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Gisela Redondo-Sama

Bio: Gisela Redondo-Sama is an academic researcher from University of Deusto. The author has contributed to research in topics: Social media & Social impact assessment. The author has an hindex of 9, co-authored 16 publications receiving 443 citations. Previous affiliations of Gisela Redondo-Sama include University of Zaragoza & University of Cambridge.

Papers
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Journal ArticleDOI
TL;DR: Analysis of the type of tweets that circulated on Twitter around the COVID-19 outbreak for two days, in order to analyze how false and true information was shared, shows that false information is tweeted more but retweeted less than science-based evidence or fact-checking tweets, while science- based evidence and fact- checking tweets capture more engagement than mere facts.
Abstract: The World Health Organization has not only signaled the health risks of COVID-19, but also labeled the situation as infodemic, due to the amount of information, true and false, circulating around t...

283 citations

Journal ArticleDOI
TL;DR: The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and deliberation contexts promoted in social media overcome false information about health.
Abstract: One of the challenges today is to face fake news (false information) in health due to its potential impact on people's lives. This article contributes to a new application of social impact in social media (SISM) methodology. This study focuses on the social impact of the research to identify what type of health information is false and what type of information is evidence of the social impact shared in social media. The analysis of social media includes Reddit, Facebook, and Twitter. This analysis contributes to identifying how interactions in these forms of social media depend on the type of information shared. The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and finally, deliberation contexts promoted in social media overcome false information about health. These results contribute to advancing knowledge in overcoming fake health-related news shared in social media.

119 citations

Journal ArticleDOI
29 Aug 2018-PLOS ONE
TL;DR: The social impact coverage ratio (SICOR) is defined to identify the percentage of tweets and Facebook posts providing information about potential or actual social impact in relation to the total amount of social media data found related to specific research projects.
Abstract: The social impact of research has usually been analysed through the scientific outcomes produced under the auspices of the research. The growth of scholarly content in social media and the use of altmetrics by researchers to track their work facilitate the advancement in evaluating the impact of research. However, there is a gap in the identification of evidence of the social impact in terms of what citizens are sharing on their social media platforms. This article applies a social impact in social media methodology (SISM) to identify quantitative and qualitative evidence of the potential or real social impact of research shared on social media, specifically on Twitter and Facebook. We define the social impact coverage ratio (SICOR) to identify the percentage of tweets and Facebook posts providing information about potential or actual social impact in relation to the total amount of social media data found related to specific research projects. We selected 10 projects in different fields of knowledge to calculate the SICOR, and the results indicate that 0.43% of the tweets and Facebook posts collected provide linkages with information about social impact. However, our analysis indicates that some projects have a high percentage (4.98%) and others have no evidence of social impact shared in social media. Examples of quantitative and qualitative evidence of social impact are provided to illustrate these results. A general finding is that novel evidences of social impact of research can be found in social media, becoming relevant platforms for scientists to spread quantitative and qualitative evidence of social impact in social media to capture the interest of citizens. Thus, social media users are showed to be intermediaries making visible and assessing evidence of social impact.

88 citations

Journal ArticleDOI
30 Jul 2020
TL;DR: Comparisons of the type of Tweets and Sina Weibo posts regarding COVID-19 that contain either false or scientific veracious information show that there is more false news published and shared on Twitter than in Sina weibo, at the same time science-based evidence is more shared onTwitter than in Weibo but less than false news.
Abstract: Since the Coronavirus health emergency was declared, many are the fake news that have circulated around this topic, including rumours, conspiracy theories and myths. According to the World Economic Forum, fake news is one of the threats in today's societies, since this type of information circulates fast and is often inaccurate and misleading. Moreover, fake-news are far more shared than evidence-based news among social media users and thus, this can potentially lead to decisions that do not consider the individual’s best interest. Drawing from this evidence, the present study aims at comparing the type of Tweets and Sina Weibo posts regarding COVID-19 that contain either false or scientific veracious information. To that end 1923 messages from each social media were retrieved, classified and compared. Results show that there is more false news published and shared on Twitter than in Sina Weibo, at the same time science-based evidence is more shared on Twitter than in Weibo but less than false news. This stresses the need to find effective practices to limit the circulation of false information.

53 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the immediate responses in social work to vulnerable groups in the first 15 days of the pandemic in Barcelona, one of the most affected areas worldwide by COVID-19.
Abstract: Social work during the COVID-19 crisis has faced one of the most challenging times to cover urgent social needs in an uncertain scenario. This study analyzes the immediate responses in social work to vulnerable groups in the first 15 days of the pandemic in Barcelona, one of the most affected areas worldwide by COVID-19. The sample for this qualitative study includes 23 semi-structured interviews with social workers from different fields of intervention, from general approaches (primary care) to specific ones (health, ageing, homeless, and justice). The data analysis followed the communicative methodology, including transformative and exclusionary dimensions, and the analytical categories focused on the impact of the COVID-19 pandemic on social services users, the organizational responses of social workers, and the impact of the interventions to cover urgent social needs of attendees. The interventions have been accompanied by an improvement in communication channels with vulnerable groups, ensuring an understanding of the situation of families and individuals, and covering the most urgent social needs. The study shows the key role of social workers from diverse social attention tools and their contribution to the sustainability of social services with a long-term impact.

52 citations


Cited by
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Journal Article
TL;DR: This research examines the interaction between demand and socioeconomic attributes through Mixed Logit models and the state of art in the field of automatic transport systems in the CityMobil project.
Abstract: 2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

4,784 citations

01 Jan 2020
TL;DR: Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.
Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

4,408 citations

Book ChapterDOI
30 Dec 2011
TL;DR: This table lists the most common surnames in the United States used to be Anglicised as "United States", then changed to "United Kingdom" in the 1990s.
Abstract: OUTPU T 29 OUTPU T 30 OUTPU T 31 OUTPU T 32 OUTPU T 25 OUTPU T 26 OUTPU T 27 OUTPU T 28 OUTPU T 21 OUTPU T 22 OUTPU T 23 OUTPU T 24 OUTPU T 17 OUTPU T 18 OUTPU T 19 OUTPU T 20 OUTPU T 13 OUTPU T 14 OUTPU T 15 OUTPU T 16 OUTPU T 9 OUTPU T 10 OUTPU T 11 OUTPU T 12 OUTPU T 5 OUTPU T 6 OUTPU T 7 OUTPU T 8 OUTPU T 1 OUTPU T 2 OUTPU T 3 OUTPU T 4 29 30 31 32 25 26 27 28 21 22 23 24 17 18 19 20 13 14 15 16 9

1,662 citations

Journal ArticleDOI
01 Mar 2021
TL;DR: In this paper, the authors identified five broad public health themes concerning the role of online social media platforms and COVID-19, focusing on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos.
Abstract: With the onset of the COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak from November, 2019, to November, 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social media platforms and COVID-19. These themes focused on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID-19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos. Furthermore, our Review emphasises the paucity of studies on the application of machine learning on data from COVID-19-related social media and a scarcity of studies documenting real-time surveillance that was developed with data from social media on COVID-19. For COVID-19, social media can have a crucial role in disseminating health information and tackling infodemics and misinformation.

377 citations

Journal ArticleDOI
TL;DR: It was found that social media users’ motivations for information sharing, socialisation, information seeking and pass time predicted the sharing of false information about COVID-19, and no significant association was found for entertainment motivation.

368 citations