bioRxiv ScienceSearch

bioRxiv · 10.1101/2020.03.06.981589

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

Abstract

Engagement with scientific manuscripts is frequently facilitated by Twitter and other social media platforms. As such, the demographics of a papers social media audience provide a wealth of information about how scholarly research is transmitted, consumed, and interpreted by online communities. By paying attention to public perceptions of their publications, scientists can learn whether their research is stimulating positive scholarly and public thought. They can also become aware of potentially negative patterns of interest from groups that misinterpret their work in harmful ways, either willfully or unintentionally, and devise strategies for altering their messaging to mitigate these impacts. In this study, we collected 331,696 Twitter posts referencing 1,800 highly tweeted bioRxiv preprints and leveraged topic modeling to infer the characteristics of various communities engaging with each preprint on Twitter. We agnostically learned the characteristics of these audience sectors from keywords each users followers provide in their Twitter biographies. We estimate that 96% of the preprints analyzed are dominated by academic audiences on Twitter, suggesting that social media attention does not always correspond to greater public exposure. We further demonstrate how our audience segmentation method can quantify the level of interest from non-specialist audience sectors such as mental health advocates, dog lovers, video game developers, vegans, bitcoin investors, conspiracy theorists, journalists, religious groups, and political constituencies. Surprisingly, we also found that 10% of the highly tweeted preprints analyzed have sizable (>5%) audience sectors that are associated with right-wing white nationalist communities. Although none of these preprints intentionally espouse any right-wing extremist messages, cases exist where extremist appropriation comprises more than 50% of the tweets referencing a given preprint. These results present unique opportunities for improving and contextualizing research evaluation as well as shedding light on the unavoidable challenges of scientific discourse afforded by social media.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Carlson, J., Harris, K.. 2020-03-10. Quantifying and contextualizing the impact of bioRxiv preprints through social media audience segmentation. https://doi.org/10.1101/2020.03.06.981589

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education

Prevalence of scabies and its associated factors among school age children in Arba Minch zuria district, Southern Ethiopia, 2018.

BackgroundScabies, a common human skin disease with a prevalence range of 0.2% to 71.4% in the world. It can have considerable impact on general health leading to illness and death not only through direct effect of its infestation and as a result of secondary bacterial infection. The aim of this study was to assess the prevalence of scabies and its associated factors among school age children in Arba Minch zuria district, Gamo zone, Southern Ethiopia. MethodsA community based cross sectional study was carried out in 845 school age children from February 20 to March 30, 2018. Multi-stage sampling technique was used to select study populations. Logistic regression an analysis was used to identify factors associated with scabies. Findings were presented using 95% CI of Crude Odds Ratios (COR) and Adjusted Odds Ratios (AOR. To declare statistical significance, p-value less than 0.05 was used. ResultA total of 825 children participated in the study with response rate of 97.6%. The overall prevalence of scabies was 16.4% [95% CI: 13.9%, 18.9%]. overcrowding index, family history of itching in the past two weeks, wealth index, knowledge of scabies, climatic zone, frequency of washing body, frequency of washing clothes, finger nails cutting practice, history of skin contact with scabies patient, washing hair more than once weekly, and sharing of clothes were significantly associated scabies disease. ConclusionIn conclusion, the prevalence of scabies in Arba Minch lies at 16.4% in the global scabies range 0.2% to 71.4%. The prevalence was highest in highlands followed by midland and then lowland. This represents a significant scabies burden which we recommend warrants health service intervention. Authors summaryScabies, a common human skin disease with a prevalence range of 0.2% to 71.4% in the world. It can have considerable impact on general health leading to illness and death not only through direct effect of its infestation and as a result of secondary bacterial infection. Conducting a research on this neglected tropical disease would contribute in designing a policies and strategies on prevention and control measures in the study area. Therefore, the aim of this study was to assess the prevalence of scabies and its associated factors among school age children in Arba Minch zuria district, Gamo zone, Southern Ethiopia.

scientific communication and education

Sorry, we're open: Golden Open Access and inequality in the natural sciences

Global Open Access (GOA) journals make research more accessible and therefore more citable; however, the publication fees associated with GOA journals can be costly and therefore not a viable option for many researchers seeking high-impact publication outlets. In this study, I collect metadata from 237 open-access natural science journals and analyze them in terms of Article Processing Charges (APC), Impact Factor (IF), Eigen Factor (EF), citability, and country of publisher. The results of this study provide evidence that with IF, EF, and citability all increase as APC increases, and each of these metrics are higher in publishers from developed countries in comparison to developing countries. Implications of these trends are discussed in regards to natural sciences and inequality within the global scientific community.

scientific communication and education