Erratum: Is global health truly global? A hashtag analysis of #GlobalHealth disparities on X by Frontiers Production Office

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Paradox in Disaster Management: 2020 Aegean Sea Earthquake by Alper Bilgili, Gaye Sanatcı Aktaş

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Elite in social networks: new forms of feedback in the digital age by O. V. Kryshtanovskaya

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Internet communities by R. V. Bolgov

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Analisis Sentimen Wacana Pemindahan Ibu Kota Indonesia Menggunakan Algoritma Support Vector Machine (SVM) by Primandani Arsi, Retno Waluyo

“…Dewasa ini, media sosial berkembang pesat di internet, salah satu yang banyak digemari adalah Twitter. Berbagai topik ramai diperbincangkan di Twitter mulai dari ekonomi, politik, sosial, budaya, hukum dan lain-lain. …”
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Analisis Dampak Kabut Asap dari Kebakaran Hutan dan Lahan dengan Pendekatan Text Mining by Zuliar Efendi, Imas Sukaesih Sitanggang, Lailan Syaufina

“…Data Twitter dapat dianalisis menggunakan text mining. …”
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تغریدات الأرشیفات الوطنیة والمکتبات والمتاحف عبر تویتر على شبکة الانترنت :دراسة تحلیلیة by د.عبد الحمید ندا

“…This study discusses national archives and libraries of the USpresidential and museums Tweets across the Twitter online analyticalstudy and what can these tweets providing services for the NationalArchives and beneficiaries at the same time, and aims to study thenational archives that have the Tweets via their own content of Twitter andthe extent of interest in them and adopt standards have on Twitter.The study sample included Tweets National Archives: EgyptianNational Archives –Oman National archives - Saudi Arabia documents,archives national center and - King Abdulaziz DARAH and the NationalArchives of the United Arab Emirates is currently, the National Centre forDocumentation and Research earlier - the US National Archives - USpresidential museums and libraries - British National archivesAmong the most important results of study is: each national archivehave Tweets on Twitter, including a formal documented and most of themare not documented with the exception of the US National Archives have ageneral Tweets and other specialized sub-multiple, and empty most of theNational Archives Tweets of specific criteria and a clear policy with theexception of the US National Archives has a strategy and policy is clearand published, and that Twitter brings the number of photos and videostogether does not specify exactly how many photos in the account and thenumber of videos and in some cases does not mention the number andsophistication in the number of tweets and Followers and Likes andFavorites - moment after moment and hour after hour and day after day - Itis an indicator of the evolution of the expense of the National archives onTwitter…”
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Implementasi Metode Naive Bayes untuk Mendeteksi Stres Siswa Berdasarkan Tweet pada Sistem Monitoring Stres by Diva Fardiana Risa, Fajar Pradana, Fitra Abdurrachman Bachtiar

“…Salah satu jenis sosial media yang banyak digunakan oleh masyarakat adalah Twitter. Salah satu keunggulan Twitter adalah dikarenakan twitter lebih mudah digunakan dan memiliki tampilan yang sederhana. …”
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Analisis Sentimen terhadap Kebijakan Kuliah Daring Selama Pandemi Menggunakan Pendekatan Lexicon Based Features dan Support Vector Machine by Natasya Eldha Oktaviana, Yuita Arum Sari, Indriati Indriati

“…Hal tersebut menimbulkan kontroversi pada kalangan masyarakat dan banyak yang akhirnya beropini pada media sosial, salah satunya Twitter. Analisis sentimen berguna untuk mengetahui ketepatan komputasi sistem dalam mengenali pembicaraan pada Twitter mengenai kebijakan pembelajaran online cenderung bersentimen negatif atau positif dengan menggunakan metode Support Vector Machine dan Lexicon Based Features. …”
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Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet by Wiga Maulana Baihaqi, Muliasari Pinilih, Miftakhul Rohmah

“…Tulisan yang disampaikan melalui twitter dinamakan dengan tweets atau dalam bahasa indonesia lebih dikenal dengan kicau, tulisan yang dishare memiliki batas maksimum, tulisan tidak boleh lebih dari 140 karakter, karakter disini terdiri dari huruf, angka, dan simbol. …”
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Aggregating, Summarizing, and Restructuring News-Related Tweets into Compositions Using Deep Learning by Richa Sharma, Anjali Thukral, Yatin Kapoor, Ashwani Varshney, Punam Bedi

“…With the advent of microblogging platforms like Twitter, there has been a substantial shift toward digital media for getting acquainted with ongoing global issues. …”
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A proof-of-concept study of extracting patient histories for rare/intractable diseases from social media by Atsuko Yamaguchi, Núria Queralt-Rosinach

“…The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. …”
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Tales of health crises: Indonesia’s dynamic narratives and counter-narratives about pandemics by Rahmi Rahmi, Totok Suhardijanto, Herdito Sandi Pratama, Ratna Djumala, Katrin Setio Devi, Aditia Aditia

“…Despite its thoroughness, the study acknowledges several limitations, including the nuances of Twitter data and the challenges in comparative analysis. …”
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Eliminasi Non-Topic Menggunakan Pemodelan Topik untuk Peringkasan Otomatis Data Tweet dengan Konteks Covid-19 by Putri Damayanti, Diana Purwitasari, Nanik Suciati

“… Akun twitter, seperti Suara Surabaya, dapat membantu menyebarkan informasi tentang COVID-19 meskipun ada bahasan lainnya seperti kecelakaan, kemacetan atau topik lain. …”
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Cross-Platform Analysis of Mammography Narratives: A Comparative Study on Social Media Engagement by Thomas Stirrat, Jonathan Garner, Parth Tailor, Daniel Weitz, Muhammad Umair, Yusuf T. Akpolat

“…Purpose: This study examines the representation of mammography on social media platforms, specifically, X (Twitter), Facebook, TikTok, and Instagram, from 2006 to 2023. …”
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Bildung through social media by Michael Paulsen, Jesper Tække

“…Through an uncovering of these new possibilities we conclude that social media like Twitter can be used to support ‘interactional Bildung.’ …”
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SOCIAL MEDIA AND NONVIOLENT PROTEST MOVEMENTS: A CONTEMPORARY REVIEW OF THE ENDSARS MOVEMENT by Olaoluwa Babatunde OYINLOYE, Adeshina Iyanuoluwa OMOTAYO

“… The use of social media platforms such as Facebook, Instagram and Twitter were pivotal in the EndSARS protest against police brutality. …”
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More than just sentiment: Using social, cognitive, and behavioral information of social media to predict stock markets with artificial intelligence and big data by Yunus Emre Akdogan, Adem Anbar

“…Relationships between Twitter-obtained features and BIST indices were analyzed using machine learning methods such as linear regression, Lasso regression, random forest, and XGBoost. …”
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Stratejik Anlatı İnşasında Sosyal Medyanın Araçsallaştırılması: Türkiye-Yunanistan Örneği by Emine Boyraz

“…Bu amaçla çalışmada sosyal medya platformu Twitter’da inşa edilen stratejik anlatı temaları tespit edilmiş, elde edilen bulgular nitel içerik analizi tekniği kullanılarak tablolaştırılmıştır. …”
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Intelligent Topical Sentiment Analysis for the Classification of E-Learners and Their Topics of Interest by M. Ravichandran, G. Kulanthaivel, T. Chellatamilan

“…Every day, huge numbers of instant tweets (messages) are published on Twitter as it is one of the massive social media for e-learners interactions. …”
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