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Information
Special Issues
Digital Literacy and Social Media: Practices, Challenges and Opportunities
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Digital Literacy and Social Media: Practices, Challenges and Opportunities

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 19655

Special Issue Editor

Dr. Ana Pérez-Escoda

E-Mail Website
Guest Editor
Faculty of Communication and Arts, Antonio de Nebrija University, 28015 Hoyo de Manzanares, Spain
Interests: digital literacy; social media; education; communication; media literacy

Special Issue Information

Dear Colleagues,

Communication has been significantly transformed in the last decade by social networks. These digital scenarios have changed human interaction, on the one hand, on a global level, given their reach all of humanity is affected, and on the other hand, in a systemic way, because they affect all human processes: personal, work, social, affective, educational, political, economic, recreational, informational, administrative, etc.

Internet growth and the exponential development of technology—big data, deep learning, artificial intelligence, IoT, etc.—have permanently and irreversibly changed our world. The flow of information, previously controlled by agencies and traditional media, as well as the flow of knowledge, previously in the hands of a few, has been opened up to the entire population so that anyone can say/publish any information, opinion, or comment. Information has consequently become the raw material of the 21st century, and its control, manipulation, interpretation, distribution, design, and production entail a potential ever known, for the good and the bad. This is shown by the phenomena of polarization, echo chambers, bubble filters, fake news, post-truth, or infodemics.

The lack of training in a context that is evolving too fast is a fact that has been noted at international level by various organisations: UNESCO, OECD, UN, WHO, etc., which stress the need for digital literacy to help the population deal with the new digitalised context and emergent issues not only related with digital competences but with critical thinking and specific skills to face challenges and benefit with opportunities.

The aim of this Special Issue is to publish original submissions related to practices, experiences, case studies or theoretical studies that, through quantitative, qualitative or mixed methodologies, provide original insights on how social networks are being used in the educational, political, informative, social, communicative, journalistic, economic, etc., fields, emphasizing how to apply digital literacy to each area.

Dr. Ana Pérez-Escoda
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • social media
  • digital communication
  • digital literacy
  • political communication
  • educational practices
  • journalism
  • polarization
  • fake news
  • digital advertising
  • international relations
  • digital journalism

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (5 papers)

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Research

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15 pages, 1532 KiB  
Article
Automated Social Media Text Clustering Based on Financial Ontologies
by Andrea Calvagna, Emiliano Tramontana and Gabriella Verga
Information 2024, 15(4), 210; https://doi.org/10.3390/info15040210 - 9 Apr 2024
Viewed by 1413
Abstract
Social media networks provide an aggregation of news and content, allowing users to share and discuss topics of greatest interest to them. Users can enrich the news by providing context and opinions that are useful to other users. Understanding topics of interest sheds [...] Read more.
Social media networks provide an aggregation of news and content, allowing users to share and discuss topics of greatest interest to them. Users can enrich the news by providing context and opinions that are useful to other users. Understanding topics of interest sheds light on the collective thinking of a group of individuals and offers important insights for exploring a given field. Among the fields of interest on social media networks, finance stands out. Automatically identifying and organizing the main issues that users discuss can be useful for multiple purposes, e.g., identifying the preferred types of loans could be useful for refining targeted advertising. Our work aims to identify and organize the topics discussed on a social media network that are related to the financial sector. For this, we propose an approach that consists of analyzing posts from Reddit communities oriented to finance. First, posts were gathered and cleaned to remove punctuation, links, and images. Then, textual similarity was computed to match posts with classes from dedicated ontologies designed for the financial sector. Finally, the populated ontology was analyzed to identify clusters of concepts. The results showed that the proposed approach and corresponding tool can summarize topics from a large number of Reddit posts using the identified classes. Over 70% of posts were linked to ontologies when considering both posts and comments, which shows that the automatic support given to posts related to financial concepts had a high degree of success. Full article
(This article belongs to the Special Issue Digital Literacy and Social Media: Practices, Challenges and Opportunities)
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14 pages, 1335 KiB  
Article
Taking on Social Media as New Gatekeepers among Young People: A Call upon Digital Literacy
by Ana Pérez-Escoda, Andrés Barrios-Rubio, Luis Miguel Pedrero-Esteban and Carolina Ávalos
Information 2024, 15(4), 180; https://doi.org/10.3390/info15040180 - 27 Mar 2024
Cited by 1 | Viewed by 3210
Abstract
Today’s public sphere is increasingly shaped by a dynamic, global, cross-cutting digital landscape, mostly ruled by social media and algorithms. Individuals are the raw material, the product, in this digital scenario, insofar as they generate and create information that coexists and is consumed [...] Read more.
Today’s public sphere is increasingly shaped by a dynamic, global, cross-cutting digital landscape, mostly ruled by social media and algorithms. Individuals are the raw material, the product, in this digital scenario, insofar as they generate and create information that coexists and is consumed alongside the information generated by the media outlets. In this context, this study focusses on an international sample from three countries (Spain, Colombia, and Costa Rica) to study the youngest information consumption, the trust they relay in media used to get informed, and their perceptions. The research was articulated from a quantitative methodological approach, focusing on a descriptive and correlational perspective. The results show interesting and innovative outcomes that point out that country origin does not constitute a significative factor when describing consumption patterns related to social media. It was confirmed in the study that these scenarios seem to become the new gatekeepers for young people, who barely consume traditional media such as press or radio broadcast. The lack of trust in the media that they consume to get informed is a matter of awareness, and digital literacy is described to be the most appropriated solution in a transformative normality in which young people do not consume information from traditional media. Full article
(This article belongs to the Special Issue Digital Literacy and Social Media: Practices, Challenges and Opportunities)
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12 pages, 984 KiB  
Article
Mobility Pattern Analysis during Russia–Ukraine War Using Twitter Location Data
by Yupei Shu, Xu Chen and Xuan Di
Information 2024, 15(2), 76; https://doi.org/10.3390/info15020076 - 27 Jan 2024
Cited by 1 | Viewed by 2344
Abstract
This paper aims to use location-based social media data to infer the impact of the Russia–Ukraine war on human mobility. We examine the impact of the Russia–Ukraine war on changes in human mobility in terms of the spatial range of check-in locations using [...] Read more.
This paper aims to use location-based social media data to infer the impact of the Russia–Ukraine war on human mobility. We examine the impact of the Russia–Ukraine war on changes in human mobility in terms of the spatial range of check-in locations using social media location data. Specifically, we collect users’ check-in location data from Twitter and analyze the average gyration of check-ins from a region across the timeline of major events associated with the war. Change-point detection is performed on these time-series check-ins to identify the timeline of abrupt changes, which are shown to be consistent with the timing of a series of sanctions and policies. We find that war-related events may contribute secondary impacts (e.g., the surge in gas prices) to users’ travel patterns. The impact of the Russia–Ukraine war on users’ travel patterns can differ based on their own scope. Our case study demonstrates that users’ gyration in Warsaw, Paris, and Berlin experienced a decrease of over 50% during periods of gas price surges. These changes in users’ gyration patterns were particularly noticeable in neighboring countries like Poland compared to the other three countries. The findings of this study can assist policymakers, regulators, and urban planners to evaluate the impact of the war and to be adaptable to city planning after the war. Full article
(This article belongs to the Special Issue Digital Literacy and Social Media: Practices, Challenges and Opportunities)
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20 pages, 4507 KiB  
Article
Cyberbullying Detection on Social Media Using Stacking Ensemble Learning and Enhanced BERT
by Amgad Muneer, Ayed Alwadain, Mohammed Gamal Ragab and Alawi Alqushaibi
Information 2023, 14(8), 467; https://doi.org/10.3390/info14080467 - 18 Aug 2023
Cited by 20 | Viewed by 7033
Abstract
The prevalence of cyberbullying on Social Media (SM) platforms has become a significant concern for individuals, organizations, and society as a whole. The early detection and intervention of cyberbullying on social media are critical to mitigating its harmful effects. In recent years, ensemble [...] Read more.
The prevalence of cyberbullying on Social Media (SM) platforms has become a significant concern for individuals, organizations, and society as a whole. The early detection and intervention of cyberbullying on social media are critical to mitigating its harmful effects. In recent years, ensemble learning has shown promising results for detecting cyberbullying on social media. This paper presents an ensemble stacking learning approach for detecting cyberbullying on Twitter using a combination of Deep Neural Network methods (DNNs). It also introduces BERT-M, a modified BERT model. The dataset used in this study was collected from Twitter and preprocessed to remove irrelevant information. The feature extraction process involved utilizing word2vec with Continuous Bag of Words (CBOW) to form the weights in the embedding layer. These features were then fed into a convolutional and pooling mechanism, effectively reducing their dimensionality, and capturing the position-invariant characteristics of the offensive words. The validation of the proposed stacked model and BERT-M was performed using well-known model evaluation measures. The stacked model achieved an F1-score of 0.964, precision of 0.950, recall of 0.92 and the detection time reported was 3 min, which surpasses the previously reported accuracy and speed scores for all known NLP detectors of cyberbullying, including standard BERT and BERT-M. The results of the experiment showed that the stacking ensemble learning approach achieved an accuracy of 97.4% in detecting cyberbullying on Twitter dataset and 90.97% on combined Twitter and Facebook dataset. The results demonstrate the effectiveness of the proposed stacking ensemble learning approach in detecting cyberbullying on SM and highlight the importance of combining multiple models for improved performance. Full article
(This article belongs to the Special Issue Digital Literacy and Social Media: Practices, Challenges and Opportunities)
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Review

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14 pages, 519 KiB  
Review
Factors Affecting the Formation of False Health Information and the Role of Social Media Literacy in Reducing Its Effects
by Kevin K. W. Ho and Shaoyu Ye
Information 2024, 15(2), 116; https://doi.org/10.3390/info15020116 - 17 Feb 2024
Cited by 6 | Viewed by 4342
Abstract
The COVID-19 pandemic heightened concerns about health and safety, leading people to seek information to protect themselves from infection. Even before the pandemic, false health information was spreading on social media. We conducted a review of recent literature in health and social sciences [...] Read more.
The COVID-19 pandemic heightened concerns about health and safety, leading people to seek information to protect themselves from infection. Even before the pandemic, false health information was spreading on social media. We conducted a review of recent literature in health and social sciences and proposed a theoretical model to understand the factors influencing the spread of false health information. Our focus was on how false health information circulated before and during the pandemic, impacting people’s perceptions of believing information on social media. We identified four possible strategies to counteract the negative effects of false health information: prebunking, refuting, legislation, and media literacy. We argue that improving people’s social media literacy skills is among the most effective ways to address this issue. Our findings provide a basis for future research and the development of policies to minimize the impact of false health information on society. Full article
(This article belongs to the Special Issue Digital Literacy and Social Media: Practices, Challenges and Opportunities)
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