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Mario Jojoa

Biographic Data

ID7841944
NAMEMario Jojoa
GIVEN NAMESMario
FAMILY NAMEJojoa
SIGNATUREJOJOA M
AFFILIATIONSUniversidad de Deusto
ORCID0000-0002-6578-071X
VERIFIEDYes
TOTAL WORKS7
TOTAL CITATIONS0
AUTHOR COUNT7
EDITOR COUNT0
FIRST PUBLICATION YEAR2021
LATEST PUBLICATION YEAR2024
H-INDEX0
  • Natural language processing analysis applied to Covid-19 open-text opinions using a distilBert model for sentiment categorization

    Open Access•Mario Jojoa, Parvin Eftekhar et al.•ARTICLE•AI & Society•2024

    COVID-19 is a disease that affects the quality of life in all aspects. However, the government policy applied in 2020 impacted the lifestyle of the whole world. In this sense, the study of sentiments of people in different countries is a very important task to face future challenges related to lockdown caused by a virus. To contribute to this objective, we have proposed a natural language processing model with the aim to detect positive and negat…

  • Are AI systems biased against the poor? A machine learning analysis using Word2Vec and GloVe embeddings

    Open Access•Georgina Curto, Mario Jojoa et al.•ARTICLE•AI & Society•2024

    Among the myriad of technical approaches and abstract guidelines proposed to the topic of AI bias, there has been an urgent call to translate the principle of fairness into the operational AI reality with the involvement of social sciences specialists to analyse the context of specific types of bias, since there is not a generalizable solution. This article offers an interdisciplinary contribution to the topic of AI and societal bias, in particul…

  • Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques

    Open Access•Mario Jojoa, Begonya García-Zapirain et al.•ARTICLE•International Journal of…•2022

    The aim of this study is to analyze the effects of lockdown using natural language processing techniques, particularly sentiment analysis methods applied at large scale. Further, our work searches to analyze the impact of COVID-19 on the university community, jointly on staff and students, and with a multi-country perspective. The main findings of this work show that the most often related words were "family", "anxiety", "house", and "life". Besi…

  • Application of Machine Learning Techniques to Help in the Feature Selection Related to Hospital Readmissions of Suicidal Behavior

    Open Access•Gema Castillo-Sánchez, Mario Jojoa et al.•ARTICLE•International Journal of Mental…•2022

    Suicide was the main source of death from external causes in Spain in 2020, with 3,941 cases. The importance of identifying those mental disorders that influenced hospital readmissions will allow us to manage the health care of suicidal behavior. The feature selection of each hospital in this region was carried out by applying Machine learning (ML) and traditional statistical methods. The results of the characteristics that best explain the readm…

  • Sentiment Analysis Techniques Applied to Raw-Text Data from a Csq-8 Questionnaire about Mindfulness in Times of Covid-19 to Improve Strategy Generation

    Open Access•Mario Jojoa, Gema Castillo-Sánchez et al.•ARTICLE•International Journal of…•2021

    The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in…

  • The Impact of Covid 19 on University Staff and Students from Iberoamerica

    Open Access•Mario Jojoa, Esther Lázaro et al.•ARTICLE•International Journal of…•2021

    (1) Background: The COVID-19 pandemic has created a great impact on mental health in society. Considering the little attention paid by scientific studies to either students or university staff during lockdown, the current study has two aims: (a) to analyze the evolution of mental health and (b) to identify predictors of educational/professional experience and online learning/teaching experience. (2) Methods: 1084 university students and 554 staff…

  • Executive Functioning in Adults with Down Syndrome

    Open Access•Mario Jojoa, Sara Signo-Miguel et al.•ARTICLE•International Journal of…•2021

    The study of executive function decline in adults with Down syndrome (DS) is important, because it supports independent functioning in real-world settings. Inhibitory control is posited to be essential for self-regulation and adaptation to daily life activities. However, cognitive domains that most predict the capacity for inhibition in adults with DS have not been identified. The aim of this study was to identify cognitive domains that predict t…

No prominent works on this page.

  • Sentiment Analysis Techniques Applied to Raw-Text Data from a Csq-8 Questionnaire about Mindfulness in Times of Covid-19 to Improve Strategy Generation

    Open Access•Mario Jojoa, Gema Castillo-Sánchez et al.•ARTICLE•International Journal of…•2021

    The use of artificial intelligence in health care has grown quickly. In this sense, we present our work related to the application of Natural Language Processing techniques, as a tool to analyze the sentiment perception of users who answered two questions from the CSQ-8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in…

  • The Impact of Covid 19 on University Staff and Students from Iberoamerica

    Open Access•Mario Jojoa, Esther Lázaro et al.•ARTICLE•International Journal of…•2021

    (1) Background: The COVID-19 pandemic has created a great impact on mental health in society. Considering the little attention paid by scientific studies to either students or university staff during lockdown, the current study has two aims: (a) to analyze the evolution of mental health and (b) to identify predictors of educational/professional experience and online learning/teaching experience. (2) Methods: 1084 university students and 554 staff…

  • Executive Functioning in Adults with Down Syndrome

    Open Access•Mario Jojoa, Sara Signo-Miguel et al.•ARTICLE•International Journal of…•2021

    The study of executive function decline in adults with Down syndrome (DS) is important, because it supports independent functioning in real-world settings. Inhibitory control is posited to be essential for self-regulation and adaptation to daily life activities. However, cognitive domains that most predict the capacity for inhibition in adults with DS have not been identified. The aim of this study was to identify cognitive domains that predict t…

  • Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques

    Open Access•Mario Jojoa, Begonya García-Zapirain et al.•ARTICLE•International Journal of…•2022

    The aim of this study is to analyze the effects of lockdown using natural language processing techniques, particularly sentiment analysis methods applied at large scale. Further, our work searches to analyze the impact of COVID-19 on the university community, jointly on staff and students, and with a multi-country perspective. The main findings of this work show that the most often related words were "family", "anxiety", "house", and "life". Besi…

  • Application of Machine Learning Techniques to Help in the Feature Selection Related to Hospital Readmissions of Suicidal Behavior

    Open Access•Gema Castillo-Sánchez, Mario Jojoa et al.•ARTICLE•International Journal of Mental…•2022

    Suicide was the main source of death from external causes in Spain in 2020, with 3,941 cases. The importance of identifying those mental disorders that influenced hospital readmissions will allow us to manage the health care of suicidal behavior. The feature selection of each hospital in this region was carried out by applying Machine learning (ML) and traditional statistical methods. The results of the characteristics that best explain the readm…

  • Natural language processing analysis applied to Covid-19 open-text opinions using a distilBert model for sentiment categorization

    Open Access•Mario Jojoa, Parvin Eftekhar et al.•ARTICLE•AI & Society•2024

    COVID-19 is a disease that affects the quality of life in all aspects. However, the government policy applied in 2020 impacted the lifestyle of the whole world. In this sense, the study of sentiments of people in different countries is a very important task to face future challenges related to lockdown caused by a virus. To contribute to this objective, we have proposed a natural language processing model with the aim to detect positive and negat…

  • Are AI systems biased against the poor? A machine learning analysis using Word2Vec and GloVe embeddings

    Open Access•Georgina Curto, Mario Jojoa et al.•ARTICLE•AI & Society•2024

    Among the myriad of technical approaches and abstract guidelines proposed to the topic of AI bias, there has been an urgent call to translate the principle of fairness into the operational AI reality with the involvement of social sciences specialists to analyse the context of specific types of bias, since there is not a generalizable solution. This article offers an interdisciplinary contribution to the topic of AI and societal bias, in particul…

Psychology (7 works) · Computer Science (5 works) · Medicine (5 works) · Artificial Intelligence (3 works) · Clinical Psychology (3 works) · Clinical Psychology (3 works) · Cognitive psychology (3 works) · Coronavirus disease 2019 (COVID-19 (3 works) · COVID-19 and Mental Health (3 works) · Data science (3 works)

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