Editorial: Media magic or mayhem?

OPTN/SRTR 2020 Annual Data Report: COVID

Deakin Interviews Author of "Fake News and Dinosaurs"

Fake news detection within online social media using supervised artificial intelligence algorithms

Social media (SM) is ‘the’ place individuals use to socialize, connect and share up-to-date information with other parties. According to The Uses and Gratification theory (U>), individuals have needs to satisfy to feel gratified; they use SM to satisfy these personal needs to achieve self-gratification. Gratifications differ for individuals depending on their background and types of SM medium used. Question is, what are the motives behind SM user’s activeness behaviour in their medium of choice in Malaysia’s scenario? Seven common motives, namely, watching, impressing, acting, surveillance, documentation, coolness and creativity were hypothesized to have significant influences over SM users’ activeness behaviour. The study disseminated online surveys to targeted and willing active SM users in the research; it resulted in 397 useable data for analysis. Overall, the study managed to identify four motives, namely, watching, impressing, documentation and coolness as the drivers behind activeness behaviour of SM users in Malaysia. The study also identifies FB as the most popular SM, followed by IG. Further segmentation analysis on each FB-active (n=125), IG-active (n=100) and other SM-active (n=82) found that the main motive for FB users was to impress (impressing) others; for IG users, the main reason was to watch others (watching). As for other SM-active, three motives emerged, i.e. watching, surveillance and documentation. The findings imply the usefulness of U> in explaining individual’s motives for being active SM user as well as importance of motives behind activeness of SM user’s behaviour for different types of SMs.

Ten Million Calls and Counting: Progress and Promise of Tobacco Quitlines in the U.S.

Solace in Social Media: Women Unite Under COVID-19

Fake news is a growing problem on social media and can have significant negative consequences for individuals and society owing to its accessibility, low cost, and quick distribution. It is difficult to automatically identify bogus news that defies the current content-based analysis techniques. One of the key reasons is that current NLP algorithms still lack common sense, which is frequently necessary for understanding how to read the news. Recent research has demonstrated that the propagation patterns of true and fake news differ on social media. With the potential for automatic fake news detection, this study investigates the use of Deep Learning (DL) models to detect fake news on social media. A Neural Network (NN) model was developed using Natural Language Toolkit (NLTK), TensorFlow, and Natural Language Processing (NLP) for textual analysis. The model was trained on a dataset of fake and real news articles, and was able to achieve high accuracy in identifying fake news. The results of this study suggest that DL models can be valuable tools for detecting fake news on social media.

Aims: Individuals use social media for various health-related purposes, such as gathering information about their illnesses, contacting healthcare professionals, learning about other patients’ experiences with doctors, and making informed decisions when selecting doctors. The aims of this study are (I) to evaluate orthopaedic patients’ utilisation of social media and (II) to ascertain the factors that are of greatest importance to patients in relation to orthopaedic surgeons’ social media accounts. Methods: A cross-sectional study was conducted with a total of 1018 patients in the orthopaedic outpatient department between November and December 2023. Patients filled out a questionnaire consisting of 15 questions about patients’ personal information (gender, age, and education level), social media preferences, social media experiences, and the content of orthopaedic surgeons’ social media accounts. Results: 80.4% of the orthopedic patients surveyed were actively using at least one social media platform. Within the group of social media users, Instagram stood out as the most preferred platform, with a usage rate of 82.4%. Patients reported that 45.8% believe it is essential for doctors to maintain a presence on social media Patients were most interested (65.1%) in educational videos on orthopaedic surgeons’ social media accounts. Conclusion: The vast majority of orthopaedic patients are active users of social media, and a significant proportion of orthopaedic patients would like their doctors to have a social media presence. Orthopaedic surgeons should adapt their social media strategies to align with their patient population in order to effectively reach and engage with them.

The aim of this study was to explore the challenges and strategies for improving health information delivery by healthcare professionals (HCPs) on lifestyle behaviours using social media. Using a phenomenological qualitative study design, data were gathered through semi-structured interviews with 22 HCPs who use social media to deliver health information, and three focus group discussions with 16 active users of social media. All participants were based in Malaysia. The sessions were audiotaped and transcribed verbatim. Data were analysed using constant comparative approach and thematic analysis. Five themes emerged: (i) credibility of health information, (ii) accessibility, and timeliness of health information, (iii) attitudes and motivation of HCPs, (iv) users' receptiveness to health information, and (v) availability of resources for HCPs. HCPs were encouraged to show commitment when delivering information, ensuring users receive information in the most engaging way. It was also suggested that HCPs access resources through collaboration with HCPs and non-HCP individuals, including digital content creators and health advocates. In conclusion, this qualitative study provides insights into the perspectives of HCPs and social media users regarding the use of social media by HCPs to deliver health information on lifestyle behaviours. These insights can be used to improve health communication on social media.

Trust, authority and credibility in the digital environment have attracted the interest of many researchers in the recent years. Reliable and credible information are key factors for making numerous decisions in our everyday lives, from making political choices to choosing a healthy lifestyle. Various health-related narratives are present in the public sphere. Health advice and recommendations on vaccination, antibiotics, nutrition, exercise and numerous other topics are provided by different sources, scientific community, healthcare professionals, media, lay people, patients, social networks, etc. It was the infodemic associated with the coronavirus pandemic that again brought to the forefront the importance of reliable and credible health information and health information literacy in this complex digital environment. In such fragmented information ecosystem, characterized by the post-truth era, where misinformation and fake news spread by uninformed individuals or advocates of various conspiracy theories are considered equivalent to reliable scientific information, individuals have to choose whom to trust, based on their critical capacities and competencies, in order to make health decisions for themselves and their families. The young people of today, especially those born after the year 2000, represent the generation of digital natives, who grew up and spent their entire lives surrounded by digital technologies that have become an integral part of their lives. They think and process information differently than their predecessors. Most of them use the Internet as their primary source for accessing information, most often through smartphones, spend the vast majority of time online, increasingly use social networks for private and professional purposes, but at the same time have difficulty assessing the reliability of online information. The way they assess trust in digital information is different from the way they question information credibility in traditional media. Given that trust and credibility of information strongly influence the effect of information message itself, which, in extraordinary circumstances and public health crisis such as the coronavirus pandemic, is of vital importance for the lives of people, it is very important to understand how users decide whom to trust. Health information literacy is a multidimensional and dynamic concept that incorporates social, cognitive, economic, and personal skills to search, understand, and use health information in order to improve and maintain good health. The evaluation of online health information, i.e. its reliability and credibility, plays a significant role in the process of health behavior change. Research to date has not reached a consensus on unique framework for understanding the process of building user confidence in online health information. The focus of this doctoral dissertation are theoretical and analytical challenges of health information literacy as a multidimensional and dynamic concept, particularly in understanding the process of creating trust in online health information. By examining the attitudes and opinions of medical students about the evaluation of online health information we aimed to determine factors that influence the assessment of health information quality and credibility. The main research objective is to examine the element of information appraisal in the concept of health information literacy and to determine the processes of creating trust in health information in an online environment. The specific research objectives are as follows: 1. to identify factors and techniques for assessing the quality, reliability and credibility of online health information; 2. to determine the elements of cognitive heuristics for assessing the reliability of online health information; 3. to determine the impact of infodemic during a healthcare crisis on online health information trust issues; 4. to examine methods for assessing the quality and reliability of user-generated online health information; 5. to investigate medical students' attitudes and knowledge of the concepts and tools for assessing health information literacy. Our research aimed to determine common elements of information appraisal in the concept of health information literacy and related concepts dealing with online health information (health literacy, information literacy, media literacy, digital literacy, etc.). The research was performed using multiple methods conducted in three phases: 1. literature review and comparative analysis of selected tools and instruments for assessment of health information literacy and related concepts; 2. a survey questionnaire that examined the attitudes and opinions of medical students of the University of Zagreb School of Medicine regarding online health information appraisal, and 3. semi-structured interviews with a smaller subgroup of respondents in order to build on the findings from the survey questionnaire related to the determination of factors that influence trust in online health information, i.e. assessment of their quality and credibility. The results of our research demonstrated that medical students have the knowledge, skills and techniques necessary to assess the quality, reliability and credibility of online health information. Although medical students generally considered Internet to be a questionable source for health information, the majority reported that they always use online search engines as the first step when searching for health topics, regardless of their purpose (general interest, academic assignment, or personal or health problem among family and friends, etc.). Medical students consider the following analytical criteria when assessing the credibility of online health information: trustworthiness, completeness, objectivity and comprehensiveness of information, referencing other data sources and author disclosure. Apart from analytical criteria, medical students also use cognitive heuristics when assessing the reliability of online health information, especially user-generated content that is published and shared via social networks. Students also emphasized the importance of critical thinking, factual analysis, information verification on multiple sources, determination of source credentials as well as sharing information with family members, friends, colleagues, physicians and university professors who they consider as cognitive authorities in health communication. Research results indicate an overall positive relationship between perceived health information literacy of medical students, their ability to evaluate online health information and trust in the Internet as a source of health information. Students with high self-perceived level of e-health literacy more often use websites of government institutions and professional medical associations than other sources for online health information. Our research also revealed that the degree of trust that medical students have in online sources of information affects their behavior when searching and evaluating online health information. In healthcare crisis situations, medical students apply additional evaluation criteria for usergenerated health information on social media. In general, medical students expressed mistrust towards social networks, especially as a source of credible health information in the context of an infodemic. Although the majority of students use social networks only passively, they also believe that social networks present a platform that has the potential, if used appropriately, to convey reliable information and improve health information literacy. Students also stressed that, during infodemic, strategic crisis communication skills should be applied for proactive dissemination of credible, factual and scientific evidence in order to contribute to a faster and more efficient containment of the spread of misinformation and fake news on social media. The results of our research have shown that online health information should be comprehensive, accurate, evidence-based, objective and up-to-date in order to convey a quality health message. According to medical students, quality of information, source credibility, comprehensibility and readability, as well as verification of information in evidence-based sources are main predictors of trust in online health information. Understanding which health channels and sources are considered most reliable among different user groups can help health professionals reach at-risk patients in order to communicate health messages more successfully and implement interventions aimed at strengthening skills that are important for health information appraisal. By analyzing medical students` attitudes and opinions about credibility of online health information, we explored ways to promote critical thinking in the digital environment in order to empower individuals to make decisions in their everyday life based on verified and credible sources of information. Placing greater emphasis on lifelong learning about health, and formal and informal health information literacy education, enables greater autonomy and empowerment of individuals, and can be viewed as part of personal development towards an improved quality of life. Health information literacy increases individual and community resistance to harmful and misleading information and reduces the impact of the infodemic on human health. Improving health information literacy among population requires joint action and cooperation between stakeholders and policymakers (government authorities, media, scientific, educational and health institutions, healthcare professionals, scientists, researchers, librarians and others). Health information literacy is an important competence of every individual, but its implications for society are much broader. They include personal and social responsibility of individuals and taking ethical actions for the benefit of the community. A modern democratic society implies engaged citizens who autonomously reflect on political, ethical and social challenges in everyday life. Empowerment in health and social care, achieved by developing critical competencies, helps in distancing oneself from various social pressures, making independent informed decisions and taking responsibility for one's own health. Croatia, unlike most other European countries, still does not have an official strategy or action plan for developing and improving health information literacy among its population. Our research results point out the importance of including health information literacy in the national health policy and education strategy, with particular emphasis on developing critical thinking skills and competencies in evidence-based approach to online health information appraisal. The results of this research contribute to the conceptual linking of theoretical constructs on information appraisal and critical theories from information and communication sciences with constructs from the field of public health. The mentioned approach resulted in unifying the narratives of different domains, and synthesizing separate theoretical frameworks, namely health information and related literacies, which adds to the value of this research. The results of this research serve as a basis for defining skills for critical appraisal of online health information in order to increase the level of health information literacy and development of tools for evaluating the reliability of online health information. On the applicative level, this doctoral dissertation provides recommendations for communication of reliable online health information from the current infodemic perspective, in planning public health activities and interventions in the future.

People lie, actions Don't! Modeling infodemic proliferation predictors among social media users

PurposeThis study aims to understand the allure and danger of fake news in social media environments and propose a theoretical model of the phenomenon.Design/methodology/approachThis qualitative research study used the uses and gratifications theory (UGT) approach to analyze how and why people used social media during the 2016 US presidential election.FindingsThe thematic analysis revealed people were gratified after using social media to connect with friends and family and to gather and share information and after using it as a vehicle of expression. Participants found a significant number of fake news stories on social media during the 2016 US presidential election. Participants tried to differentiate between fake news and real news using fact-checking websites and news sources and interacted with the social media users who posted fake news and became part of the echo chamber. Behaviors like these emerged in the analysis that could not be completely explained by UGT and required further exploration which resulted in a model that became the core of this study.Research limitations/implicationsThis is a small-scale exploratory study with eight diverse participants, findings should not be generalized to larger populations. Time-specific self-reporting of information from social media and fake news during the 2016 US presidential election. Upgrading public policies related to social media is recommended in the study, contributing to burgeoning policy discussions and provides recommendations for both purveyors of social media and public policymakers.Practical implicationsUpgrade in public policies related to social media is recommended in the study and contributes to burgeoning policy discussions and provides recommendations for both purveyors of social media and public policymakers.Social implicationsSocial media users are spending increased time on their preferred platforms. This study increases the understanding of the nature, function and transformation of virtual social media environments and their effects on real individuals, cultures and societies.What is original/of value about the paper?This exploratory study establishes the foundation on which to expand research in the area of social media use and fake news.Originality/valueThis exploratory study establishes the foundation to expand research in the area of social media use and fake news.

The availability and expansion of social media has made it difficult to distinguish between fake and real news. Information falsification has exponentially increased as a result of how simple it is to spread information through sharing. Social media dependability is also under jeopardy due to the extensive dissemination of false information. Therefore, it has become a research problem to automatically validate information, specifically source, content, and publisher, to identify it as true or false. Despite its limitations, machine learning (ML) has been crucial in the categorization of information. Previous studies suggested three-step methods for categorising false information on social media. In the first step of the process, the data set is subjected to a number of pre-processing processes in order to transform unstructured data sets into structured data sets. The unknowable properties of fake news and the features are extracted by the Lexicon Model in the second stage. In the third stage of this research project, a feature selection method by WOA (Whale Optimization Algorithm) for weight value to tune the classification part. Finally, a Hybrid Classification model that is hybrid with a fuzzy based Convolutional Neural Network and kernel based support vector machine is constructed in order to identify the data pertaining to bogus news. However using single classifier for fake news detection produces the insufficient accuracy. To overcome this issue in this work introduced an improved model for fake news classification. To turn unstructured data sets into structured data sets, a variety of pre-processing operations are used on the data set in the initial phase of the procedure. The unknowable properties of fake news and the features are extracted by the Lexicon Model in the second stage. In the third stage of this research project, a feature selection method by COA (Coati Optimization Algorithm) for weight value to tune the classification part. Finally, an ensemble of RNN (Recurrent Neural Networks), VGG-16 and ResNet50.A classification model was developed to recognise bogus news information. Evaluate each fake news analysis' performance in terms of accuracy, precision, recall, and F1 score. The suggested model, out of all the methodologies taken into consideration in this study, provides the highest outcomes, according to experimental findings

Since the outbreak of COVID-19, social media plays an important role to circulate pandemic news around the world. Some malevolent users may take an advantage of this and spread fake news to attract people for business and research purposes. In this paper, we take an approach by applying existing machine learning algorithms to detect fake news in social media and show a comparison of their performances. In our study, the support vector classifier (SVC) outperforms the rest of the classifiers based on different statistical metrics. Therefore, the SVC classifier has been considered as our proposed classifier model to identify fake COVID-19 news in social media. Two word clouds have also been generated based on the appearance of words in the news that shows an insignificant difference between true and fake news.

Head is Where the Herd is: Fake News and Effect of Online Social Conformity on Islamophobia in Indians