Beyond Google Scholar, Scopus, and Web of Science: An evaluation of the backward and forward citation coverage of 59 databases' citation indices.

Citation indices providing information on backward citation (BWC) and forward citation (FWC) links are essential for literature discovery, bibliographic analysis, and knowledge synthesis, especially when language barriers impede document identification. However, the suitability of citation indices varies. While some have been analyzed, the majority, whether new or established, lack comprehensive evaluation. Therefore, this study evaluates the citation coverage of the citation indices of 59 databases, encompassing the widely used Google Scholar, Scopus, and Web of Science alongside many others never previously analyzed, such as the emerging Lens, Scite, Dimensions, and OpenAlex or the subject-specific PubMed and JSTOR. Through a comprehensive analysis using 259 journal articles from across disciplines, this research aims to guide scholars in selecting indices with broader document coverage and more accurate and comprehensive backward and forward citation links. Key findings highlight Google Scholar, ResearchGate, Semantic Scholar, and Lens as leading options for FWC searching, with Lens providing superior download capabilities. For BWC searching, the Web of Science Core Collection can be recommended over Scopus for accuracy. BWC information from publisher databases such as IEEE Xplore or ScienceDirect was generally found to be the most accurate, yet only available for a limited number of articles. The findings will help scholars conducting systematic reviews, meta-analyses, and bibliometric analyses to select the most suitable databases for citation searching.

The influence of incidental emotions on decision-making under risk and uncertainty: a systematic review and meta-analysis of experimental evidence.

Emotions influence human decisions under risk and uncertainty, even when they are unrelated to the decisions, i.e. incidental to them. Empirical findings are mixed regarding the directions and sizes of the effects of discrete emotions such as fear, anger, or happiness. According to the Appraisal-Tendency Framework (ATF), appraisals of certainty and control determine why same-valence emotions can differentially alter preferences for risky and uncertain options. Building upon this framework of emotion-specific appraisals, we conducted a systematic review and meta-analysis of 28 experimental studies on the effects of discrete incidental emotions on decision-making under risk and uncertainty. We evaluated potential moderators at the task and study levels. We find emotion-specific, moderately heterogeneous effects partially in line with the expectations of the ATF. The framing and financial consequences of choices, the type of choices, and the presence of other participants during the task do not moderate the effect. Our meta-analytic results support the differential influence of discrete, incidental emotions on decision-making under risk and uncertainty depending on appraisals other than valence. We discuss limited sample sizes and heterogeneity as reasons for the absence of significant moderators and encourage experimental investigations of individual differences in the susceptibility to incidental affective influences.

Search where you will find most: Comparing the disciplinary coverage of 56 bibliographic databases.

This paper introduces a novel scientometrics method and applies it to estimate the subject coverages of many of the popular English-focused bibliographic databases in academia. The method uses query results as a common denominator to compare a wide variety of search engines, repositories, digital libraries, and other bibliographic databases. The method extends existing sampling-based approaches that analyze smaller sets of database coverages. The findings show the relative and absolute subject coverages of 56 databases-information that has often not been available before. Knowing the databases' absolute subject coverage allows the selection of the most comprehensive databases for searches requiring high recall/sensitivity, particularly relevant in lookup or exploratory searches. Knowing the databases' relative subject coverage allows the selection of specialized databases for searches requiring high precision/specificity, particularly relevant in systematic searches. The findings illustrate not only differences in the disciplinary coverage of Google Scholar, Scopus, or Web of Science, but also of less frequently analyzed databases. For example, researchers might be surprised how Meta (discontinued), Embase, or Europe PMC are found to cover more records than PubMed in Medicine and other health subjects. These findings should encourage researchers to re-evaluate their go-to databases, also against newly introduced options. Searching with more comprehensive databases can improve finding, particularly when selecting the most fitting databases needs particular thought, such as in systematic reviews and meta-analyses. This comparison can also help librarians and other information experts re-evaluate expensive database procurement strategies. Researchers without institutional access learn which open databases are likely most comprehensive in their disciplines.

The age of abundant scholarly information and its synthesis- A time when 'just google it' is no longer enough.

Academic research has changed in recent years. It has entered the age of abundant scholarly information. New scientometric data shows impressive increases in both the quantity and quality of information researchers produce. Since 2007 about the same number of publications have become accessible on databases as more than the hundred years prior. At the same time, evidence synthesis has become key in making this wealth of information understandable and useful. Researchers need to be increasingly proficient in identifying relevant information - to be able to build on an increasingly comprehensive research base and to adhere to rising standards in evidence synthesis. Both these requirements make a 'true partnership between librarians and researchers' in demand like never before.

What every researcher should know about searching - clarified concepts, search advice, and an agenda to improve finding in academia.

We researchers have taken searching for information for granted for far too long. The COVID-19 pandemic shows us the boundaries of academic searching capabilities, both in terms of our know-how and of the systems we have. With hundreds of studies published daily on COVID-19, for example, we struggle to find, stay up-to-date, and synthesize information-all hampering evidence-informed decision making. This COVID-19 information crisis is indicative of the broader problem of information overloaded academic research. To improve our finding capabilities, we urgently need to improve how we search and the systems we use. We respond to Klopfenstein and Dampier (Res Syn Meth. 2020) who commented on our 2020 paper and proposed a way of improving PubMed's and Google Scholar's search functionalities. Our response puts their commentary in a larger frame and suggests how we can improve academic searching altogether. We urge that researchers need to understand that search skills require dedicated education and training. Better and more efficient searching requires an initial understanding of the different goals that define the way searching needs to be conducted. We explain the main types of searching that we academics routinely engage in; distinguishing lookup, exploratory, and systematic searching. These three types must be conducted using different search methods (heuristics) and using search systems with specific capabilities. To improve academic searching, we introduce the "Search Triangle" model emphasizing the importance of matching goals, heuristics, and systems. Further, we suggest an urgently needed agenda toward search literacy as the norm in academic research and fit-for-purpose search systems.

Which academic search systems are suitable for systematic reviews or meta-analyses? Evaluating retrieval qualities of Google Scholar, PubMed, and 26 other resources.

Rigorous evidence identification is essential for systematic reviews and meta-analyses (evidence syntheses) because the sample selection of relevant studies determines a review's outcome, validity, and explanatory power. Yet, the search systems allowing access to this evidence provide varying levels of precision, recall, and reproducibility and also demand different levels of effort. To date, it remains unclear which search systems are most appropriate for evidence synthesis and why. Advice on which search engines and bibliographic databases to choose for systematic searches is limited and lacking systematic, empirical performance assessments. This study investigates and compares the systematic search qualities of 28 widely used academic search systems, including Google Scholar, PubMed, and Web of Science. A novel, query-based method tests how well users are able to interact and retrieve records with each system. The study is the first to show the extent to which search systems can effectively and efficiently perform (Boolean) searches with regards to precision, recall, and reproducibility. We found substantial differences in the performance of search systems, meaning that their usability in systematic searches varies. Indeed, only half of the search systems analyzed and only a few Open Access databases can be recommended for evidence syntheses without adding substantial caveats. Particularly, our findings demonstrate why Google Scholar is inappropriate as principal search system. We call for database owners to recognize the requirements of evidence synthesis and for academic journals to reassess quality requirements for systematic reviews. Our findings aim to support researchers in conducting better searches for better evidence synthesis.