Design Principles and a Software Reference Architecture for Big Data Question Answering Systems

Companies continuously produce several documents containing valuable information for users. However, querying these documents is challenging, mainly because of the heterogeneity and volume of documents available. In this work, we investigate the challenge of developing a Big Data Question Answering system, i.e., a system that provides a unified, reliable, and accurate way to query documents through naturally asked questions. We define a set of design principles and introduce BigQA, the first software reference architecture to meet these design principles. The architecture consists of high-level layers and is independent of programming language, technology, querying and answering algorithms. BigQA was validated through a pharmaceutical case study managing over 18k documents from Wikipedia articles and FAQ about Coronavirus. The results demonstrated the applicability of BigQA to real-world applications. In addition, we conducted 27 experiments on three open-domain datasets and compared the recall results of the well-established BM25, TF-IDF, and Dense Passage Retriever algorithms to find the most appropriate generic querying algorithm. According to the experiments, BM25 provided the highest overall performance. Copyright © 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

Global utilization of online information for substance use disorder: An infodemiological study of Google and Wikipedia from 2004 to 2022.

INTRODUCTION: The increasing number of people who use drugs (PWUDs) can be attributed to the rising online sales of drugs and other related substances. Information on drugs and drug markets has also become easily accessible in web-search engines and social media. Aside from providing direct care, nurses have essential roles in preventing substance use disorder. These roles include health education, liaison, and researcher. Thus, nurses must examine and utilize the Internet, where information and transactions related to these substances are increasing. DESIGN/METHODS: This study utilized an infodemiological design in exploring the worldwide information utilization for substance use disorder. Data were gathered from Google Trends and Wikimedia Pageview. The data included relative search volumes (RSV), top and rising related queries and topics, and Wikipedia page views between 2004 and 2022. After describing the data, autoregressive integrated mean averaging (ARIMA) models were used to predict future utilization of online information from Google and Wikipedia. RESULTS: Google trends ranked 37 countries based on the search volumes for substance use disorder. Ethiopia, Finland, the United States, Kenya, and Canada have the highest RSVs, while the lowest-ranked country is Turkey, followed by Mexico, Spain, Japan, and Indonesia. Google searches for substance use disorder-related information increased by more than 900% between 2004 and 2022. In addition, Wikipedia page views for substance use disorder-related information increased by almost 200% between 2015 and 2022. Based on the ARIMA models, RSVs and page views are predicted to increase by about 150% and 120% by December 2025. Top and rising search-related topics and queries revealed that the public increasingly utilized online information to understand specific substances and the possible mental health comorbidities related to substance use disorders. Their recent concerns revolved around diagnostics, specific substances, and specific disorders. CONCLUSION: The Internet can be of paradoxical use in substance use disorder. It has been previously reported to be increasingly used in drug trades, contributing to the increasing prevalence of substance use disorder. Likewise, the present study's findings revealed that it is increasingly utilized for substance use disorder-related information. Thus, nurses and other healthcare professionals should ensure that online information regarding substance use disorders is accurate and up-to-date. CLINICAL RELEVANCE: Nurse informaticists can form and lead Internet- and social-media-based health teams that perform national infodemiological investigations to assess online information. In doing so, they can inform, expand, and contextualize ehealth substance use education and strengthen the accessibility and delivery of substance use healthcare. In addition, public health nurses can collaborate to engage patients and communities in identifying harmful substance use disorder information online and creating culturally-appropriate messages that will correct misinformation and improve ehealth literacy, specifically in substance use disorder.

Dungeons and dragons and digital writing: A case study of worldbuilding

Collaborative worldbuilding is an ideal digital writing project for promoting critical thinking about contemporary issues, developing and applying disciplinary expertise writing transfer, and building digital literacies. In the context of the global Covid-19 pandemic where the student experience was characterised by isolation, collaborative worldbuilding also offered a powerful means of building solidarity and community. This paper presents a case study of using collaborative worldbuilding for gaming to achieve key digital writing learning outcomes. The case study shows how this innovative pedagogical approach can be mapped to two key frameworks for information and digital literacies: the Digital Competence Framework for Citizens and the Framework for Information Literacy in Higher Education of the Association of College and Research Libraries. The case study also illustrates how a MediaWiki installation can be used for worldbuilding and as a means of critically introducing students to Wikipedia itself. Qualitative feedback from the students shows that the class achieved its key learning outcomes. More importantly, student engagement during the class and their feedback ascertains that collaborative worldbuilding is a powerful means of building connections and empathy between students in the context of isolation, amid a global pandemic. Practitioner Notes 1. The worldbuilding framework for collaborative writing developed by Trent Hergenrader can be adapted to contribute to the goals of a first-year seminar. However, there are logistical and technical factors to consider. 2. Worldbuilding for gaming is an engaging class activity whether used for online or in-person education. 3. Using a MediaWiki installation as the platform for digital writing is a felicitous means of imparting proficiencies identified by two information literacy frames, the Framework for Information Literacy for Higher Education and the Digital Competence Framework for Citizens. 4. Worldbuilding by authoring encyclopaedic entries on a MediaWiki installation allows for a critical consideration of Wikipedia itself. 5. Genre knowledge is essential to a student's development as a writer. Discussions of knowledge transfer often focus on the ability of students to apply and transfer expertise across disciplines. Speculative fiction writing based on academic research is an example of knowledge transfer between genres. © 2023, University of Wollongong. All rights reserved.

Opening up Minds with Argumentative Dialogues

Recent research on argumentative dialogues has focused on persuading people to take some action, changing their stance on the topic of discussion, or winning debates. In this work, we focus on argumentative dialogues that aim to open up (rather than change) people's minds to help them become more understanding to views that are unfamiliar or in opposition to their own convictions. To this end, we present a dataset of 183 argumentative dialogues about 3 controversial topics: veganism, Brexit and COVID-19 vaccination. The dialogues were collected using the Wizard of Oz approach, where wizards leverage a knowledge-base of arguments to converse with participants. Open-mindedness is measured before and after engaging in the dialogue using a questionnaire from the psychology literature, and success of the dialogue is measured as the change in the participant's stance towards those who hold opinions different to theirs. We evaluate two dialogue models: a Wikipedia-based and an argument-based model. We show that while both models perform closely in terms of opening up minds, the argument-based model is significantly better on other dialogue properties such as engagement and clarity. © 2022 Association for Computational Linguistics.

A spectrum of surveillance: Charting functions of epistemic inequality across EdTech platforms in the post-COVID-19 era

Covid-19 and the public health policies emerging in response have laid bare a multiplicity of issues related to educational access and knowledge equity on a global scale. Among these, the quick shift to online and hybrid education models led teachers to adapt a plethora of digital platforms to deliver content and sponsor interactions). Such platforms range from institutionally sanctioned (and subscribed) Learning Management Systems (LMSs) to software provided by organizations beyond the institution and can pose a threat to student data and privacy. Data surveillance in educational contexts is not a new issue, nor is it only a strictly digital problem. However, the current milieu of constant and continuing public health crises has led to more frequent, uncritical, and hurried adoption of learning technologies. This article challenges professionals in higher education specifically to take a more critical look at the various EdTech platforms they are, have, and will adopt in the post-COVID-19 era, and the spectrum of surveillance such platforms enact. Through a review of common entities such as LMSs, Google Workspace for Education, and Zoom video conferencing software, this article demonstrates how these technologies place both teachers and students in a relationship to data and learning characterised by "epistemic inequality” or "unequal access to learning imposed by private commercial mechanisms''. By taking a closer look at the problematic surveillance functioning across EdTech, this article makes a case for Commons-based Peer Production communities as equitable, open educational alternatives that have resisted market-based neoliberalism and surveillance capitalism. Practitioner Notes 1. The Covid-19 pandemic led to dramatic increases in Edtech adoption at all levels of education. Such adoption was often hurried and uncritical, furthermore. 2. Both traditional Edtech such as Learning Management Systems (LMSs) and more recent educational and communication platforms introduced by "big tech” actors such as Zoom and Google sponsor unethical surveillance and datafication of students, leading to dehumanizing educational models. However, such surveillance exists on a spectrum and LMSs are much less exploitative than "big tech” projects. 3. Educators at all levels, but especially postsecondary, should practice criticality when adopting and using Edtech, and offer students opportunities to better understand issues related to surveillance, privacy, and data extraction. 4. Educators should consider engaging students in more ethical models of digital and non-digital education platforms and projects, such as those offered by Commons-based Peer Production (CBPP) projects like Wikipedia. © 2023, University of Wollongong. All rights reserved.

What's hot and what's not in lay psychology: Wikipedia's most-viewed articles.

We studied views of articles about psychology on 10 language editions of Wikipedia from July 1, 2015, to January 6, 2021. We were most interested in what psychology topics Wikipedia users wanted to read, and how the frequency of views changed during the COVID-19 pandemic and lockdowns. Our results show that the topics of interest to people seeking psychological knowledge changed during the pandemic. In addition, the interests differ noticeably among the languages. We made two important observations. The first was that during the pandemic, people in most countries looked for new ways to manage their stress without resorting to external help. This is understandable, given the increased stress of lockdown and the limited amount of professional help available. We also found that academic topics, typically covered in university classes, experienced a substantial drop in traffic, which could be indicative of issues with remote teaching. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-022-03826-0.

Topic Modeling on News Articles using Latent Dirichlet Allocation

Topic modeling is widely used to obtain the most vis-ible topics from a given text corpus. In this work, a demonstration of the most discussed topic modeling is presented from articles on the Reuters news website. These articles are collected and consequently processed with a Latent Dirichlet Allocation (LDA) unsupervised learning algorithm. The main goal is to build the best model(s) that accurately produces the most discussed topics. Such a model(s) can be used in real life to instantly get information about actual news to classify documents in a given dataset and extract dominated topics with their keywords. This helps to build, for example, correlations with user preferences and recommend interesting content. There are works which use different models to evaluate texts and obtain statistics about them, such as the most popular people's opinions about some question or to obtain popular and dominating subtopics of the specific topic dataset (e.g., medicine articles). As a result of the work, we were able to create a generic LDA model, trained on Wikipedia articles. The model successfully analyzes Reuters articles and extracted their topics as keyword sets. Then, they can be used to recommend content that is interesting to the target user, for example, based on the recommended content tags. © 2022 IEEE.

When public administration education switches online: Student perceptions during COVID-19

Public administration education is traditionally known for its emphasis on interaction, discussion and experiential learning, which require effective in-person instructions. With COVID-19 pushing many programmes across the globe to be delivered online rather than in person, how this shift has affected the student experience in public administration programmes has been a pertinent and important consideration. This paper addresses the question through two surveys of 147 students in total, at a graduate-level public policy school in Singapore. Two distinctive waves of data collection allow us to capture a nuanced picture of student perceptions both when online teaching was introduced as an emergency response and when it was planned as a deliberate strategy later on. Our findings suggest that students consistently reported a decline in participation and interaction in an online setting, compared with a face-to-face setting. Our study fills a critical gap in the literature related to online public administration education in Asia, while the immediate constraints it highlights and lessons it offers on maintaining a highly interactive and engaging public administration education are likely to apply for educators elsewhere both during and beyond the COVID-19 era.

Fostering college students' fact-checking skills: Three studies assessing lateral reading instruction in a general education course

While online information is abundant and easily accessible, its quality varies widely. Fact-checkers evaluate online information by reading laterally, i.e., opening a new browser tab to research sources and verify claims. This dissertation consisted of three studies that used course outcomes assessment data to examine the impact of a lateral reading curriculum on college students' fact-checking skills. The curriculum was first implemented in Fall 2018 as part of a general education civics course. It has been taught every semester since then, though the content and format of implementation have changed. Data used in the current studies were collected during the Fall 2018, Fall 2019, and Fall 2020 semesters.The Fall 2018 study used a pre/posttest control-group design to evaluate an in-person implementation of a curriculum teaching students four fact-checking "moves". Students who received the curriculum were more likely to read laterally and accurately assess the trustworthiness of online content at posttest than controls. They also reported greater use of Wikipedia at posttest than controls, but did not show significantly greater trust in Wikipedia. Students in the curriculum condition that read laterally on at least one problem at posttest completed more online assignments reviewing lateral reading strategies than their peers. Across conditions, students demonstrated high general media literacy knowledge, but this was unrelated to responsiveness to the curriculum.The Fall 2019 study used a pre/post control-group design to evaluate an asynchronous, online version of the curriculum which taught students a revised set of fact-checking moves summarized by the acronym "SIFT". Students who received the curriculum were more likely to read laterally and were more aware of lateral reading strategies at posttest than controls. Students who used lateral reading strategies during the curriculum had higher reading comprehension and better posttest outcomes. Use and awareness of lateral reading were unrelated at pretest. At posttest, use and awareness were weakly correlated, while reading comprehension was moderately correlated with awareness. Awareness of lateral reading strategies fully mediated the effect of reading comprehension on use of lateral reading at posttest.Lastly, given the proliferation of false and misleading information surrounding the COVID-19 pandemic, the Fall 2020 study assessed how gains in lateral reading from the asynchronous, online SIFT curriculum related to students' confidence in their ability to fact-check COVID-19-related news. Students made gains in their use of lateral reading from pretest to posttest, with both reading comprehension and assignment completion significantly predicting use. Students also made gains in their confidence in fact-checking COVID-19-related news, as well their use, endorsement, and knowledge of Wikipedia. At posttest, use of lateral reading was only weakly correlated with fact-checking confidence.The three studies in this dissertation add to the growing literature documenting both the dearth of lateral reading skills among college students and the efficacy of educational interventions for increasing students' use of these skills. While findings are encouraging, students' gains were also modest. These studies identify factors that may explain individual differences in students' use of lateral reading after instruction, including awareness of lateral reading strategies, attitudes, use, and knowledge of Wikipedia, and reading comprehension. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Text Analysis of Evolving Emotions and Sentiments in COVID-19 Twitter Communication.

Scientists and regular citizens alike search for ways to manage the widespread effects of the COVID-19 pandemic. While scientists are busy in their labs, other citizens often turn to online sources to report their experiences and concerns and to seek and share knowledge of the virus. The text generated by those users in online social media platforms can provide valuable insights about evolving users' opinions and attitudes. The objective of this research is to analyze text of such user disclosures to study human communication during a pandemic in four primary ways. First, we analyze Twitter tweet information, generated throughout the pandemic, to understand users' communications concerning COVID-19 and how those communications have evolved during the pandemic. Second, we analyze linguistic sentiment concepts (analytic, authentic, clout, and tone concepts) in different Twitter settings (sentiment in tweets with pictures or no pictures and tweets versus retweets). Third, we investigate the relationship between Twitter tweets with additional forms of internet activity, namely, Google searches and Wikipedia page views. Finally, we create and use a dictionary of specific COVID-19-related concepts (e.g., symptom of lost taste) to assess how the use of those concepts in tweets are related to the spread of information and the resulting influence of Twitter users. The analysis showed a surprisingly lack of emotion in the initial phases of the pandemic as people were information seeking. As time progressed, there were more expressions of sentiment, including anger. Further, tweets with and without pictures and/or video had statistically significant differences in text sentiment characteristics. Similarly, there were differences between the sentiment in tweets and retweets and tweets. We also found that Google and Wikipedia searches were predictive of sentiment in the tweets. Finally, a variable representing a dictionary of COVID-related concepts was statistically significant when related to users' Twitter influence score and number of retweets, illustrating the general impact of COVID-19 on Twitter and human communication. Overall, the results provide insights into human communication as well as models of human internet and social media use. These findings could be useful for the management of global challenges beyond, or different from, a pandemic.

An Exploration of Wikipedia Contributions in the Era of COVID-19

With the declaration of COVID-19 as a pandemic by the World Health Organization and associated public health concerns and emergency measures, the lives of many came to a grinding halt. Whether due to stay-at-home orders and lockdowns, or quarantines, many were required to change their day-to-day way of life overnight. This not only changed the mechanical activities performed daily, such as driving to the office, going out to a restaurant, or attending a party, but this also changed the resultant implications of the utility we received from those activities. Utility theory posits that individuals choose what activities to perform based on some utility function, where the utility satisfies some need. As these activities to meet existing needs were disrupted, we seek to use this as an opportunity to explore how contribution in open-source communities changed, specifically the English Wikipedia. We utilize a natural experiment methodology, centered around the COVID-19 pandemic, and explore contribution patterns before and after the pandemic. Our project will contribute to the understanding of IS during unusual times, specifically in the context of open source communities that rely on volunteer time and effort

The role of Wikipedia in the dissemination of new knowledge: Analysis of the entry desinformación as a changeable concept

The main goal of Wikipedia’s founders, Jimmy Wales and Larry Sanger, was to create a collaborative encyclopaedia driven by the users of the internet who, on a nonprofit basis, would compile and share all human wisdom and knowledge. In times of crisis, such as the coronavirus pandemic, Wikipedia has emerged as a reference point for users around the world. In this vein, Wikipedia once again highlighted its cultural role in the production of available knowledge in the face of new knowledge. Therefore, the main objective of this study is to analyse the specific entry of desinformación –disinformation in English– in the Spanish version of Wikipedia, given the importance that this concept has acquired during the coronavirus crisis and given the need to disseminate a homogeneous definition of this term. For that purpose, we have applied the content analysis method to a textual case, that is, to the disinformation entry in Wikipedia. The main results show that the basic characteristics of the Spanish entry of desinformación on Wikipedia are not the suitable ones to inform users or readers of the real meaning of this concept. Furthermore, the content of the Wikipedia disinformation entry is incomplete, disjointed and of dubious reliability. Therefore, this research advocates the creation of a homogeneous definition that permeates the common imaginary and that is the result of a combination of experts’ opinions and the definitions proposed by institutions, governments, media and organizations. (English) [ FROM AUTHOR] El principal objetivo de los fundadores de Wikipedia, Jimmy Wales y Larry Sanger, era crear una enciclopedia colaborativa impulsada por los usuarios de internet que, sin ánimo de lucro, recopilara y compartiera toda la sabiduría y el conocimiento humanos. En tiempos de crisis, como la pandemia de coronavirus, Wikipedia se ha convertido en un punto de referencia para los usuarios de todo el mundo. En este sentido, Wikipedia volvió a poner de manifiesto su papel cultural en la producción de conocimiento disponible frente a los nuevos conocimientos. Por ello, el objetivo principal de este estudio es analizar la entrada específica desinformación en Wikipedia, dada la importancia que este concepto ha adquirido durante la crisis del coronavirus y ante la necesidad de difundir una definición homogénea sobre este término. Para ello se ha aplicado el método de análisis de contenido de un caso textual, es decir, de la entrada sobre desinformación en la versión en español de Wikipedia. Los principales resultados muestran que las características básicas de la entrada desinformación en Wikipedia no son las más adecuadas para que cualquier usuario o lector esté bien informado sobre el significado real de este concepto. Además, el contenido de la citada entrada es incompleto, inconexo y de dudosa fiabilidad. Por ello, esta investigación aboga por crear una definición homogénea que impregne el imaginario común y que sea el resultado de una combinación entre lo que dicen los expertos y lo que proponen instituciones, gobiernos, medios de comunicación y organizaciones. (Spanish) [ FROM AUTHOR] Copyright of Communication & Society is the property of Servicio de Publicaciones de la Universidad de Navarra, S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

COVID-19 and the social organization of knowledge in Wikipedia: a study of social representations

PurposeThe paper aims to present the development of conceptualization of coronavirus disease 2019 (COVID-19) based on associations with other articles on English edition of Wikipedia. The main goal of the paper is to study the social organization of knowledge about COVID-19 within the Wikipedia community of practice.Design/methodology/approachThe methodological approach taken in this study was based on the application of Moscovici's theory of social representations to Wikipedia's knowledge organization system (KOS). Internal links in the Wikipedia article about COVID-19 were considered anchors in its social representations. Each link in the introductory part of the article was considered an indicator of the semantic relationship between COVID-19 and other concepts from Wikipedia's knowledge base. The subject of this study was links extracted from all revisions of the COVID-19 article between February and September 2020. Qualitative and quantitative analyses were performed on these conceptual structures using both synchronic and diachronic approaches.FindingsIt was found that the evolution of anchors in the Wikipedia article on COVID-19 was in line with the mechanism of symbolic coping related to infectious disease. It went through stages of divergence, convergence and normalization. It shows that this mechanism governs the social organization of knowledge related to COVID-19 on Wikipedia.Originality/valueNo studies have been devoted to the image of COVID-19 as presented by the evolution of links in Wikipedia and its implications for knowledge organization (KO).

Effects of COVID-Induced Public Anxiety on European Stock Markets: Evidence From a Fear-Based Algorithmic Trading System.

The effect of COVID-induced public anxiety on stock markets, particularly in European stock market returns, is examined in this research. The search volumes for the notion of COVID-19 gathered by Google Trends and Wikipedia were used as proxies for COVID-induced public anxiety. COVID-induced public anxiety was shown to be linked with negative returns in European stock markets when a panel data method was used to a sample of data from 14 European stock markets from January 2, 2020 to September 17, 2020. Using an automated trading system, we used this finding to suggest investment methods based on COVID-induced anxiety. The findings of back-testing indicate that these techniques have the potential to generate exceptional profits. These results have significant consequences for government officials, the media, and investors.

Citation needed? Wikipedia bibliometrics during the first wave of the COVID-19 pandemic.

BACKGROUND: With the COVID-19 pandemic's outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic," ensuring the quality of information is a crucial vector of public health. Investigating whether and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked which sources informed Wikipedia's COVID-19-related articles before and during the pandemic's first wave (January-May 2020). RESULTS: We found that coronavirus-related articles referenced trusted media outlets and high-quality academic sources. Regarding academic sources, Wikipedia was found to be highly selective in terms of what science was cited. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English-language COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how pre-existing articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Last, we constructed a network of DOI-Wikipedia articles, which showed the landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 drug development. CONCLUSIONS: Understanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists," it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts.

Enabling a Question-Answering System for COVID Using a Hybrid Approach Based on Wikipedia and Q/A Pairs

The research on COVID-19 disease has produced much information, but there are more questions than certainty. This proposal aims to contribute by providing reliable and updated answers to questions aimed at the general public. To achieve this goal, we design a question-answering architecture that leverages two information sources of different nature, controlled-official and open-collaborative. Thus, the system can answer several questions that the community may have about COVID. During the experimentation, we found that thanks to knowledge graphs, information retrieval, and NLP methods, the system can provide explainable answers;i.e., they obtain direct answers and can browse into enriched responses. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Wikipedia, Google Trends and Diet: Assessment of Temporal Trends in the Internet Users' Searches in Italy before and during COVID-19 Pandemic.

We obtained data from Google Trends and Wikipedia in order to assess whether an analysis of Internet searches could provide information on the Internet users' behaviour/interest in diets. Differences in seasonality, year and before/during COVID-19 pandemic were assessed. From Wikipedia, we extracted the number of times a page is viewed by users, aggregated on monthly and seasonal bases. We also used Google Trends to evaluate the frequency of the users' web searches. The Mediterranean diet was the most frequently (33.9%), followed by the pescatarian diet (9.0%). Statistically, significant seasonal differences were found for the Mediterranean, vegetarian, Atkins, Scarsdale, and zone diets and pescetarianism. The most commonly searched diet and consequent diet-related queries on Google resulted to be: Dukan diet, Dukan and weight loss. Ketogenic, FODMAP and intermittent fasting diets were statistically more frequently searched during the pandemic compared with before. Our data show a different trend of searches based on the seasonality, year and the pandemic. These data could be useful for scientists, practitioners and policy makers because they can inform educational campaigns via the Internet, especially in periods when the population is more receptive.

Writing for Wikipedia: An Exercise in Microbiology, Writing, Research, Communication, and Public Service.

The COVID-19 pandemic has had a tremendous impact on how postsecondary education was and is delivered. Educators were forced to rapidly move their instruction online and find new and innovative ways to convey content, stimulate student engagement, and satisfy curricular requirements. The purpose of this article is to describe the use of a Wikipedia writing assignment in Veterinary Bacteriology and Mycology, a second-year course in the Doctor of Veterinary Medicine (DVM) curriculum at the University of Saskatchewan. Students had the opportunity to write and edit incomplete articles on topics related to course content. In addition to deep exploration of a topic, this fostered in students the development of research and communication skills, which have been articulated as core competencies in veterinary programs.

COVID-19, media coverage of bats and related Web searches: a turning point for bat conservation?

SARS-CoV-2, the virus that caused the COVID-19 pandemic, is genomically similar to a SARS-like beta-coronavirus found in Asian rhinolophid bats. This evolutionary relationship impressed the global media, which then emphasised bats as key actors in the spillover that resulted in the pandemic. In this study, we highlight changes in the traditional and new media coverage of bats and in Internet search volumes that occurred since the beginning of the COVID-19 pandemic in 2020.We analysed Google and Wikipedia searches for bats and coronaviruses in 21 countries and eight languages, as well as television broadcasts in the USA, some of which have global coverage, between January 2016 and December 2020. In January 2020, the amount of television news about bats boomed, and news associated with the term 'bat' shifted to COVID-19-related topics. A nearly identical pattern was observed in Google searches during 2020 at the global scale. The daily time series of television coverage and Internet search volumes on bats and coronavirus in the USA covaried in the first quarter of 2020, in line with the existence of a media bubble. Time-series analysis revealed that both the Google Trends index and visits to Wikipedia pages about bats boomed in early 2020, despite the fact that this time of year is usually characterised by low search volumes.Media coverage emphasised, correctly or not, the role of bats in the COVID-19 pandemic and amplified public interest in bats worldwide. The public image of these mammals, in many cases threatened and important ecosystem service providers, was seriously compromised. We therefore recommend that policymakers and journalists prioritise scientifically accurate communication campaigns about bats, which would help counteract the surge in bat persecution, and leverage interest towards positive human-bat interactions.

SARS­CoV­2, el virus causante de la pandemia COVID­19, es genómicamente símil al SARS­tipo beta­coronavirus encontrado en los murciélagos rinolófidos asiáticos. Esta relación evolutiva impresionó a los medios mundialmente, hasta tal punto que se ha enfatizado el papel de los murciélagos como uno de los principales vectores en la expansión de la pandemia. En este estudio, se resaltan los cambios producidos en la percepción de los murciélagos por los medios de comunicación (nuevos y tradicionales), y en las búsquedas en Internet que ocurrieron desde el inicio de la pandemia COVID­19 en 2020.Para ello se han analizado las búsquedas del término 'murciélago' en Google y Wikipedia en 21 países y ocho lenguas, así como las retransmisiones televisivas en EE.UU. (algunas de las cuales con cobertura global) entre enero 2016 y diciembre 2020. En enero 2020, la cantidad de noticias televisadas sobre murciélagos se disparó, y el número de noticias previamente asociadas con el término 'murciélago' cambiaron por temáticas relacionadas con el COVID­19. Un patrón idéntico puede ser observado a escala global en las búsquedas de Google durante el 2020. La serie temporal de cobertura televisiva y búsquedas en internet sobre murciélagos y coronavirus en EE.UU. covaría durante el primer cuarto del 2020, en líneo con la existencia de la burbuja mediática. El análisis de la cobertura diaria televisiva revela que tanto el índice Google Trend como las visitas a páginas de Wikipedia sobre murciélagos incrementaron al comienzo del 2020, a pesar de que esta época del año suele caracterizarse por bajos volúmenes de búsqueda.La cobertura mediática enfatizó, correctamente o no, el papel de los murciélagos en la propagación de la pandemia COVID­19, ampliando el interés público a lo largo del globo. La imagen pública de estos mamíferos, en muchos casos especies amenazadas o proveedoras de importantes funciones ecosistémicas, ha sido seriamente comprometida. Por lo tanto, se recomienda a periodistas y responsables políticos la priorización de campañas de comunicación científicamente fundamentadas que ayuden a contrarrestar este aumento en la persecución de los murciélagos aprovechando el interés actual para concienciar al público de sus interacciones positivas con el hombre.

Public Interest in Neurological Diseases on Wikipedia during Coronavirus Disease (COVID-19) Pandemic.

Infodemiology is a research discipline that investigates parameters of information distribution in order to support public health and public policy. Wikipedia, a free online encyclopedia, is commonly used as a source of information for infodemiological studies. Using Pageviews analysis, we descriptively assessed the total monthly number of views of the Wikipedia articles in English describing main neurological diseases in the period from January 2018 to July 2020. Our results show a general trend of a decrease in interest in neurological disease-related pages throughout years and especially during the burst of interest towards coronavirus. The monitoring of infodemiological indicators shall be prioritized to reshape global campaigns and tailored advocacy programs.