limitations of these methods.

Project description:Systematically evaluating scientific literature is a time consuming endeavor that requires hours of coding and rating. Here, we describe a method to distribute these tasks across a large group through online crowdsourcing. Using Amazon's Mechanical Turk, crowdsourced workers (microworkers) completed four groups of tasks to evaluate the question, "Do nutrition-obesity studies with conclusions concordant with popular opinion receive more attention in the scientific community than do those that are discordant?" 1) Microworkers who passed a qualification test (19% passed) evaluated abstracts to determine if they were about human studies investigating nutrition and obesity. Agreement between the first two raters' conclusions was moderate (κ = 0.586), with consensus being reached in 96% of abstracts. 2) Microworkers iteratively synthesized free-text answers describing the studied foods into one coherent term. Approximately 84% of foods were agreed upon, with only 4 and 8% of ratings failing manual review in different steps. 3) Microworkers were asked to rate the perceived obesogenicity of the synthesized food terms. Over 99% of responses were complete and usable, and opinions of the microworkers qualitatively matched the authors' expert expectations (e.g., sugar-sweetened beverages were thought to cause obesity and fruits and vegetables were thought to prevent obesity). 4) Microworkers extracted citation counts for each paper through Google Scholar. Microworkers reached consensus or unanimous agreement for all successful searches. To answer the example question, data were aggregated and analyzed, and showed no significant association between popular opinion and attention the paper received as measured by Scimago Journal Rank and citation counts. Direct microworker costs totaled $221.75, (estimated cost at minimum wage: $312.61). We discuss important points to consider to ensure good quality control and appropriate pay for microworkers. With good reliability and low cost, crowdsourcing has potential to evaluate published literature in a cost-effective, quick, and reliable manner using existing, easily accessible resources.

Project description:IntroductionPopulation surveillance provides data on the health status of the population through continuous scrutiny of different indicators. Identifying risk factors is essential for the quickly detecting and controlling of epidemic outbreaks and reducing the incidence of cross-infections and non-communicable diseases. The objective of the present study is to analyze research on population surveillance, identifying the main topics of interest for investigators in the area.MethodologyWe included documents indexed in the Web of Science Core Collection in the period from 2000 to 2019 and assigned with the generic Medical Subject Heading (MeSH) "population surveillance" or its related terms ("public health surveillance," "sentinel surveillance" or "biosurveillance"). A co-occurrence analysis was undertaken to identify the document clusters comprising the main research topics. Scientific production, collaboration, and citation patterns in each of the clusters were characterized bibliometrically. We also analyzed research on coronaviruses, relating the results obtained to the management of the COVID-19 pandemic.ResultsWe included 39,184 documents, which reflected a steady growth in scientific output driven by papers on "Public, Environmental & Occupational Health" (21.62% of the documents) and "Infectious Diseases" (10.49%). Research activity was concentrated in North America (36.41%) and Europe (32.09%). The USA led research in the area (40.14% of documents). Ten topic clusters were identified, including "Disease Outbreaks," which is closely related to two other clusters ("Genetics" and "Influenza"). Other clusters of note were "Cross Infections" as well as one that brought together general public health concepts and topics related to non-communicable diseases (cardiovascular and coronary diseases, mental diseases, diabetes, wound and injuries, stroke, and asthma). The rest of the clusters addressed "Neoplasms," "HIV," "Pregnancy," "Substance Abuse/Obesity," and "Tuberculosis." Although research on coronavirus has focused on population surveillance only occasionally, some papers have analyzed and collated guidelines whose relevance to the dissemination and management of the COVID-19 pandemic has become obvious. Topics include tracing the spread of the virus, limiting mass gatherings that would facilitate its propagation, and the imposition of quarantines. There were important differences in the scientific production and citation of different clusters: the documents on mental illnesses, stroke, substance abuse/obesity, and cross-infections had much higher citations than the clusters on disease outbreaks, tuberculosis, and especially coronavirus, where these values are substantially lower.ConclusionsThe role of population surveillance should be strengthened, promoting research and the development of public health surveillance systems in countries whose contribution to the area is limited.

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Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

Publications

Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.

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