A typology of research discovery tools

Nishikawa-Pacher, Andreas

doi:10.1177/01655515211040654

Cited by 6 publications

(5 citation statements)

References 70 publications

(83 reference statements)

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“…Such a metadata scheme could also help with building better search engines that allow for a more precise discovery of scholarly works, such as based on a given method or theory or research goal, something that already exists for the clinical literature at the PubMed PICO Tool [46,47] but which could be broadened to other disciplines as well. This implementation would thus come close to the original intention of the mnemonic as a tool for research discovery [48] and literature search, rather than just for the formulation of research questions [11,36,49]. In addition, the aggregate patterns of such metadata could also provide insights into the prevalence (or absence) of explicit control groups in specific disciplines.…”

Section: Discussionmentioning

confidence: 80%

Research Questions with PICO: A Universal Mnemonic

Nishikawa-Pacher

2022

Publications

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A well-formulated research question should incorporate the components of a ‘problem’, an ‘intervention’, a ‘control’, and an ‘outcome’—at least according to the PICO mnemonic. The utility of this format, however, has been said to be limited to clinical studies that pose ‘which’ questions demanding correlational study designs. In contrast, its suitability for descriptive approaches outside of clinical investigations has been doubted. This paper disagrees with the alleged limitations of PICO. Instead, it argues that the scheme can be used universally for every scientific endeavour in any discipline with all study designs. This argument draws from four abstract components common to every research, namely, a research object, a theory/method, a (null) hypothesis, and the goal of knowledge generation. Various examples of how highly heterogenous studies from different disciplines can be grounded in the single scheme of PICO are offered. The finding implies that PICO is indeed a universal technique that can be used for teaching academic writing in any discipline, beyond clinical settings, regardless of a preferred study design.

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Section: Discussionmentioning

confidence: 80%

Research Questions with PICO: A Universal Mnemonic

Nishikawa-Pacher

2022

Publications

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“…To what extent do journals reproduce extant citation patterns via their social media postings? 50 How does the composition of an editorial board influence a journal's social media strategy? What would a sentiment analysis reveal about the journals' Tweets regarding the impact factor, and what does the result imply for a 'culture change' that would lead research evaluation away from journal-based metrics?…”

Section: Discussionmentioning

confidence: 99%

The Twitter accounts of scientific journals: a dataset

Nishikawa-Pacher¹

2023

Insights the UKSG Journal

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Twitter harbours dense networks of academics, but to what extent do scientific journals use that platform? This article introduces a dataset of 3,485 Twitter accounts pertaining to a sample of 13,821 journals listed in Web of Science's three major indices (SCIE, SSCI and AHCI). The summary statistics indicate that 25.2% of the journals have a dedicated Twitter presence. This number is likely to grow, as, on average, every one and a half days sees yet another journal setting up a new profile. The share of Twitter presence, however, varies strongly by publisher and discipline. The most active discipline is political science, which has almost 75% of its journals on Twitter, while other research categories have zero. The median account issues 116 messages a year and it interacts with distinct other users once in two to three Tweets. Approximately 600 journals refer to themselves as 'peer-reviewed', while 263 journals refer to their citation-based impact (like the impact factor) in their profile description. All in all, the data convey immense heterogeneity with respect to the Twitter behaviour of scientific journals. As there are numerous deceptive Twitter profile names established by predatory publishers, it is recommended that journals establish their official accounts lest bogus journals mislead the public about scientific findings. The dataset is available for use for further scientometric analyses.

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“…with regards to research evaluation and serendipity-based academic discovery (González-Valiente et al, 2016;Nishikawa-Pacher, 2021;Park & Park, 2018), the time for a more profound analysis of journals' community engagement may already be ripe. To enrich the concept of community engagement by journals, this venue could start with broad data-collection efforts pertaining to journal-initiated prizes, awards, blogs, conferences, newsletters, social media channels or podcasts (this is certainly only an incomplete taxonomy that will dynamically change over time), or collect ever-more fine-grained data such as on whether humour is used or not (Su et al, 2022;Zhang & Lu, 2022), or how the messages teem with jargon (König et al, 2023).…”

Section: Discussionmentioning

confidence: 99%

Predatory Journals on Twitter: The Lack of Community Engagement

Nishikawa-Pacher

2023

Preprint

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Scientific journals disseminate research findings not only via the usual editorial processes, but also by actively engaging with communities on social media platforms such as Twitter. While such an outreach is associated with direct benefits for journals (greater readership, higher citation counts), visibility may not be beneficial to predatory journals whose guiding principle lies in questionable practices. One may thus assume that predatory journals shun community engagement as opposed to serious journals. To test this hypothesis, this paper compares the Twitter interactions of predatory journals’ accounts with that of ‘serious’ (non-predatory) medical-clinical journals. It indeed finds that the median predatory journal hardly ever mentions, retweets or replies to other users, while the median non-predatory journal interacts with distinct, unique users roughly once in three Tweets. The effect size is moderate, but statistically significant. This paper thus suggests that (the absence of) community engagement could possibly serve as yet another indicator distinguishing predatory outlets from their ‘serious’ counterparts, at least as an additional marker in case one is in severe doubt.

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A typology of research discovery tools

Cited by 6 publications

References 70 publications

Research Questions with PICO: A Universal Mnemonic

Research Questions with PICO: A Universal Mnemonic

The Twitter accounts of scientific journals: a dataset

Predatory Journals on Twitter: The Lack of Community Engagement

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