Novel technologies and Geopolitical Strategies: Disinformation Narratives in the Countries of the Visegrád Group

Abstract In the current media environment of growing information disorder and social media platforms emerging as primary news sources, the creation and spread of disinformation is becoming increasingly easy and cost-effective. The projection of strategic narratives through disinformation campaigns is an important geopolitical tool in the global competition for power and status. We have analysed close to 1,000 individual news pieces from more than 60 different online sources containing disinformation, which originally appeared in one of the V4 languages, using a natural language processing algorithm. We have assessed the frequency of recurring themes within the articles and their relationship structure, to see whether consistent disinformation narratives were to be found among them. Through frequency analysis and relationship charting, we have been able to uncover individual storylines connected to more than ten overarching disinformation narratives. We have also exposed five key meta-narratives present in all Visegrád Countries, which fed into a coherent system of beliefs, such as the envisioned collapse of the European Union or the establishment of a system of Neo-Atlantism, which would permanently divide the continent.

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Detection of Radicalisation and Extremism Online: A Survey

10.21203/rs.3.rs-1185415/v1 ◽

2022 ◽

Author(s):

Irfan Tanoli ◽

Sebastião Pais ◽

João Cordeiro ◽

Muhammad Luqman Jamil

Keyword(s):

Social Media ◽

Sentiment Analysis ◽

Language Processing ◽

Opinion Mining ◽

Probabilistic Methods ◽

Automatic Identification ◽

News Sources ◽

Independent Information ◽

Social Media Platforms ◽

The Subject

Abstract Introduction: Due to the lack of regulation, the large volume of user-generated online content reflects more closely the offline world than official news sources. Therefore, social media platforms have become an attractive space for anyone seeking independent information. One of the main goals of this work is to clarify concepts such as Extremism and Collective Radicalisation, Social Media, Sentiments/Emotions/Opinions Analysis, as well as the combinations of all of them. Methods: The automatic identification of extremism and collective radicalisation requires sophisticated Natural Language Processing (NLP) methods and resources, especially those dealing with opinions, emotions or sentiment analysis. Text mining and knowledge extraction are also crucial, in particular, directed toward social media and micro-blogging. Results: The present document comprehends a study on theoretical material, focusing on the main concepts of the subject, including the main problems and challenges, from the different areas that compose online radicalisation research. Understanding and detecting extremism and collective radicalism online has a connection to sentiment analysis and opinion mining. There are many barriers to understanding extremism and collective radicalisation; one is to differentiate between who is really engaged in the process and who is just eventually talking about it. Conclusions: The other focus of this work is to find the best ways to identify extremism and collective radicalisation on the internet, using sentiment analysis and focusing on probabilistic methods to create an unsupervised and language-independent approach.

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Intelligent Detection of False Information in Arabic Tweets Utilizing Hybrid Harris Hawks Based Feature Selection and Machine Learning Models

Symmetry ◽

10.3390/sym13040556 ◽

2021 ◽

Vol 13 (4) ◽

pp. 556

Author(s):

Thaer Thaher ◽

Mahmoud Saheb ◽

Hamza Turabieh ◽

Hamouda Chantar

Keyword(s):

Machine Learning ◽

Social Media ◽

Feature Selection ◽

Language Processing ◽

User Profile ◽

Vital Role ◽

Classification Model ◽

Fake News ◽

False Information ◽

Social Media Platforms

Fake or false information on social media platforms is a significant challenge that leads to deliberately misleading users due to the inclusion of rumors, propaganda, or deceptive information about a person, organization, or service. Twitter is one of the most widely used social media platforms, especially in the Arab region, where the number of users is steadily increasing, accompanied by an increase in the rate of fake news. This drew the attention of researchers to provide a safe online environment free of misleading information. This paper aims to propose a smart classification model for the early detection of fake news in Arabic tweets utilizing Natural Language Processing (NLP) techniques, Machine Learning (ML) models, and Harris Hawks Optimizer (HHO) as a wrapper-based feature selection approach. Arabic Twitter corpus composed of 1862 previously annotated tweets was utilized by this research to assess the efficiency of the proposed model. The Bag of Words (BoW) model is utilized using different term-weighting schemes for feature extraction. Eight well-known learning algorithms are investigated with varying combinations of features, including user-profile, content-based, and words-features. Reported results showed that the Logistic Regression (LR) with Term Frequency-Inverse Document Frequency (TF-IDF) model scores the best rank. Moreover, feature selection based on the binary HHO algorithm plays a vital role in reducing dimensionality, thereby enhancing the learning model’s performance for fake news detection. Interestingly, the proposed BHHO-LR model can yield a better enhancement of 5% compared with previous works on the same dataset.

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Avenues to News and Diverse News Exposure Online: Comparing Direct Navigation, Social Media, News Aggregators, Search Queries, and Article Hyperlinks

The International Journal of Press/Politics ◽

10.1177/19401612211009160 ◽

2021 ◽

pp. 194016122110091

Author(s):

Magdalena Wojcieszak ◽

Ericka Menchen-Trevino ◽

Joao F. F. Goncalves ◽

Brian Weeks

Keyword(s):

Social Media ◽

Search Engines ◽

Direct Access ◽

Data Set ◽

Individual Level ◽

News Sources ◽

Internet Users ◽

News Websites ◽

The Us ◽

Social Media Platforms

The online environment dramatically expands the number of ways people can encounter news but there remain questions of whether these abundant opportunities facilitate news exposure diversity. This project examines key questions regarding how internet users arrive at news and what kinds of news they encounter. We account for a multiplicity of avenues to news online, some of which have never been analyzed: (1) direct access to news websites, (2) social networks, (3) news aggregators, (4) search engines, (5) webmail, and (6) hyperlinks in news. We examine the extent to which each avenue promotes news exposure and also exposes users to news sources that are left leaning, right leaning, and centrist. When combined with information on individual political leanings, we show the extent of dissimilar, centrist, or congenial exposure resulting from each avenue. We rely on web browsing history records from 636 social media users in the US paired with survey self-reports, a unique data set that allows us to examine both aggregate and individual-level exposure. Visits to news websites account for about 2 percent of the total number of visits to URLs and are unevenly distributed among users. The most widespread ways of accessing news are search engines and social media platforms (and hyperlinks within news sites once people arrive at news). The two former avenues also increase dissimilar news exposure, compared to accessing news directly, yet direct news access drives the highest proportion of centrist exposure.

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Comparative Assessment of the Built-Up Area Expansion Based on Corine Land Cover and Landsat Datasets: A Case Study of a Post-Socialist City

Remote Sensing ◽

10.3390/rs12132137 ◽

2020 ◽

Vol 12 (13) ◽

pp. 2137 ◽

Cited By ~ 1

Author(s):

Ilinca-Valentina Stoica ◽

Marina Vîrghileanu ◽

Daniela Zamfir ◽

Bogdan-Andrei Mihai ◽

Ionuț Săvulescu

Keyword(s):

Land Cover ◽

Urban Expansion ◽

Ground Truth ◽

Cost Effective ◽

Planning System ◽

The European Union ◽

Scale Level ◽

Corine Land Cover ◽

Macro Scale ◽

Area Expansion

Monitoring uncontained built-up area expansion remains a complex challenge for the development and implementation of a sustainable planning system. In this regard, proper planning requires accurate monitoring tools and up-to-date information on rapid territorial transformations. The purpose of the study was to assess built-up area expansion, comparing two freely available and widely used datasets, respectively, Corine Land Cover and Landsat, to each other, as well as the ground truth, with the goal of identifying the most cost-effective and reliable tool. The analysis was based on the largest post-socialist city in the European Union, the capital of Romania, Bucharest, and its neighboring Ilfov County, from 1990 to 2018. This study generally represents a new approach to measuring the process of urban expansion, offering insights about the strengths and limitations of the two datasets through a multi-level territorial perspective. The results point out discrepancies between the datasets, both at the macro-scale level and at the administrative unit’s level. On the macro-scale level, despite the noticeable differences, the two datasets revealed the spatiotemporal magnitude of the expansion of the built-up area and can be a useful tool for supporting the decision-making process. On the smaller territorial scale, detailed comparative analyses through five case-studies were conducted, indicating that, if used alone, limitations on the information that can be derived from the datasets would lead to inaccuracies, thus significantly limiting their potential to be used in the development of enforceable regulation in urban planning.

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The Effectiveness and Cost-Effectiveness of Hepatitis C Screening for Migrants in the EU/EEA: A Systematic Review

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15092013 ◽

2018 ◽

Vol 15 (9) ◽

pp. 2013 ◽

Cited By ~ 12

Author(s):

Christina Greenaway ◽

Iuliia Makarenko ◽

Claire Abou Chakra ◽

Balqis Alabdulkarim ◽

Robin Christensen ◽

...

Keyword(s):

Cost Effectiveness ◽

Hepatitis C ◽

Lower Risk ◽

Linkage To Care ◽

Cost Effective ◽

Screening Tests ◽

European Economic Area ◽

The European Union ◽

Wide Range ◽

The Eu

Chronic hepatitis C (HCV) is a public health priority in the European Union/European Economic Area (EU/EEA) and is a leading cause of chronic liver disease and liver cancer. Migrants account for a disproportionate number of HCV cases in the EU/EEA (mean 14% of cases and >50% of cases in some countries). We conducted two systematic reviews (SR) to estimate the effectiveness and cost-effectiveness of HCV screening for migrants living in the EU/EEA. We found that screening tests for HCV are highly sensitive and specific. Clinical trials report direct acting antiviral (DAA) therapies are well-tolerated in a wide range of populations and cure almost all cases (>95%) and lead to an 85% lower risk of developing hepatocellular carcinoma and an 80% lower risk of all-cause mortality. At 2015 costs, DAA based regimens were only moderately cost-effective and as a result less than 30% of people with HCV had been screened and less 5% of all HCV cases had been treated in the EU/EEA in 2015. Migrants face additional barriers in linkage to care and treatment due to several patient, practitioner, and health system barriers. Although decreasing HCV costs have made treatment more accessible in the EU/EEA, HCV elimination will only be possible in the region if health systems include and treat migrants for HCV.

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Electronic Health Use in the European Union and the Effect of Multimorbidity: Cross-Sectional Survey (Preprint)

10.2196/preprints.7299 ◽

2017 ◽

Author(s):

Francisco Lupiáñez-Villanueva ◽

Dimitra Anastasiadou ◽

Cristiano Codagnone ◽

Roberto Nuño-Solinís ◽

Maria Begona Garcia-Zapirain Soto

Keyword(s):

Health Care Professionals ◽

Online Survey ◽

New Technologies ◽

Cost Effective ◽

Health Problems ◽

Exploratory Research ◽

The European Union ◽

Cross Sectional Survey ◽

Cross Sectional ◽

Electronic Health

BACKGROUND Multimorbidity is becoming increasingly common and is a leading challenge currently faced by societies with aging populations. The presence of multimorbidity requires patients to coordinate, understand, and use the information obtained from different health care professionals, while simultaneously striving to distinguish the symptoms of different diseases and self-manage their sometimes conflicting health problems. Electronic health (eHealth) tools provide a means to disseminate health information and education for both patients and health professionals and hold promise for more efficient and cost-effective care processes. OBJECTIVE The aim of this study was to analyze the use of eHealth tools, taking into account the citizens’ sociodemographic and clinical characteristics, and above all, the presence of multimorbidity. METHODS Cross-sectional and exploratory research was conducted using online survey data from July 2011 to August 2011. Participants included a total of 14,000 citizens from 14 European countries aged 16 to 74 years, who had used an eHealth tool in the past 3 months. The variables studied were sociodemographic variables of the participants, the questionnaire items assessing the frequency of using eHealth tools, the degree of morbidity, and the eHealth adoption gradient. Chi-square tests were conducted to examine the relationship between the sociodemographic and clinical variables of participants and the group the participants were assigned to according to their frequency of eHealth use (eHealth user group). A one-way analysis of variance (ANOVA) allowed for assessing the differences in the eHealth adoption gradient average between different groups of individuals according to their morbidity level. A two-way between-groups ANOVA was performed to explore the effects of multimorbidity and age group on the eHealth adoption gradient. RESULTS According to the eHealth adoption gradient, most participants (68.15%, 9541/14,000) were labeled as rare users, with the majority of them (55.1%, 508/921) being in the age range of 25 to 54 years, with upper secondary education (50.3%, 464/921), currently employed (49.3%, 454/921), and living in medium-sized cities (40.7%, 375/921). Results of the one-way ANOVA showed that the number of health problems significantly affected the use of eHealth tools (F2,13996=11.584; P<.001). The two-way ANOVA demonstrated that there was a statistically significant interaction between the effects of age and number of health problems on the eHealth adoption gradient (F4,11991=7.936; P<.001). CONCLUSIONS The eHealth adoption gradient has proven to be a reliable way to measure different aspects of eHealth use. Multimorbidity is associated with a more intense use of eHealth, with younger Internet users using new technologies for health purposes more frequently than older groups with the same level of morbidity. These findings suggest the need to consider different strategies aimed at making eHealth tools more sensitive to the characteristics of older populations to reduce digital disadvantages.

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A 2019. évi ARIA kezelési irányelvek magyar adaptációja és a hazai alkalmazás lehetőségei allergiás rhinitisben

Orvosi Hetilap ◽

10.1556/650.2020.31919 ◽

2020 ◽

Vol 161 (49) ◽

pp. 2059-2071

Author(s):

Helga Kraxner ◽

Andor Hirschberg ◽

Kristóf Nékám

Keyword(s):

Health Care ◽

Allergic Rhinitis ◽

Mobile Health ◽

Health Care Systems ◽

Cost Effective ◽

Allergic Diseases ◽

The European Union ◽

Sentinel Network ◽

Intranasal Corticosteroids ◽

Care Systems

Összefoglaló. Az allergiás betegségekben szenvedő emberek száma világszerte, köztük Magyarországon is növekszik. Az egészségügyi ellátórendszerek azon dolgoznak, hogy minél hatékonyabban tudják felhasználni a rendelkezésre álló forrásokat. Az Allergic Rhinitis and its Impact on Asthma (ARIA) szervezet célja az allergiás náthában szenvedő betegek ellátásának javítása, szakmai ajánlások készítése, aktualizálása. Ennek egyik módja integrált betegellátási utak kidolgozása. Célunk ezek hazai elérhetővé tétele, az ajánlások széles körű elterjesztése az Európai Unió (EU) többi tagállamához hasonlóan Magyarországon is. Az ARIA más nemzetközi innovatív szervezetek bevonásával olyan integrált betegellátási utakat fejlesztett ki, amelyek allergiás nátha, esetleg társbetegsége, az asztma esetén támogatják a kezelést. Ezeket újgenerációs irányelvek kidolgozása útján alkották, amelyekhez felhasználták a mobiltechnológiából és pollenkamra-vizsgálatokból származó valós evidenciákat is. A gyógyszeres terápia optimalizálásához a vizuális analóg skálán alapuló, úgynevezett Mobil Légúti Figyelő Hálózat algoritmusát digitalizálták, és valós evidenciák felhasználásával tovább finomították. Allergén immunterápiára az ARIA a világon elsőként dolgozott ki integrált betegellátási utakat 2019-ben. A kezelési irányelvekhez való adherenciaszint alacsony, a betegek a tüneteik erőssége alapján módosítják a kezelést. A flutikazon-propionát–azelasztin kombináció hatása erősebb az intranasalis kortikoszteroidokénál, míg az utóbbi hatásosabb az oralis H1-antihisztaminoknál. A mobiltelefonokban tárolt elektronikus napló vagy más ’mobile health’ (mHealth) eszközök használata segíti a betegek kiválasztását allergén immunterápiára. Az ARIA által javasolt algoritmus megfelelőnek mutatkozott az allergiás rhinitis kezelésére, ezért ezek az irányelvek bekerülnek integrált betegellátási utakba, és részét fogják képezni az EU Egészségügyi és Élelmiszer-biztonsági Főigazgatósága digitalizált, személyközpontú gondozási anyagainak. Az allergén immunterápia hatékony az inhalatív allergének által okozott allergiás betegségekben, alkalmazását azonban korlátozni kell gondosan válogatott betegekre. Orv Hetil. 2020; 161(49): 2059–2071. Summary. The number of allergic patients is increasing all over the world, also in Hungary. Delivering effective and cost-effective health care is essential for all health care systems. ARIA (Allergic Rhinitis and its Impact on Asthma) aims to improve the care of patients who suffer from allergic rhinitis by setting up guidelines and updating them. Development of ICPs (integrated care pathways) can play an essential role in attaining this goal. Our aim is to make ICP-s developed by ARIA available also in Hungary, as is already the case in other countries of the European Union (EU). Together with other international initiatives, ARIA has worked out digitally-enabled ICPs to support care in allergic rhinitis and comorbid asthma. ICPs are based on new-generation guidelines using RWE (real-world evidence) from chamber studies and mobile technology. The MASK (Mobile Airways Sentinel NetworK) algorithm – based on visual analogue scale – was digitalized to support pharmacotherapy, and was refined by using RWE. ARIA was the first to develop ICPs for allergen immunotherapy (AIT) in 2019. Based on MASK data, patients did not follow guidelines and their adherence to treatment was poor. Patients would modify their treatments, depending on the disease control. The effect of fluticasone propionate–azelastine combination is superior to intranasal corticosteroids which are superior to oral H1-antihistamines. Electronic diaries obtained from cell phones and other ’mobile health’ (mHealth) devices help select patients for AIT. The ARIA algorithm for AR was found appropriate and no change is necessary. These guidelines will inform ICPs and will be included in the DG Santé digitally-enabled, person-centred care system. AIT is an effective treatment for allergic diseases caused by inhaled allergens. Its use should, however, be restricted to carefully selected patients. Orv Hetil. 2020; 161(49): 2059–2071.

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Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a Dutch cultural controversy on Twitter

PLoS ONE ◽

10.1371/journal.pone.0256696 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0256696

Author(s):

Anna Keuchenius ◽

Petter Törnberg ◽

Justus Uitermark

Keyword(s):

Machine Learning ◽

Social Media ◽

Network Analysis ◽

Language Processing ◽

User Interaction ◽

User Interactions ◽

Online Interactions ◽

Network Analyses ◽

Social Media Platforms ◽

Signed Network

Despite the prevalence of disagreement between users on social media platforms, studies of online debates typically only look at positive online interactions, represented as networks with positive ties. In this paper, we hypothesize that the systematic neglect of conflict that these network analyses induce leads to misleading results on polarized debates. We introduce an approach to bring in negative user-to-user interaction, by analyzing online debates using signed networks with positive and negative ties. We apply this approach to the Dutch Twitter debate on ‘Black Pete’—an annual Dutch celebration with racist characteristics. Using a dataset of 430,000 tweets, we apply natural language processing and machine learning to identify: (i) users’ stance in the debate; and (ii) whether the interaction between users is positive (supportive) or negative (antagonistic). Comparing the resulting signed network with its unsigned counterpart, the retweet network, we find that traditional unsigned approaches distort debates by conflating conflict with indifference, and that the inclusion of negative ties changes and enriches our understanding of coalitions and division within the debate. Our analysis reveals that some groups are attacking each other, while others rather seem to be located in fragmented Twitter spaces. Our approach identifies new network positions of individuals that correspond to roles in the debate, such as leaders and scapegoats. These findings show that representing the polarity of user interactions as signs of ties in networks substantively changes the conclusions drawn from polarized social media activity, which has important implications for various fields studying online debates using network analysis.

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P112 SMILE: Sustaining Medical Education In a Lockdown Environment.Using social media to develop a free online access medical education platform during lockdown

BJS Open ◽

10.1093/bjsopen/zrab032.111 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

Author(s):

John Pascoe ◽

Paul Foster ◽

Muntasha Quddus ◽

Angeliki Kosti ◽

Francesca Guest ◽

...

Keyword(s):

Social Media ◽

Medical Education ◽

Online Survey ◽

Cost Effective ◽

User Comments ◽

Surgical Trainees ◽

Social Media Platforms ◽

Online Access ◽

Education Platform

Abstract Introduction SMILE is a free online access medical education (FOAMEd) platform created by two UK surgical trainees and a medical student that delivered over 200 medical lectures during lockdown. Method The role of Social Media in the development of SMILE was interrogated using a survey sent to all SMILE participants and by analysing activity on SMILE social media platforms. Results 1306 students responded to the online survey with 57.2% saying they heard of SMILE through Facebook. Engagement using facebook remained highest with 13,819 members, over 800 user comments and >16,000 user reactions. 4% of the students heard of SMILE through Twitter or Instagram. Facebook analytics revealed the highest level of traffic when lectures were most commonly held suggesting students used Facebook to access lectures. Other educators were able to find SMILE on social media, leading to collaborations with other platforms. Throughout the survey many mentioned how social media created and maintained a community of medical students enhancing group-based learning Conclusions We demonstrate that social media platforms provide popular and cost-effective methods to promote, sustain & deliver medical education for students and educators.

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Understanding Language Features in Loneliness Forum Posts that Elicit Comments (Preprint)

10.2196/preprints.32756 ◽

2021 ◽

Author(s):

Anietie Andy

Keyword(s):

Language Processing ◽

Latent Dirichlet Allocation ◽

Well Being ◽

Time Of Day ◽

Online Forums ◽

Cohen’S D ◽

Increased Risk ◽

Social Media Platforms ◽

Cohen's D ◽

To Receive

BACKGROUND Loneliness is a threat to the well-being of individuals and in older adults is associated with increased risk of early mortality. Studies have shown that some individuals seek support around loneliness on online forums/social media platforms. A common challenge in online forums is that some posts do not receive comments. In some non-health related forums, posts not receiving comments may not be a serious concern, however, in an online health forum such as those focused on discussions around loneliness, posts not receiving comments could translate to individuals seeking support around loneliness not receiving adequate support. OBJECTIVE The aim of this work is to analyze posts published on an active online forum focused on discussions around loneliness (loneliness forum) to determine the language features associated with posts that elicit comments from members of the forum. METHODS For the analysis in this work, 15,012 posts published on an online loneliness forum by 9,956 users were analyzed. Of these posts, 6,450 received five or more comments, 13,221 received one or more comments, and 1,791 received no comments. Using the natural language processing method, latent dirichlet allocation (LDA) and a psycholinguistic dictionary, Linguistics Inquiry and Word Count (LIWC), the language features expressed in posts that elicit comments from members of the forum were determined. RESULTS The findings from this work show that posts related to topics themes on relationships (Cohen’s D = 0.319) and the use of negation words (Cohen’s D = 0.149) tend to receive one or more comments. Also, posts associated with LIWC categories on first person singular pronouns (Cohen’s D = 0.264) tend to elicit one or more comments. Posts on topic themes related to spending time around holidays/birthdays/year/time of day or week (Cohen’s D = 0.79) and affection relative to relationships (Cohen’s D = 0.102) tend to receive five or more comments. CONCLUSIONS This work identifies language features expressed in loneliness forum posts that elicit comments. The findings from this work can provide members of online loneliness forums tips on how to write posts that potentially elicit comments from members of the forum.

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