Artificial Intelligence, one more weapon in the fight against disinformation: overview in the IFCN Hispanic network of fact-checkers (DataJConf 2023, Zurich)
Artificial intelligence is being used by some fact-checking organizations to aid in their work, though implementation is uneven and still developing. Around half of the 17 organizations studied have created 1-3 AI tools, mainly chatbots, to help with tasks like verifying sources and statements. However, many lack dedicated research teams or funding. While AI offers opportunities to increase efficiency, fact-checkers also see challenges from advances like deepfakes requiring new verification methods. Ongoing collaboration and adapting to changing information threats will help fact-checkers continue leveraging AI responsibly.
How does fakenews spread understanding pathways of disinformation spread thro...Araz Taeihagh
What are the pathways for spreading disinformation on social media platforms? This article addresses this question by collecting, categorising, and situating an extensive body of research on how application programming interfaces (APIs) provided by social media platforms facilitate the spread of disinformation. We first examine the landscape of official social media APIs, then perform quantitative research on the open-source code repositories GitHub and GitLab to understand the usage patterns of these APIs. By inspecting the code repositories, we classify developers' usage of the APIs as official and unofficial, and further develop a four-stage framework characterising pathways for spreading disinformation on social media platforms. We further highlight how the stages in the framework were activated during the 2016 US Presidential Elections, before providing policy recommendations for issues relating to access to APIs, algorithmic content, advertisements, and suggest rapid response to coordinate campaigns, development of collaborative, and participatory approaches as well as government stewardship in the regulation of social media platforms.
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
COMBINING MACHINE LEARNING AND SEMANTIC ANALYSIS FOR EFFICIENT MISINFORMATION...ijcsit
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
How does fakenews spread understanding pathways of disinformation spread thro...Araz Taeihagh
What are the pathways for spreading disinformation on social media platforms? This article addresses this question by collecting, categorising, and situating an extensive body of research on how application programming interfaces (APIs) provided by social media platforms facilitate the spread of disinformation. We first examine the landscape of official social media APIs, then perform quantitative research on the open-source code repositories GitHub and GitLab to understand the usage patterns of these APIs. By inspecting the code repositories, we classify developers' usage of the APIs as official and unofficial, and further develop a four-stage framework characterising pathways for spreading disinformation on social media platforms. We further highlight how the stages in the framework were activated during the 2016 US Presidential Elections, before providing policy recommendations for issues relating to access to APIs, algorithmic content, advertisements, and suggest rapid response to coordinate campaigns, development of collaborative, and participatory approaches as well as government stewardship in the regulation of social media platforms.
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
COMBINING MACHINE LEARNING AND SEMANTIC ANALYSIS FOR EFFICIENT MISINFORMATION...ijcsit
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGijaia
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety,
Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
Categorizing 2019-n-CoV Twitter Hashtag Data by Clusteringgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
[2018] Tech Trends For Journalism and Media – The Future Today InstituteFilipp Paster
Key Takeaways
2018 marks the beginning of the end of smartphones in the world's largest economies. What's coming next are conversational interfaces with zero-UIs. This will radically change the media landscape, and now is the best time to start thinking through future scenarios.
In 2018, a critical mass of emerging technologies will converge finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. News organizations should devote attention to emerging trends in voice interfaces, the decentralization of content, mixed reality, new types of search, and hardware (such as CubeSats and smart cameras).
Journalists need to understand what artificial intelligence is, what it is not, and what it means for the future of news. AI research has advanced enough that it is now a core component of our work at FTI. You will see the AI ecosystem represented in many of the trends in this report, and it is vitally important that all decision-makers within news organizations familiarize themselves with the current and emerging AI landscapes. We have included an AI Primer For Journalists in our Trend Report this year to aid in that effort.
Decentralization emerged as a key theme for 2018. Among the companies and organizations FTI covers, we discovered a new emphasis on restricted peer-to-peer networks to detect harassment, share resources and connect with sources. There is also a push by some democratic governments around the world to divide internet access and to restrict certain content, effectively creating dozens of “splinternets.”
Consolidation is also a key theme for 2018. News brands, broadcast spectrum, and artificial intelligence startups will continue to be merged with and acquired by relatively few corporations. Pending legislation and policy in the U.S., E.U. and in parts of Asia could further concentrate the power among a small cadre of information and technology organizations in the year ahead.
To understand the future of news, you must pay attention to the future of many industries and research areas in the coming year. When journalists think about the future, they should broaden the usual scope to consider developments from myriad other fields also participating in the knowledge economy. Technology begets technology. We are witnessing an explosion in slow motion.
Disinformation and AI: Separating fact from fictionTitanEurope1
Presentation by Ana Fernandez from VUB on the challenges presented by disinformation, and how the TITAN project is advancing the state of the art in countering this phenomenon through AI tools. Namely, using a chatbot to help people ask the right question about content to decide if it is true or not. This presentation was given at the European Week of Regions and Cities 2023.
To learn more about TITANs approach and to subscribe for updates visit www.titanthinking.eu
Defin
ing artificial intelligence is no easy matter. Since the mid
-
20th century when it
was first
recognized
as a specific field of research, AI has always been envisioned as
an evolving boundary, rather than a settled research field. Fundamentally, it refers
to
a programme whose ambitious objective is to understand and reproduce human
cognition; creating cognitive processes comparable to those found in human beings.
Therefore, we are naturally dealing with a wide scope here, both in terms of the
technical proced
ures that can be employed and the various disciplines that can be
called upon: mathematics, information technology, cognitive sciences, etc. There is
a great variety of approaches when it comes to AI: ontological, reinforcement
learning, adversarial learni
ng and neural networks, to name just a few. Most of them
have been known for decades and many of the algorithms used today were
developed in the ’60s and ’70s.
Since the 1956 Dartmouth conference, artificial intelligence has alternated between
periods of
great enthusiasm and disillusionment, impressive progress and frustrating
failures. Yet, it has relentlessly pushed back the limits of what was only thought to
be achievable by human beings. Along the way, AI research has achieved significant
successes: o
utperforming human beings in complex games (chess, Go),
understanding natural language, etc. It has also played a critical role in the history
of mathematics and information technology. Consider how many softwares that we
now take for granted once represen
ted a major breakthrough in AI: chess game
apps, online translation programmes, etc
This research is presenting a critical review of existing methodologies and researches that deal with using
AI as a tool of mining data in order to smooth and lead evidence in enforcing law. It will review as well the
current situation in Jordan as possible as we can access the current available resources, where the method
of mining information and using AI or soft evidence are to be addressed. The research concluded the
importance of AI as supportive technology in policing, fighting crimes, cybercrimes, as models for
enforcing law, but there were no cutoff evidence in using AI advanced methods in mining data in Jordan
police and intelligence, simply because it was impossible mission to access the security information of such
bodies.
Digital development and Online Gender-Based ViolenceAnand Sheombar
Online talk held for Cordaid 18th November 2021, on the concept of digital development, and what online gender-based violence (GBV or eVAW) means for the activities of international development NGOs.
The technology is one of the fastest growing industries. This paper illustrates just how and why the lack of diversity in the technology industry affects individuals in the real world as well as in education. This paper expresses why diversity in the tech industry should be addressed and how the lack of it begins to trickle into our education system.
A comprehensive review of AI use within the public relations profession.
At time of writing (February 2023), there’s been a burst of new AI-driven tools, services and use cases with the potential to impact virtually every aspect of the public relations profession.
This report is an attempt to assess the likely rapid progress of AI technology over the next year and the longer-term strategic considerations for all public relations practitioners as a result.
Co-authored by Andrew Bruce Smith and Stephen Waddington, with contributions from Professor Anne Gregory, Jean Valin and Scott Brinker.
Generative AI in Organizations: Insights and Strategies from Communication Le...Olivia Kresic
In “Generative AI in Organizations: Insights and Strategies from Communication Leaders,” the Institute for Public Relations (IPR) conducted interviews from November 2023 to January 2024 with 30 communication executives, chief communication officers (CCOs), agency CEOs, academics, and leaders to examine how generative AI is impacting their function and organization. This report specifically examines the role of AI tools like ChatGPT, Microsoft Copilot, DALL-E, and others, probing how they are shaping communication and marketing strategies.
Generative AI in Organizations: Insights and Strategies from Communication Le...Olivia Kresic
New! In, “Generative AI in Organizations: Insights and Strategies from Communication Leaders,” the Institute for Public Relations (IPR) conducted interviews from November 2023 to January 2024 with 30 communication executives, chief communication officers (CCOs), agency CEOs, academics, and leaders to examine how generative AI is impacting their function and organization. This report specifically examines the role of AI tools like ChatGPT, Microsoft Copilot, DALL-E, and others, probing how they are shaping communication and marketing strategies.
Ponencia en I SEMINARIO SOBRE LA APLICABILIDAD DE LA INTELIGENCIA ARTIFICIAL EN LA EDUCACIÓN SUPERIOR UNIVERSITARIA. 3 de junio de 2024. Facultad de Estudios Sociales y Trabajo, Universidad de Málaga.
Presentación base de ponencia invitada en Jornadas de Innovación Educativa en comunicación y alfabetización mediática organizadas por Departamento de Periodismo de la Universidad de País Vasco, 27 y 28 de abril de 2023.
More Related Content
Similar to Artificial Intelligence, one more weapon in the fight against disinformation: overview in the IFCN Hispanic network of fact-checkers (DataJConf 2023, Zurich)
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGijaia
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety,
Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
Categorizing 2019-n-CoV Twitter Hashtag Data by Clusteringgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
[2018] Tech Trends For Journalism and Media – The Future Today InstituteFilipp Paster
Key Takeaways
2018 marks the beginning of the end of smartphones in the world's largest economies. What's coming next are conversational interfaces with zero-UIs. This will radically change the media landscape, and now is the best time to start thinking through future scenarios.
In 2018, a critical mass of emerging technologies will converge finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. News organizations should devote attention to emerging trends in voice interfaces, the decentralization of content, mixed reality, new types of search, and hardware (such as CubeSats and smart cameras).
Journalists need to understand what artificial intelligence is, what it is not, and what it means for the future of news. AI research has advanced enough that it is now a core component of our work at FTI. You will see the AI ecosystem represented in many of the trends in this report, and it is vitally important that all decision-makers within news organizations familiarize themselves with the current and emerging AI landscapes. We have included an AI Primer For Journalists in our Trend Report this year to aid in that effort.
Decentralization emerged as a key theme for 2018. Among the companies and organizations FTI covers, we discovered a new emphasis on restricted peer-to-peer networks to detect harassment, share resources and connect with sources. There is also a push by some democratic governments around the world to divide internet access and to restrict certain content, effectively creating dozens of “splinternets.”
Consolidation is also a key theme for 2018. News brands, broadcast spectrum, and artificial intelligence startups will continue to be merged with and acquired by relatively few corporations. Pending legislation and policy in the U.S., E.U. and in parts of Asia could further concentrate the power among a small cadre of information and technology organizations in the year ahead.
To understand the future of news, you must pay attention to the future of many industries and research areas in the coming year. When journalists think about the future, they should broaden the usual scope to consider developments from myriad other fields also participating in the knowledge economy. Technology begets technology. We are witnessing an explosion in slow motion.
Disinformation and AI: Separating fact from fictionTitanEurope1
Presentation by Ana Fernandez from VUB on the challenges presented by disinformation, and how the TITAN project is advancing the state of the art in countering this phenomenon through AI tools. Namely, using a chatbot to help people ask the right question about content to decide if it is true or not. This presentation was given at the European Week of Regions and Cities 2023.
To learn more about TITANs approach and to subscribe for updates visit www.titanthinking.eu
Defin
ing artificial intelligence is no easy matter. Since the mid
-
20th century when it
was first
recognized
as a specific field of research, AI has always been envisioned as
an evolving boundary, rather than a settled research field. Fundamentally, it refers
to
a programme whose ambitious objective is to understand and reproduce human
cognition; creating cognitive processes comparable to those found in human beings.
Therefore, we are naturally dealing with a wide scope here, both in terms of the
technical proced
ures that can be employed and the various disciplines that can be
called upon: mathematics, information technology, cognitive sciences, etc. There is
a great variety of approaches when it comes to AI: ontological, reinforcement
learning, adversarial learni
ng and neural networks, to name just a few. Most of them
have been known for decades and many of the algorithms used today were
developed in the ’60s and ’70s.
Since the 1956 Dartmouth conference, artificial intelligence has alternated between
periods of
great enthusiasm and disillusionment, impressive progress and frustrating
failures. Yet, it has relentlessly pushed back the limits of what was only thought to
be achievable by human beings. Along the way, AI research has achieved significant
successes: o
utperforming human beings in complex games (chess, Go),
understanding natural language, etc. It has also played a critical role in the history
of mathematics and information technology. Consider how many softwares that we
now take for granted once represen
ted a major breakthrough in AI: chess game
apps, online translation programmes, etc
This research is presenting a critical review of existing methodologies and researches that deal with using
AI as a tool of mining data in order to smooth and lead evidence in enforcing law. It will review as well the
current situation in Jordan as possible as we can access the current available resources, where the method
of mining information and using AI or soft evidence are to be addressed. The research concluded the
importance of AI as supportive technology in policing, fighting crimes, cybercrimes, as models for
enforcing law, but there were no cutoff evidence in using AI advanced methods in mining data in Jordan
police and intelligence, simply because it was impossible mission to access the security information of such
bodies.
Digital development and Online Gender-Based ViolenceAnand Sheombar
Online talk held for Cordaid 18th November 2021, on the concept of digital development, and what online gender-based violence (GBV or eVAW) means for the activities of international development NGOs.
The technology is one of the fastest growing industries. This paper illustrates just how and why the lack of diversity in the technology industry affects individuals in the real world as well as in education. This paper expresses why diversity in the tech industry should be addressed and how the lack of it begins to trickle into our education system.
A comprehensive review of AI use within the public relations profession.
At time of writing (February 2023), there’s been a burst of new AI-driven tools, services and use cases with the potential to impact virtually every aspect of the public relations profession.
This report is an attempt to assess the likely rapid progress of AI technology over the next year and the longer-term strategic considerations for all public relations practitioners as a result.
Co-authored by Andrew Bruce Smith and Stephen Waddington, with contributions from Professor Anne Gregory, Jean Valin and Scott Brinker.
Generative AI in Organizations: Insights and Strategies from Communication Le...Olivia Kresic
In “Generative AI in Organizations: Insights and Strategies from Communication Leaders,” the Institute for Public Relations (IPR) conducted interviews from November 2023 to January 2024 with 30 communication executives, chief communication officers (CCOs), agency CEOs, academics, and leaders to examine how generative AI is impacting their function and organization. This report specifically examines the role of AI tools like ChatGPT, Microsoft Copilot, DALL-E, and others, probing how they are shaping communication and marketing strategies.
Generative AI in Organizations: Insights and Strategies from Communication Le...Olivia Kresic
New! In, “Generative AI in Organizations: Insights and Strategies from Communication Leaders,” the Institute for Public Relations (IPR) conducted interviews from November 2023 to January 2024 with 30 communication executives, chief communication officers (CCOs), agency CEOs, academics, and leaders to examine how generative AI is impacting their function and organization. This report specifically examines the role of AI tools like ChatGPT, Microsoft Copilot, DALL-E, and others, probing how they are shaping communication and marketing strategies.
Similar to Artificial Intelligence, one more weapon in the fight against disinformation: overview in the IFCN Hispanic network of fact-checkers (DataJConf 2023, Zurich) (20)
Ponencia en I SEMINARIO SOBRE LA APLICABILIDAD DE LA INTELIGENCIA ARTIFICIAL EN LA EDUCACIÓN SUPERIOR UNIVERSITARIA. 3 de junio de 2024. Facultad de Estudios Sociales y Trabajo, Universidad de Málaga.
Presentación base de ponencia invitada en Jornadas de Innovación Educativa en comunicación y alfabetización mediática organizadas por Departamento de Periodismo de la Universidad de País Vasco, 27 y 28 de abril de 2023.
Intervención como ponente invitada en Mesa redonda "El papel de las organizaciones verificadoras de la información durante la covid-19 en Iberoamérica". VII Workshop Internacional de Estudios Iberoamericanos y Transatlánticos “La dimensión social de la pandemia durante la Covid-19. Una mirada transatlántica”. Málaga, 25 de enero de 2023.
*Presentación de elaboración propia, con contenido adaptado de trabajos anteriores.
* Vectores tomados de Freepik/ Flaticon. Imágenes de Pixabay.
En este seminario virtual, enmarcado en el Plan de Formación de Profesorado de la UNIA de 2022-23, María Sánchez González (@cibermarikiya) repasa el potencial de la información visual y sus posibilidades en el ámbito de la enseñanza-aprendizaje y la difusión de la investigación y de la innovación y comparte claves del proceso de producción y herramientas digitales útiles para diseñar infografías y visualizaciones de datos, entre otras cuestiones.
Sánchez González, M.; Sánchez Gonzales, H..M.; Martos Moreno, J. (2021). Periodismo emprendedor sobre verificación: casos significativos de habla hispana. Presentación de comunicación para Congreso SEP 2021, online, 28 de mayo de 2021. Más información: https://www.sepsevilla2021.com/
Material empleado en taller sobre elevator pitch y presentaciones de proyectos impartido como voluntaria invitada en Club de Insipiring Girls de niñas gitanas en Málaga. Polo de Contenidos Digitales, Málaga, 27 de mayo de 2021.
Presentación del seminario virtual "Claves para el diseño e impartición de MOOCs y derivados" (#webinarsUNIA, Plan de Formación, apoyo y asesoramiento al profesorado 2020-21). Impartido el 03/02/2012, con más de 600 personas inscritas, por webconferencia.
Grabación y presentación también en repositorio institucional de UNIA: https://dspace.unia.es/handle/10334/5753
Presentación empleada por María Sánchez (UMA/UNIA) para su intervención como invitada en el Seminario Internacional en educación abierta, colaborativa y sostenible en red, organizado por la Universidad Austral de Chile y el Grupo de investigación en Tecnologías de Aprendizaje (GITA) de dicha universidad, bajo el soporte del grupo de universidades iberoamericanas La Rábida, presidido por la UNIA.
El seminario tuvo lugar los días 30 de noviembre y 1 de diciembre de 2020 online.
Presentación utilizada en ponencia impartida en el marco del I Hackathon para docentes de FPI FormaT&T, 13 de noviembre de 2020. Evento online en el que han participado más de 250 docentes de formación profesional de toda España.
Ver vídeo de ponencia en Youtube vía: https://t.co/FwvuhkaBF8?amp=1
Presentación empleada para seminario sobre "Estrategias y herramientas de evaluación no presencial en Ciencias de la Comunicación".- Dentro del ciclo de seminarios virtuales de formación para el modelo de enseñanza bimodal (sept. 2020) impartidos el 16 y 17 de septiembre por webconferencia como parte de mi labor como Mentora de Competencias Digitales de la Facultad de Ciencias de la Comunicación de la Universidad de Málaga. Presentación de mi autoría. La segunda parte de este seminario, de carácter práctico, fue a cargo de mi compañero Antonio Castro.
Presentación empleada para seminario sobre "Planificación de asignaturas semipresenciales: aspectos clave, ideas, herramientas y casos prácticos aplicables a Ciencias de la Comunicación".- Dentro del ciclo de seminarios virtuales de formación para el modelo de enseñanza bimodal (sept. 2020) impartidos el 16 y 17 de septiembre por webconferencia como parte de mi labor como Mentora de Competencias Digitales de la Facultad de Ciencias de la Comunicación de la Universidad de Málaga.
Presentación del seminario virtual "Vídeos y podcasts para humanizar la experiencia de estudiantes en línea" (#webinarsUNIA, Plan de Formación, apoyo y asesoramiento al profesorado 2020-21). Impartido el 14/09/2020, con más de 600 personas inscritas, por webconferencia.
Presentación empleada para el seminario online impartido para profesorado de la Universidad Técnica Federico de Santa María, Chile, el 17 de agosto de 2020, con más de 120 inscripciones y conexiones en directo. Actividad arranque de Jornadas docentes "Nuevos tiempos exigen modelos docentes innovadores"
Presentación realizada por María Sánchez y Francisco Martín, profesores de Periodismo de la Universidad de Málaga, en Jornadas de reflexión sobre los estudios de Periodismo. Iniciativa organizada por Departamento de Periodismo. Febrero de 2020.
Presentación empleada como ponente invitada en seminario virtual "Universidad Next Normal: Innovación y Redes en Docencia". Organizado en el marco de proyecto de innovación educativa coordinado desde la Universidad de Sevilla y en el que participan también la Universidad de Cádiz y la Universidad de Valladolid.
Presentación empleada en seminario virtual "Actividades educativas por webconferencia: planificar y comunicar ante la cámara". Universidad de Cádiz, 21 de julio de 2020.
Presentación sobre “Diseño y planificación de asignaturas semipresenciales ante la COVID-19″, empleada para seminario virtual para profesorado de Universidad de Alcalá. Organizado por I.C.E./ Vicerrectorado de Gestión de la Calidad UAH. Impartido el 22/ 07/2020. Con 250 personas asistentes (tope de plazas ofertadas).
Título: Presentación del seminario virtual "Diseñar/ adaptar programas formativos a e-learning: claves sobre el modelo de la UNIA" (#webinarsUNIA, Plan de Formación, apoyo y asesoramiento al profesorado 2020-21).
Fecha: 22/06/2020.
Temática: Innovación, Formación de Profesorado.
Descriptores: webinarsUNIA, webinars, seminario, UNIA, universidad, Málaga Innovación, Formación de Profesorado, TICs, competencias digitales, enseñanza-aprendizaje online, uniainnova, webconferencia, María Sánchez González, b-learning, e-learning, casos prácticos, virtualización, teledocencia, diseño, guías, evaluación, materiales, actividades, organización, planificación, secuenciación, recursos, campus virtual.
Sinopsis:
En este seminario virtual, enmarcado en el Plan de Formación de Profesorado de la UNIA de 2020-21, María Sánchez González, técnico de Innovación de la UNIA y profesora asociada doctora e investigadora en Periodismo en la UMA, reflexionar sobre la importancia del diseño y la planificación en
actividades formativas en red y aporta ideas, claves y casos
prácticos desde el punto de vista organizativo, tecnológico y
didáctico- metodológico sobre su experiencia docente y el propio modelo de enseñanza-aprendizaje en red de la UNIA.
El seminario tuvo lugar empleando el servicio de aulas virtuales de la UNIA (basado en Adobe Connect), y en él pudo participar cualquier interesado/a, más allá de docentes en activo de la Universidad. Contó con unas 500 personas inscritas de diverso perfil y procedencia geográfica.
Más información: unia.es/oferta-academica/webinars-unia
Título: Presentación del seminario virtual "La webconferencia para el aprendizaje síncrono en red: posibilidades y organización de actividades" (#webinarsUNIA, Plan de Formación, apoyo y asesoramiento al profesorado 2020-21).
Fecha: 29/06/2020.
Temática: Innovación, Formación de Profesorado.
Descriptores: webinarsUNIA, webinars, seminario, UNIA, universidad, Málaga Innovación, Formación de Profesorado, TICs, competencias digitales, enseñanza-aprendizaje online, uniainnova, webconferencia, María Sánchez González, b-learning, e-learning, casos prácticos, virtualización, teledocencia, diseño, actividades, organización, planificación, comunicación ante la cámara, webinars, evaluación online, sesiones síncronas, videoconferencia, aulas virtuales
Sinopsis:
En este seminario virtual, enmarcado en el Plan de Formación de Profesorado de la UNIA de 2020-21, María Sánchez González, técnico de Innovación de la UNIA y profesora asociada doctora e investigadora en Periodismo en la UMA, repasa posibles usos de la webconferencia en e-learning, b-learning, docencia presencial y programas de aprendizaje abierto en red y aporta claves y ejemplos relacionados con la organización e impartición de actividades educativas síncronas por videoconferencia.
El seminario tuvo lugar empleando el servicio de aulas virtuales de la UNIA (basado en Adobe Connect), y en él pudo participar cualquier interesado/a, más allá de docentes en activo de la Universidad. Contó con más de 520 personas inscritas de diverso perfil y procedencia geográfica.
Más información: unia.es/oferta-academica/webinars-unia
More from María Sánchez González (@cibermarikiya) (20)
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Artificial Intelligence, one more weapon in the fight against disinformation: overview in the IFCN Hispanic network of fact-checkers (DataJConf 2023, Zurich)
1. Artificial Intelligence, one more
weapon in the fight against
disinformation: overview in the
IFCN Hispanic network of fact-
checkers
*R+D+i project “DESINFOPER”, PID2019-108956RB-I00.
other authors: Hada Sánchez and Sergio Martínez
speaker: María Sánchez González
University of Malaga, Spain | m.sanchezgonzalez@uma.es
2. The case of Spanish and Ibero-American baseline verification
platforms *members of IFCN's #CoronavirusFacts Alliance (17)
Research questions
How do these verifiers contemplate
Artificial Intelligence and its possible
applications for fact-checking?
Have these verifiers developed their
own initiatives and/or do they use
external tools? What kind of tools are
they used for?
To what extent do verifiers take
advantage of AI to carry out their
work? What are the limitations and
opportunities?
Fuente: IFCN en Facebook, mayo de 2020
3. [Census: 14, by 8/17 fact-checkers] [March-May
2022]
Collecting on an online form technological and
functional categories and variables such as:
● Context for technological innovation and the use of AI
in verifiers analyzed (existence or not of R+D+i
sections; profiles; perception of AI potential;
participation in programs or external collaborations;
etc.).
● Development of AI tools/initiatives for each of the
verifiers analyzed (Yes/No; typology; use in journalism
and verification; etc.).
Online consultation on AI projects (2022) +
information retrieved from interviews with
professionals responsible for some verifiers (2020-
21)
Collection of perception regarding digital verification tools
and regarding their plans to develop their own initiatives
based on big data and artificial intelligence in the short and
medium term.
Methodology
Localization, classification and analysis
of self-developed AI project
CORE COMPLEMENT
Vision of its responsible professionals
Documentary review | Expert vision (8
people) | etc.
4. Methodology
Basic data of projects analyzed (17) and interviews/ contacts made
Fact-checker Country Person Interviewed (2020-21) Person contacted online (2022)
Agencia Lupa Brasil -
Agencia Ocote (Fáctica) Guatemala Alejandra Gutiérrez (directora y coord. editorial) Alejandra Gutiérrez (directora y coord. editorial)
Animal Político (El Sabueso) México Tania Montalvo (editora general)
Aos Fatos Brasil -
Bolivia Verifica Bolivia -
Chequeado Argentina Laura Zommer (directora ejecutiva y periodística)
Colombia Check Colombia - Jeanfreddy Gutiérrez (director)
Ecuador Chequea Ecuador Erika Astudillo (editora)
EFE Verifica España Desireé García (responsable)
Estadão Verifica Brasil -
La Silla Vacía (Detector de
mentiras) Colombia - María Echeverry (fact-checker)
Maldita (Maldito Bulo) España Clara Jiménez (cofundadora y codirectora)
Newtral España Joaquín Ortega (responsable de contenido)
Irene Larraz (coordinadora de fact-checking) y
Pablo Hernández
Observador Portugal -
Salud con Lupa (Comprueba) Perú Fabiola Torres (directora co-fundadora)
La República (Verificador) Perú Irene Ignacio (coordinadora de contenidos) Irene Ignacio (coordinadora de contenidos)
Professionals and experts
consulted on AI (8)
Miriam Hernanz (ex Lab RTVE, now Prisa
Media). Interview 23/03/21.
Rocío Celeste (experta en IA). Interview
25/03/21.
Ana Valdivia (experta en datos). Interview
26/03/21.
José Carlos Sánchez (Prodigioso Volcán).
Eirini Chatzikoumi (investigadora periodismo
e IA). Interview 01/04/21.
Idoia Salazar (periodista y presidenta de
OdiseIA). Interview 12/04/21.
Javier Cantón (experto en datos y
verificación). Interview 26/04/21.
David Fernández (Maldita). Interview 28/04/21.
5. ● Warning and early detection of disinformation in texts, statements,
images and videos (deep fakes).
● Time saving by automating routine tasks.
● Increasing productivity and efficiency, especially as AI algorithms
are trained.
● Etc.
General agreement among
professionals about the possibilities of
AI for fact-checking
Almost as a complement to their
human work as verifiers
Results and discussion
6. However, uneven and
incipient implementation
of AI in the verifiers
analyzed
Around half of the cases studied (8 out of
17 verifiers) have initiatives/tools based on
AI (14 localized in total) that apply to fact-
checking.
These are the most veteran and innovative
verifiers, such as the Spanish Maldita and
Newtral, with 3 initiatives each.
Practically all of the tools emerged in the
last 5 years (many, during the Covid-19
pandemic) and were available (also openly)
at the time of the study.
Fact-checker AI initiative(s) or tool(s) Year of
creation
Available
at study
time
Agencia Lupa Projeto Lupe! 2018 No
No Epicentro 2020 Yes
AOS Fatos Fátima 2018 Yes
Radar 2020 Yes
Colombia
Check
Redcheq 2019 No
Bolivia Verifica Olivia 2022 Yes
Chequeado Chequeabot 2016 Yes
Maldita Chatbot Maldita.es 2020 Yes
Maldita.es 2019 Yes
Caja de herramientas 2018 Yes
Newtral ClaimHunter 2020 Yes
Editor 2020 Yes
Servicio de verificación de WhatsApp 2020 Yes
EFE Verifica Videre AI 2022 Yes
7. Features of self-developed AI tools: chatbots for verification as
majority trends while others are still to be exploited (eg.
Generative AI or Deep Fakes)
Typology
Orientation regarding
journalistic work
Use in verification processes
1. Bot (8)
2. Service (4)
3. Online Aplication (2)
4. Mobile App (1)
5. Browser Extension (1)
6. Microsite (1)
1. Verification procedures (12)
2. Management and debugging
of massive databases (5)
3. Sending automated
responses/content to
audiences (5)
4. Automatic content generation
(2)
1. Source verification (11)
2. Verification of phrases that
have previously been
published (7)
3. Verification in text processing
and interpretation (6)
4. Verification of audio in text (6)
5. Automatic transcription (1)
8. Journalists
Teachers/ Professors
Health/other disciplines scientists
Computer programmers/developers
Statisticians/analysts/data scientists/ etc.
Linguists
Yes
No
The lack of economic resources, adapted structures and
specific profiles, causes of limited use of AI
*More than a third (76.5%) did not have their
own R+D+i section.
AI, an example of convergence between disciplines (Prodigioso Volcán, 2020: 54): importance of
interdisciplinary collaboration as an opportunity.
*Exceptions: Chequeado, Newtral, Maldita.es (and Aos Fatos, with specific sections
for technological innovation and multidisciplinary teams of professionals.
Does it have its R+D+i section or similar?
(17 answers)
Profile of professionals that make up teams linked to R+D+i
(4 answers)
9. Co-creation in different modalities and with various entities,
another opportunity: context of implementation of tools
Technological
innovation
projects/programs
Most arose and developed internally
by the fact-checkers.
Exceptions (3 of 14):
Collaborative
alliances within the
IFCN framework
External
collaborations in its
creation
More than half (10 of the 14) were
created and/or disseminated thanks
to alliances, collaborations or
contracts with external organizations.
The economic support of
large technology
companies such as
Facebook (3) or Google
(2), essential.
10. Changing context = limitations of the study: what the results would be like one
year later.
Double consequence of the vertiginous advance of AI, especially Generative
AI:
Final notes for discussion
1) New threats and questions. E.g. verifiers'
perception of deep fakes and other dangers of
the irresponsible use of generative AI to spread
disinformation; the effectiveness of the tools
developed by fact-checkers to verify content
generated by new AI Generative tools (that is, if
they recognize it as not real); etc.
2) New opportunities for fact-checkers. E.g.
innovations on their own development tools; incorporation
into their routines of new external AI tools; participation in
external verification/content generation AI projects as
experts or advisors: they know the questions to ask the
machines and are aware of the importance of certain “rules”
or good practices to avoid irresponsible use of these tools
by citizens or certain actors and, with it, misinformation; etc.
2023, year of AI
11. Thank you for your attention
Dra. María Sánchez González
Universidad de Málaga (and UNIA and Databeers Málaga) | m.sanchezgonzalez@uma.es
Research part of the project "The Impact of Disinformation in Journalism: Contents, Professional Routines and Audiences (DESINFOPER)”,
PID2019-108956RB-I00.
Special thanks to all fact-checking professionals and AI experts consuted.
Vectors taken from Flaticon/ Freepik.
Other authors: Dra. Hada M.Sánchez Gonzales y Sergio Martínez Gonzalo