A comparative analysis on digital libraries and academic search engines from the dual-route perspective

Lorena Delgado-Quirós José Luis Ortega

8 Februari 2024

Abstract The main objective of this study is to compare the amount of metadata and the completeness degree of research publications in new academic databases. Using a quantitative approach, we selected a random Crossref sample of more than 115,000 records, which was then searched in seven databases (Dimensions, Google Scholar, Microsoft Academic, OpenAlex, Scilit, Semantic Scholar, and The Lens). Seven characteristics were analyzed (abstract, access, bibliographic info, document type, publication date, language, and identifiers), to observe fields that describe this information, the completeness rate of these fields, and the agreement among databases. The results show that academic search engines (Google Scholar, Microsoft Academic, and Semantic Scholar) gather less information and have a low degree of completeness. Conversely, third-party databases (Dimensions, OpenAlex, Scilit, and The Lens) have more metadata quality and a higher completeness rate. We conclude that academic search engines lack the ability to retrieve reliable descriptive data by crawling the web, and the main problem of third-party databases is the loss of information derived from integrating different sources.

O. Sundin Jutta Haider D. Lewandowski

21 Agustus 2021

This opinion piece takes Google's response to the so‐called COVID‐19 infodemic, as a starting point to argue for the need to consider societal relevance as a complement to other types of relevance. The authors maintain that if information science wants to be a discipline at the forefront of research on relevance, search engines, and their use, then the information science research community needs to address itself to the challenges and conditions that commercial search engines create in. The article concludes with a tentative list of related research topics.

Maryna Sydorova Roberto Ulloa Mona Bielig + 2 lainnya

16 November 2023

Researchers rely on academic Web search engines to find scientific sources, but search engine mechanisms may selectively present content that aligns with biases embedded in queries. This study examines whether confirmation biased queries prompted into Google Scholar and Semantic Scholar will yield results aligned with a query’s bias. Six queries (topics across health and technology domains such as ‘vaccines’, ‘Internet use’) were analyzed for disparities in search results. We confirm that biased queries (targeting ‘benefits’ or ‘risks’) affect search results in line with bias, with technology-related queries displaying more significant disparities. Overall, Semantic Scholar exhibited fewer disparities than Google Scholar. Topics rated as more polarizing did not consistently show more disparate results. Academic search results that perpetuate confirmation bias have strong implications for both researchers and citizens searching for evidence. More research is needed to explore how scientific inquiry and academic search engines interact.

Kevin Matthe Caramancion

11 Januari 2024

This study embarked on a comprehensive exploration of user preferences between Search Engines and Large Language Models (LLMs) in the context of various information retrieval scenarios. Conducted with a sample size of 100 internet users (N=100) from across the United States, the research delved into 20 distinct use cases ranging from factual searches, such as looking up COVID-19 guidelines, to more subjective tasks, like seeking interpretations of complex concepts in layman's terms. Participants were asked to state their preference between using a traditional search engine or an LLM for each scenario. This approach allowed for a nuanced understanding of how users perceive and utilize these two predominant digital tools in differing contexts. The use cases were carefully selected to cover a broad spectrum of typical online queries, thus ensuring a comprehensive analysis of user preferences. The findings reveal intriguing patterns in user choices, highlighting a clear tendency for participants to favor search engines for direct, fact-based queries, while LLMs were more often preferred for tasks requiring nuanced understanding and language processing. These results offer valuable insights into the current state of digital information retrieval and pave the way for future innovations in this field. This study not only sheds light on the specific contexts in which each tool is favored but also hints at the potential for developing hybrid models that leverage the strengths of both search engines and LLMs. The insights gained from this research are pivotal for developers, researchers, and policymakers in understanding the evolving landscape of digital information retrieval and user interaction with these technologies.

Omotoyosi Eluyemi Bolanle Clifford Ishola Sarah Akpobasah-Amugen + 1 lainnya

1 April 2023

The study adopted a research design of the qualitative type to investigate library services amid the COVID-19 Pandemic using remotely exploitable electronic academic databases in two Nigerian foremost university libraries, as case studies. An Interview guide was used to elicit data from E-Librarians of the two Federal University libraries randomly selected for the study. The interview guide contains seventeen questions that seek to proffer answers to the main objective of the study. Response retrieved were analyzed using thematic analysis to extract codes, identify patterns, and create themes relevant to the study’s objective. The study revealed that both libraries have a functional E-library and subscribes to key databases. The study also revealed that both libraries’ websites are connected to open source databases remotely accessible to library users. The study reinforces the need to embrace the change in the global architecture of library services in the wake of the COVID -19 pandemic and make their E-resources remotely accessible to users. The study recommended that library managers should adopt best practices in providing users with remote access to their E-resources. Also, the study underscores the need for library managers to reappraise their memorandum of understanding with E-databases aggregator, allowing their E-resources to be remotely accessible to library users’ thereby limiting users contact with their physical library environment amid the COVID-19 Pandemic.