Collaborating neuroscience online: The case of the Human Brain Project forum

PLOS ONE RESEARCH ARTICLE Collaborating neuroscience online: The case of the Human Brain Project forum Ann-Christin Kreyer ID1,2☯*, Lucy Xiaolu Wang ID1,3,4☯ 1 Max Planck Institute for Innovation and Competition, München, Germany, 2 Munich Graduate School of Economics, Ludwig-Maximilians-University Munich, München, Germany, 3 Department of Resource Economics, University of Massachusetts, Amherst, Massachusetts, United States of America, 4 Canadian Centre for Health Economics, University of Toronto, Toronto, Ontario, Canada a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Kreyer A-C, Wang LX (2022) Collaborating neuroscience online: The case of the Human Brain Project forum. PLoS ONE 17(12): e0278402. https://doi.org/10.1371/journal. pone.0278402 Editor: Onur Varol, Sabanci University: Sabanci Universitesi, TURKEY Received: July 21, 2022 Accepted: November 16, 2022 Published: December 7, 2022 Copyright: © 2022 Kreyer, Wang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: A stable, public GitHub repository hosted at the Max Planck Institute for Innovation and Competition has been created. This repository contains the minimal anonymized dataset and corresponding code necessary to replicate our study findings. The link to the repository is: https://github.com/maxplanck-innovation-competition/HBP_Forum. Funding: The authors received no specific funding for this work. Competing interests: The authors have declared that no competing interests exist. ☯ These authors contributed equally to this work. * Abstract This paper analyzes user interactions on the public-access online forum of the Human Brain Project (HBP), a major European Union-funded neuroscience research initiative, to understand the utility of the Forum for collaborative problem solving. We construct novel data using discussion forum posts and detailed user profiles on the HBP Forum. We find that HBP Forum utilization is comparable to that of a leading general-interest coding platform, and that online usage metrics quickly recovered after an initial Covid-19-related dip. Regression results show that user interactions on the Forum are more active for questions on programming and in HBP core areas. Further, Cox proportional hazard analyses show that such problems are solved faster. Forum posts with users from different countries tend to be discussed more actively but solved slower. Higher shares of administrator support tend to solve problems faster. There are no clear patterns regarding gender and seniority. Our results suggest that building novel collaborative forums can support researchers working on complex topics in challenging times. 1. Introduction Neurological disorders are the leading cause of disability and the second leading cause of death worldwide, accounting for 9 million deaths (16.5% of total global deaths) and the loss of 276 million disability-adjusted life years in 2016 [1]. Most brain diseases have no cure, and many existing treatments are very expensive. Meanwhile, there is growing public and private investment in artificial intelligence (AI) for health care projects, with health care being the most invested sector by AI investors [2]. Although many life science areas, including neuroscience, are traditionally more laboratory- and experimentally-based, both Covid-19 and the massive global cost of neurological diseases heighten the need to harness digitization in upstream health care markets. Since 2013, there have been different brain science initiatives launched in Europe, US, Israel, Japan, and China [3] as well as an emerging international brain initiative [4], leading to a burgeoning “brain race” [5]. PLOS ONE | https://doi.org/10.1371/journal.pone.0278402 December 7, 2022 1 / 16 PLOS ONE Collaborating neuroscience online: The case of the Human Brain Project forum This paper studies the public-access online forum of one of the earliest brain initiatives, the Human Brain Project (HBP). Launched in 10/2013, the HBP is a flagship science initiative in the European Commission’s Future and Emerging Technologies program and recipient of a 10-year, €1 billion grant. The HBP aims to advance brain research and improve treatments for neurological diseases by merging neuroscience with information and communication technology (ICT) including computational science, robotics, and artificial intelligence [6]. As of 2021, a total of 179 institutions from over 20 countries had participated in the HBP. As well as making grants to research partners, the HBP allocates resources to build digital platforms, including a public-access online HBP Forum. As a major public discussion channel of the HBP, the utilization and collaborative problem-solving on the HBP Forum offers a valuable case study of institutional design to facilitate scientific collaboration. We construct a novel dataset to examine whether and to what extent the HBP Forum is actively used, what factors are tied with richer online user interactions, and whether the HBP Forum offers an effective platform for problem-solving. We collected data from public sources to capture all user interactions and discussion content on the HBP Forum as well as characteristics of forum user profiles (e.g., demographics, institutions, scientific areas). We categorize the discussion threads based on the nature of topics, and further identify whether, when, and by whom a question has been solved. Data reveal that the HBP Forum is well-utilized and remains resilient during Covid-19, reflected in both the extensive margin of usage and intensive margin of user interactions. With the novel data constructed, this paper offers the first systematic empirical analyses of the utilization and performance of the HBP Forum. We employ regression analyses to investigate what factors are associated with richer user interactions measured by the numbers of user replies per post within a quarter. We analyze covariates related to the content of discussed topics, the technical aspects, and the demographic and institutional profile of users who post the initial questions and users who reply. We further create a content-based measure of whether and when each question raised is solved effectively. We define a post as solved effectively if the asking user confirms the proposed solution; when direct confirmation is not available, we label the solution status based on the content and co-users’ confirmation. We then utilize Cox proportional hazard models to analyze the time taken to solve a posted problem and covariates that accelerate problem-solving. We find that questions closely tied with HBP platforms and questions on programming issues with a higher share of explicit code in communications generate more discussions, especially when (...truncated)