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We propose to use Twitter data as social-spatial sensors. This study deals with the question whether research papers on certain diseases are perceived by people in regions (worldwide) that are especially concerned by these diseases. Since (some) Twitter data contain location information, it is possible to spatially map the activity of Twitter users referring to certain papers (e.g., dealing with tuberculosis). The resulting maps reveal whether heavy activity on Twitter is correlated with large numbers of people having certain diseases. In this study, we focus on tuberculosis, human immunodeficiency virus (HIV), and malaria, since the World Health Organization ranks these diseases as the top three causes of death worldwide by a single infectious agent. The results of the social-spatial Twitter maps (and additionally performed regression models) reveal the usefulness of the proposed sensor approach. One receives an impression of how research papers on the diseases have been perceived by people in regions that are especially concerned by these diseases. Our study demonstrates a promising approach for using Twitter data for research evaluation purposes beyond simple counting of tweets., Competing Interests: The authors have declared that no competing interests exist.

Objective: The objective of this study was to examine the correlation between Twitter mentions and the number of academic citations of radiation oncology articles., Materials and Methods: We reviewed all 178 clinical manuscripts of the 2 most important radiation oncology journals and "Brachytherapy," and all clinical manuscripts relating to radiation oncology from the top 10 impact factor oncology journals, published between January and February 2018. We collected the record of citations utilizing Scopus and Google Scholar platforms and the number of times an article was tweeted about using the "Altmetric Bookmarklet." χ test was used to compare distributions between groups and the Pearson coefficient was used for correlations between the Twitter metrics and academic citations., Results: Overall, 71% of all articles were tweeted about at least once. There was a significant correlation between the number of tweets and the number of citations in Google Scholar (r=0.55, P<0.001) and in Scopus (r=0.59, P<0.001). The 11% of articles with a prepublication Twitter "buzz" (defined as an article with ≥10 tweets before publication) had 3.6 times more citations in Scopus (mean: 14.8 vs. 4.2, P<0.001) and 2.9 times more citations in Google Scholar (17.8 vs. 6.0, P<0.001) when compared with papers with no "buzz.", Conclusions: Presence on Twitter was correlated with the number of academic citations of an article in radiation oncology. This suggests that Twitter is being utilized by the oncology community as a platform to discuss and disseminate high impact scientific articles. The correlation between Twitter and increasing the number of citations of an article through larger dissemination and exposure requires further studies.

This paper reports a study coauthored with second-year undergraduate students that examines student experiences of undertaking real-life, client-set marketing assessments with an equality and inclusion remit. Students were set a marketing assessment with an explicit social justice focus, thereby prompting them to reflect on their own backgrounds and unconscious biases whilst addressing issues of societal injustice. This study explores the impact on students of closely engaging with this material and how the assessment, which involved them interviewing experts and developing actionable recommendations, altered their views and career plans. Data were generated via focus groups with students who undertook the assessment, supplemented by some alumni and client interviews. The findings are presented as a "3A" framework of Awareness, Application, and Action: first, the assessment raised "Awareness" of broader societal issues and fostered transformation in terms of personal views; second, students developed core skills and networks they could "Apply" in their future careers; and third, "Action" describes the way students felt empowered to make a positive difference to their client and wider society. The 3A model provides simple design principles that educators could implement if they want to introduce transformational experiences based on social justice issues into the marketing curriculum.

The notable increase in retraction papers has attracted considerable attention from diverse stakeholders. Various sources are now offering information related to research integrity, including concerns voiced on social media, disclosed lists of paper mills, and retraction notices accessible through journal websites. However, despite the availability of such resources, there remains a lack of a unified platform to consolidate this information, thereby hindering efficient searching and cross-referencing. Thus, it is imperative to develop a comprehensive platform for retracted papers and related concerns. This article aims to introduce "Amend," a platform designed to integrate information on research integrity from diverse sources. The Amend platform consolidates concerns and lists of problematic articles sourced from social media platforms (e.g., PubPeer, For Better Science), retraction notices from journal websites, and citation databases (e.g., Web of Science, CrossRef). Moreover, Amend includes investigation and punishment announcements released by administrative agencies (e.g., NSFC, MOE, MOST, CAS). Each related paper is marked and can be traced back to its information source via a provided link. Furthermore, the Amend database incorporates various attributes of retracted articles, including citation topics, funding details, open access status, and more. The reasons for retraction are identified and classified as either academic misconduct or honest errors, with detailed subcategories provided for further clarity. Within the Amend platform, a total of 32,515 retracted papers indexed in SCI, SSCI, and ESCI between 1980 and 2023 were identified. Of these, 26,620 (81.87%) were associated with academic misconduct. The retraction rate stands at 6.64 per 10,000 articles. Notably, the retraction rate for non-gold open access articles significantly differs from that for gold open access articles, with this disparity progressively widening over the years. Furthermore, the reasons for retractions have shifted from traditional individual behaviors like falsification, fabrication, plagiarism, and duplication to more organized large-scale fraudulent practices, including Paper Mills, Fake Peer-review, and Artificial Intelligence Generated Content (AIGC). The Amend platform may not fully capture all retracted and concerning papers, thereby impacting its comprehensiveness. Additionally, inaccuracies in retraction notices may lead to errors in tagged reasons. Amend provides an integrated platform for stakeholders to enhance monitoring, analysis, and research on academic misconduct issues. Ultimately, the Amend database can contribute to upholding scientific integrity. This study introduces a globally integrated platform for retracted and concerning papers, along with a preliminary analysis of the evolutionary trends in retracted papers. [ABSTRACT FROM AUTHOR]

Background: Social media (SM) have altered the way we live and, for many, the way we die. The information available on even the rarest conditions is vast. Free from restrictions of mobility, time and distance, SM provides a space for people to share experiences of illness, death and dying, and potentially benefit from the emotional and practical support of others n similar positions. The communications that take place in these spaces also create large amounts of 'data' which, for any research centre, cannot be ignored. However, for a palliative care research centre the use of this 'data' comes with specific ethical dilemmas., Methods: This paper details the process that we, as a research, went through in constructing a set of ethical guidelines by which to work. This involved conducting two consensus days; one with researchers from within the centre, and one with the inclusion of external researchers with a specific interest in SM., Results: The primary themes that emerged from the consensus meetings includes; SM as a public or private space; the status of open and closed groups; the use of historical data; recruiting participants and obtaining informed consent and problems of anonymity associated with dissemination., Conclusions: These are the themes that this paper will focus on prior to setting out the guidelines that we subsequently constructed., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Aims: A discussion of methodological issues and social media recruitment to a feasibility study to investigate mHealth resources for asthma and pregnancy care., Background: Pregnant women with asthma are reported to be poorly supported according to an international research. We sought to establish if a mHealth intervention might be feasible and acceptable to them., Design: A Phase I or modelling study., Methods: A project team designed an intervention to address UK national guidelines for the management of asthma during pregnancy, using other resources already accessible on the web. This was made available on a project website optimized for mobile phone usage. Links were Tweeted and advertised on Facebook, asking participants to access the project website, which included links to the resources and before- and after-use questionnaires to establish baseline symptom data and participant views of the resources., Results: Despite 55,700 Twitter impressions in a 76-day period over winter 2016-2017, this recruitment strategy garnered 402 engagements but only seven respondents for questionnaire 1 and zero respondents for questionnaire 2., Conclusions: We could not recruit to this study despite believing that social media recruitment would be effective and we recommend that social media recruitment be used cautiously. Apparently, we did not sufficiently address the theoretical aspects of communications theory and were not clear enough about our key messages. Publication bias may exist about the non-publication of other failed telemedicine studies using social media; this goes largely unreported in some systematic reviews and may influence researchers' decision-making about social media recruitment., (© 2018 John Wiley & Sons Ltd.)

In an era overwhelmed by academic big data, students grapple with identifying academic papers that resonate with their learning objectives and research interests, due to the sheer volume and complexity of available information. This study addresses the challenge by proposing a novel academic paper recommendation system designed to enhance personalized learning through the nuanced understanding of academic social networks. Utilizing the theory of social homogeneity, the research first constructs a sophisticated academic social network, capturing high-order social relationships, such as co-authorship and advisor–advisee connections, through hypergraph modeling and advanced network representation learning techniques. The methodology encompasses the development and integration of a hypergraph convolutional neural network and a contrastive learning framework to accurately model and recommend academic papers, focusing on aligning with students' unique preferences and reducing reliance on sparse interaction data. The findings, validated across multiple real-world datasets, demonstrate a significant improvement in recommendation accuracy, particularly in addressing the cold-start problem and effectively mapping advisor–advisee relationships. The study concludes that leveraging complex academic social networks can substantially enhance the personalization and precision of academic paper recommendations, offering a promising avenue for addressing the challenges of academic information overload and fostering more effective personalized learning environments. [ABSTRACT FROM AUTHOR]

Conservative activism around the purported influence of Critical Race Theory (CRT) on K-12 education has swept the country in recent years. While others have documented the sources of these messages, how school districts have responded to these critiques has not yet been investigated. Drawing on research on how social media algorithms elevate polarizing information and activate emotions, we analyze public social media posts on school/district Facebook pages mentioning the phrase "critical race" to examine how educators address the claim of teaching CRT and how the local community responds. We use sentiment analysis to examine the emotions of these posts and how they are distributed across states. We also explore the sentiment of subsequent community reactions reflected in the comments of each post, including negative emotions such as anger and fear, and positive emotions such as trust. This study has implications for how school districts can help to stop cycles of fearful rhetoric and engage with stakeholders in ways that unite a school community around shared priorities.