Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation

The methodological and ethical concerns of genetic studies of same-sex sexual behavior

Same-sex sexual behavior has long interested genetics researchers in part because, while there is evidence of heritability, the trait as typically defined is associated with fewer offspring. Investigations of this phenomenon began in the 1990s with linkage studies and continue today with the advent of genome-wide association studies. As this body of research grows, so does critical scientific and ethical review of it. Here, we provide a targeted overview of existing genetics studies on same-sex sexual behavior, highlight the ethical and scientific considerations of this nascent field, and provide recommendations developed by the authors to enhance social and ethical responsibility.

The clinical, mechanistic, and social impacts of air pollution on atopic dermatitis

Atopic dermatitis (AD) is a complex disease characterized by dry, pruritic skin and significant atopic and psychological sequelae. Although AD has always been viewed as multifactorial, early research was dominated by overlapping genetic determinist views of either innate barrier defects leading to inflammation or innate inflammation eroding skin barrier function. Since 1970, however, the incidence of AD in the United States has increased at a pace that far exceeds genetic drift, thus suggesting a modern, environmental etiology. Another implicated factor is Staphylococcus aureus; however, a highly contagious microorganism is unlikely to be the primary etiology of a noncommunicable disease. Recently, the roles of the skin and gut microbiomes have received greater attention as potentially targetable drivers of AD. Here too, however, dysbiosis on a population scale would require induction by an environmental factor. In this review, we describe the evidence supporting the environmental hypothesis of AD etiology and detail the molecular mechanisms of each of the AD-relevant toxins. We also outline how a pollution-focused paradigm demands earnest engagement with environmental injustice if the field is to meaningfully address racial and geographic disparities. Identifying specific toxins and their mechanisms can also inform in-home and national mitigation strategies.

Feminist retroviruses to white Sharia: Gender "science fan fiction" on 4Chan

This article demonstrates-based on an interpretive discourse analysis of three types of memes (Rabid Feminists, Women's Bodies, Policy Ideas) and secondary thread discourse on 4chan's "Politically Incorrect" discussion board-two key findings: (1) the existence of a gendered hate based scientific discourse, "science fan fiction," in online spaces and (2) how gender "science fan fiction" is an outcome of the male supremacist cosmology, by producing and justifying resentment against white women as being both inherently untrustworthy (politically, sexually, intellectually) and dangerous. This perspective-which combines hatred and distrust of women with white nationalist anxieties about demographic shifts, racial integrity, and sexuality-then motivates misogynist policy ideas including total domination of women or their removal. 4chan users employ this discourse to "scientifically" substantiate claims of white male supremacy, the fundamental untrustworthiness of white women, and to argue white women's inherent threat to white male supremacist goals.

Race science without racists: how bigoted paradigms persist in allergy research

In the wake of the murder of George Floyd and the massacre in Buffalo, the editorial boards of the prominent scientific publication companies formally apologized for their journals' historical role in advancing race science and promised to improve their standards. However, flowery commentaries cannot undo the consistent pattern of endorsing biologic differences between ethnic groups, even when discussing diseases or traits that are not considered politically charged. In this report, an exemplar is made of a recent publication claiming to identify phenotypes of atopic dermatitis that are distinct between European Americans, Asians, and African Americans. The insufficiency of the evidence and logic underlying these claims are discussed. Although devoid of malice, numerous publications continue to demonstrate how claims of biological differences between races is mainstreamed in modern scientific publications. Overall, the goal of this work is to challenge the scientific community, particularly the publication companies, to evaluate how assumptions of innate biologic disadvantage have clouded assessments of racial disparities in disease beyond the topics that are more stereotypical of race science.

Reimagining bioRxiv and preprint servers as platforms for academic learning

A popular preprint server, bioRxiv, is important as a tool for increased visibility for life science research. If used properly, however, bioRxiv can also be an important tool for training, as it may expose trainees (degree-seeking students undertaking research or internships directly related to their field of study) to the peer review process. Here, we offer a comprehensive guide to using bioRxiv as a training tool, as well as offer suggestions for improvements in bioRxiv, including confusion that may be caused by bioRxiv articles appearing on PubMed.

Typological thinking in human genomics research contributes to the production and prominence of scientific racism

Public genomic datasets like the 1000 Genomes project (1KGP), Human Genome Diversity Project (HGDP), and the Adolescent Brain Cognitive Development (ABCD) study are valuable public resources that facilitate scientific advancements in biology and enhance the scientific and economic impact of federally funded research projects. Regrettably, these datasets have often been developed and studied in ways that propagate outdated racialized and typological thinking, leading to fallacious reasoning among some readers that social and health disparities among the so-called races are due in part to innate biological differences between them. We highlight how this framing has set the stage for the racist exploitation of these datasets in two ways: First, we discuss the use of public biomedical datasets in studies that claim support for innate genetic differences in intelligence and other social outcomes between the groups identified as races. We further highlight recent instances of this which involve unauthorized access, use, and dissemination of public datasets. Second, we discuss the memification, use of simple figures meant for quick dissemination among lay audiences, of population genetic data to argue for a biological basis for purported human racial groups. We close with recommendations for scientists, to preempt the exploitation and misuse of their data, and for funding agencies, to better enforce violations of data use agreements.

"What Do I Say? How Do I Say it?" Twitter as a Knowledge Dissemination Tool for Mental Health Research

This study aims to generate evidence-based guidelines for researchers regarding how to effectively disseminate mental health research via Twitter. Three hundred mental health research Tweets posted from September 2018 to September 2019 were sampled from two large Australian organizations. Twenty-seven predictor variables were coded for each Tweet across five thematic categories: messaging; research area; mental health area; external networks; and media features. Regression analyses were conducted to determine associations with engagement outcomes of Favourites, Retweets, and Comments. Less than half (n = 10) of predictor variables passed validity tests. Notably, conclusions could not reliably be drawn on whether a Tweet featured evidence-based information. Tweets were significantly more likely to be Retweeted if they contained a hyperlink or multimedia. Tweets were significantly more likely to receive comments if they focused on a specific population group. These associations remain significant when controlling for organization. These findings indicate that researchers may be able to maximize engagement on Twitter by highlighting the population groups that the research applies to and enriching Tweets with multimedia content. In addition, care should be taken to ensure users can infer which messages are evidence-based. Guidelines and an accompanying resource are proposed.

Addressing the ethical and societal challenges posed by genome-wide association studies of behavioral and brain-related traits

Genome-wide association studies have led to the identification of robust statistical associations of genetic variants with numerous brain-related traits, including neurological and psychiatric conditions, and psychological and behavioral measures. These results may provide insight into the biology underlying these traits and may facilitate clinically useful predictions. However, these results also carry the risk of harm, including possible negative effects of inaccurate predictions, violations of privacy, stigma and genomic discrimination, raising serious ethical and legal implications. Here, we discuss ethical concerns surrounding the results of genome-wide association studies for individuals, society and researchers. Given the success of genome-wide association studies and the increasing availability of nonclinical genomic prediction technologies, better laws and guidelines are urgently needed to regulate the storage, processing and responsible use of genetic data. Also, researchers should be aware of possible misuse of their results, and we provide guidance to help avoid such negative impacts on individuals and society.

A systematic review of the use of topic models for short text social media analysis

Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures do not inform whether the topics produced can yield meaningful insights for those examining social media data. Efforts to address this issue, including gauging the alignment between automated and human evaluation tasks, are hampered by a lack of knowledge about how researchers use topic models. Further problems could arise if researchers do not construct topic models optimally or use them in a way that exceeds the models' limitations. These scenarios threaten the validity of topic model development and the insights produced by researchers employing topic modelling as a methodology. However, there is currently a lack of information about how and why topic models are used in applied research. As such, we performed a systematic literature review of 189 articles where topic modelling was used for social media analysis to understand how and why topic models are used for social media analysis. Our results suggest that the development of topic models is not aligned with the needs of those who use them for social media analysis. We have found that researchers use topic models sub-optimally. There is a lack of methodological support for researchers to build and interpret topics. We offer a set of recommendations for topic model researchers to address these problems and bridge the gap between development and applied research on short text topic models.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10462-023-10471-x.

How localized are computational templates? A machine learning approach

A commonly held background assumption about the sciences is that they connect along borders characterized by ontological or explanatory relationships, usually given in the order of mathematics, physics, chemistry, biology, psychology, and the social sciences. Interdisciplinary work, in this picture, arises in the connecting regions of adjacent disciplines. Philosophical research into interdisciplinary model transfer has increasingly complicated this picture by highlighting additional connections orthogonal to it. But most of these works have been done through case studies, which due to their strong focus struggle to provide foundations for claims about large-scale relations between multiple scientific disciplines. As a supplement, in this contribution, we propose to philosophers of science the use of modern science mapping techniques to trace connections between modeling techniques in large literature samples. We explain in detail how these techniques work, and apply them to a large, contemporary, and multidisciplinary data set (n=383.961 articles). Through the comparison of textual to mathematical representations, we suggest formulaic structures that are particularly common among different disciplines and produce first results indicating the general strength and commonality of such relationships.

Wrestling with Social and Behavioral Genomics: Risks, Potential Benefits, and Ethical Responsibility

In this consensus report by a diverse group of academics who conduct and/or are concerned about social and behavioral genomics (SBG) research, the authors recount the often-ugly history of scientific attempts to understand the genetic contributions to human behaviors and social outcomes. They then describe what the current science-including genomewide association studies and polygenic indexes-can and cannot tell us, as well as its risks and potential benefits. They conclude with a discussion of responsible behavior in the context of SBG research. SBG research that compares individuals within a group according to a "sensitive" phenotype requires extra attention to responsible conduct and to responsible communication about the research and its findings. SBG research (1) on sensitive phenotypes that (2) compares two or more groups defined by (a) race, (b) ethnicity, or (c) genetic ancestry (where genetic ancestry could easily be misunderstood as race or ethnicity) requires a compelling justification to be conducted, funded, or published. All authors agree that this justification at least requires a convincing argument that a study's design could yield scientifically valid results; some authors would additionally require the study to have a socially favorable risk-benefit profile.

Genetic determinism, essentialism and reductionism: semantic clarity for contested science

Research linking genetic differences with human social and behavioural phenotypes has long been controversial. Frequently, debates about the ethical, social and legal implications of this area of research centre on questions about whether studies overtly or covertly perpetuate genetic determinism, genetic essentialism and/or genetic reductionism. Given the prominent role of the '-isms' in scientific discourse and criticism, it is important for there to be consensus and clarity about the meaning of these terms. Here, the author integrates scholarship from psychology, genetics and philosophy of science to provide accessible definitions of genetic determinism, genetic reductionism and genetic essentialism. The author provides linguistic and visual examples of determinism, reductionism and essentialism in science and popular culture, discusses common misconceptions and concludes with recommendations for science communication.

Forecasting the publication and citation outcomes of COVID-19 preprints

Many publications on COVID-19 were released on preprint servers such as medRxiv and bioRxiv. It is unknown how reliable these preprints are, and which ones will eventually be published in scientific journals. In this study, we use crowdsourced human forecasts to predict publication outcomes and future citation counts for a sample of 400 preprints with high Altmetric score. Most of these preprints were published within 1 year of upload on a preprint server (70%), with a considerable fraction (45%) appearing in a high-impact journal with a journal impact factor of at least 10. On average, the preprints received 162 citations within the first year. We found that forecasters can predict if preprints will be published after 1 year and if the publishing journal has high impact. Forecasts are also informative with respect to Google Scholar citations within 1 year of upload on a preprint server. For both types of assessment, we found statistically significant positive correlations between forecasts and observed outcomes. While the forecasts can help to provide a preliminary assessment of preprints at a faster pace than traditional peer-review, it remains to be investigated if such an assessment is suited to identify methodological problems in preprints.

Reporting preprints in the media during the COVID-19 pandemic

Preprints have gained prominence in the dissemination of scientific findings. This development has been reinforced by the COVID-19 pandemic, which continues to require the rapid dissemination of new scientific information. However, since preprints usually have not undergone peer review, they lack the rigour of other scientific publications such as journal articles. This presents a challenge for the news media tasked with keeping the public informed about the latest scientific developments in the context of great uncertainty during a global pandemic. This research note investigates the reporting of scientific information from preprints in 80 news articles identified in news articles related to COVID-19 published in four South African online media outlets. Our results show that despite the publication of guidelines for reporting on preprints in the media, there is still a way to go regarding the judicious use of scientific information from preprints by the news media.

The apportionment of citations: a scientometric analysis of Lewontin 1972

'The apportionment of human diversity' (1972) is the most highly cited research article published by geneticist Richard Lewontin in his career. This study's primary result-that most genetic diversity in humans can be accounted for by within-population differences, not between-population differences-along with Lewontin's outspoken, politically charged interpretations thereof, has become foundational to the scientific and cultural discourse pertaining to human genetic variation. The article has an unusual bibliometric trajectory in that it is much more salient in the bibliographic record today compared to the first 20 years after its publication. Here, we highlight four factors that may have played a role in shaping the paper's fame: (i) citations in influential publications across several disciplines; (ii) Lewontin's own popular books and media appearances; (iii) the renaissance of population genetics research of the early 1990s; and (iv) the serendipitous collision of scientific progress, influential books and papers, and heated controversies around the year 1994. We conclude with an analysis of Twitter data to characterize the communities and conversations that continue to keep this study at the centre of discussions about race and genetics, prompting new challenges for scientists who have inherited Lewontin's legacy. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Who tweets climate change papers? investigating publics of research through users’ descriptions

As social issues like climate change become increasingly salient, digital traces left by scholarly documents can be used to assess their reach outside of academia. Our research examine who shared climate change research papers on Twitter by looking at the expressions used in profile descriptions. We categorized users in eight categories (academia, communication, political, professional, personal, organization, bots and publishers) associated to specific expressions. Results indicate how diverse publics may be represented in the communication of scholarly documents on Twitter. Supplementing our word detection analysis with qualitative assessments of the results, we highlight how the presence of unique or multiple categorizations in textual Twitter descriptions provides evidence of the publics of research in specific contexts. Our results show a more substantial communication by academics and organizations for papers published in 2016, whereas the general public comparatively participated more in 2015. Overall, there is significant participation of publics outside of academia in the communication of climate change research articles on Twitter, although the extent to which these publics participate varies between individual papers. This means that papers circulate in specific communities which need to be assessed to understand the reach of research on social media. Furthermore, the flexibility of our method provide means for research assessment that consider the contextuality and plurality of publics involved on Twitter.

Examining linguistic shifts between preprints and publications

Preprints allow researchers to make their findings available to the scientific community before they have undergone peer review. Studies on preprints within bioRxiv have been largely focused on article metadata and how often these preprints are downloaded, cited, published, and discussed online. A missing element that has yet to be examined is the language contained within the bioRxiv preprint repository. We sought to compare and contrast linguistic features within bioRxiv preprints to published biomedical text as a whole as this is an excellent opportunity to examine how peer review changes these documents. The most prevalent features that changed appear to be associated with typesetting and mentions of supporting information sections or additional files. In addition to text comparison, we created document embeddings derived from a preprint-trained word2vec model. We found that these embeddings are able to parse out different scientific approaches and concepts, link unannotated preprint-peer-reviewed article pairs, and identify journals that publish linguistically similar papers to a given preprint. We also used these embeddings to examine factors associated with the time elapsed between the posting of a first preprint and the appearance of a peer-reviewed publication. We found that preprints with more versions posted and more textual changes took longer to publish. Lastly, we constructed a web application (https://greenelab.github.io/preprint-similarity-search/) that allows users to identify which journals and articles that are most linguistically similar to a bioRxiv or medRxiv preprint as well as observe where the preprint would be positioned within a published article landscape.

Preprint articles as a tool for teaching data analysis and scientific communication

The skill of analyzing and interpreting research data is central to the scientific process, yet it is one of the hardest skills for students to master. While instructors can coach students through the analysis of data that they have either generated themselves or obtained from published articles, the burgeoning availability of preprint articles provides a new potential pedagogical tool. We developed a new method in which students use a cognitive apprenticeship model to uncover how experts analyzed a paper and compare the professional's cognitive approach to their own. Specifically, students first critique research data themselves and then identify changes between the preprint and final versions of the paper that were likely the results of peer review. From this activity, students reported diverse insights into the processes of data presentation, peer review, and scientific publishing. Analysis of preprint articles is therefore a valuable new tool to strengthen students' information literacy and understanding of the process of science.

Psychologists update their beliefs about effect sizes after replication studies

Self-correction-a key feature distinguishing science from pseudoscience-requires that scientists update their beliefs in light of new evidence. However, people are often reluctant to change their beliefs. We examined belief updating in action by tracking research psychologists' beliefs in psychological effects before and after the completion of four large-scale replication projects. We found that psychologists did update their beliefs; they updated as much as they predicted they would, but not as much as our Bayesian model suggests they should if they trust the results. We found no evidence that psychologists became more critical of replications when it would have preserved their pre-existing beliefs. We also found no evidence that personal investment or lack of expertise discouraged belief updating, but people higher on intellectual humility updated their beliefs slightly more. Overall, our results suggest that replication studies can contribute to self-correction within psychology, but psychologists may underweight their evidentiary value.

The evolving role of preprints in the dissemination of COVID-19 research and their impact on the science communication landscape

The world continues to face a life-threatening viral pandemic. The virus underlying the Coronavirus Disease 2019 (COVID-19), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has caused over 98 million confirmed cases and 2.2 million deaths since January 2020. Although the most recent respiratory viral pandemic swept the globe only a decade ago, the way science operates and responds to current events has experienced a cultural shift in the interim. The scientific community has responded rapidly to the COVID-19 pandemic, releasing over 125,000 COVID-19-related scientific articles within 10 months of the first confirmed case, of which more than 30,000 were hosted by preprint servers. We focused our analysis on bioRxiv and medRxiv, 2 growing preprint servers for biomedical research, investigating the attributes of COVID-19 preprints, their access and usage rates, as well as characteristics of their propagation on online platforms. Our data provide evidence for increased scientific and public engagement with preprints related to COVID-19 (COVID-19 preprints are accessed more, cited more, and shared more on various online platforms than non-COVID-19 preprints), as well as changes in the use of preprints by journalists and policymakers. We also find evidence for changes in preprinting and publishing behaviour: COVID-19 preprints are shorter and reviewed faster. Our results highlight the unprecedented role of preprints and preprint servers in the dissemination of COVID-19 science and the impact of the pandemic on the scientific communication landscape.