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    <dc:publisher>Springer Berlin Heidelberg</dc:publisher>
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    <rss:title>Heavy-tail-aware representation learning and dynamic Bayesian state modelling to derive an operational proxy definition of problem gambling risk from routine online gambling data</rss:title>
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    <rss:description>Authors: Sam Andersson, Helga Westerlind, Timo Koski, Keenan Lyon, Per Carlbring, Philip Lindner and Olof Molander.&lt;br /&gt;EPJ Data Science Vol. 15 , page 77&lt;br /&gt;Published online: 4/9/2026&lt;br /&gt;
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       Problem gambling ; Operational risk definition ; Heavy-tailed behavior ; Representation learning ; Variational autoencoder ; Hidden Markov model ; Alert-to-assessment interval ; Capacity-constrained triage ; Missing-not-at-random labels.</rss:description>
    <dc:title>Heavy-tail-aware representation learning and dynamic Bayesian state modelling to derive an operational proxy definition of problem gambling risk from routine online gambling data</dc:title>
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    <dc:creator>Timo Koski</dc:creator>
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    <dc:date>2026-9-4</dc:date>
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    <rss:title>Assessing the value of objective suspicious transactions in Dutch anti-money laundering investigations: a network approach</rss:title>
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    <rss:description>Authors: Elena Candellone, Peter Gerbrands, Mahdi Shafiee Kamalabad and Javier Garcia-Bernardo.&lt;br /&gt;EPJ Data Science Vol. 15 , page 78&lt;br /&gt;Published online: 25/6/2026&lt;br /&gt;
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       Suspicious transaction reports ; Money laundering ; Network analysis ; Financial intelligence ; Anti-money laundering investigations.</rss:description>
    <dc:title>Assessing the value of objective suspicious transactions in Dutch anti-money laundering investigations: a network approach</dc:title>
    <dc:creator>Elena Candellone</dc:creator>
    <dc:creator>Peter Gerbrands</dc:creator>
    <dc:creator>Mahdi Shafiee Kamalabad</dc:creator>
    <dc:creator>Javier Garcia-Bernardo</dc:creator>
    <dc:subject>Suspicious transaction reports</dc:subject>
    <dc:subject>Money laundering</dc:subject>
    <dc:subject>Network analysis</dc:subject>
    <dc:subject>Financial intelligence</dc:subject>
    <dc:subject>Anti-money laundering investigations</dc:subject>
    <dc:date>2026-6-25</dc:date>
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    <rss:title>Modeling the coevolution of relational events and relational states in social networks</rss:title>
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    <rss:description>Authors: Christoph Stadtfeld, Maria Eugenia Gil-Pallares and Viviana Amati.&lt;br /&gt;EPJ Data Science Vol. 15 , page 81&lt;br /&gt;Published online: 3/7/2026&lt;br /&gt;
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       Dynamic social networks ; Statistical modeling ; Relational events ; Relational states ; Friendship ; Social media.</rss:description>
    <dc:title>Modeling the coevolution of relational events and relational states in social networks</dc:title>
    <dc:creator>Christoph Stadtfeld</dc:creator>
    <dc:creator>Maria Eugenia Gil-Pallares</dc:creator>
    <dc:creator>Viviana Amati</dc:creator>
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    <dc:subject>Relational events</dc:subject>
    <dc:subject>Relational states</dc:subject>
    <dc:subject>Friendship</dc:subject>
    <dc:subject>Social media</dc:subject>
    <dc:date>2026-7-3</dc:date>
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    <rss:title>When transparency falls short: auditing platform moderation during a high-stakes election</rss:title>
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    <rss:description>Authors: Benedetta Tessa, Gautam Kishore Shahi, Amaury Trujillo and Stefano Cresci.&lt;br /&gt;EPJ Data Science Vol. 15 , page 79&lt;br /&gt;Published online: 23/9/2026&lt;br /&gt;
       Keywords:
       Content moderation ; Social media ; Digital Service Act ; 2024 European Parliament election ; Statement of reasons ; Data visualization ; Online regulation.</rss:description>
    <dc:title>When transparency falls short: auditing platform moderation during a high-stakes election</dc:title>
    <dc:creator>Benedetta Tessa</dc:creator>
    <dc:creator>Gautam Kishore Shahi</dc:creator>
    <dc:creator>Amaury Trujillo</dc:creator>
    <dc:creator>Stefano Cresci</dc:creator>
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    <dc:date>2026-9-23</dc:date>
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    <rss:title>Multi-source, multi-level: a hierarchical taxonomy-based framework for AI trends analysis</rss:title>
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    <rss:description>Authors: Sondre Sørbø, Shanshan Jiang, Phil Tinn, Mihai Gheorghe, Roberto Avogadro and Dumitru Roman.&lt;br /&gt;EPJ Data Science Vol. 15 , page 82&lt;br /&gt;Published online: 3/7/2026&lt;br /&gt;
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       Temporal trend analysis ; Metrics for trend analysis ; Multi-source trend analysis ; Trend exploration tool ; AI trends analysis.</rss:description>
    <dc:title>Multi-source, multi-level: a hierarchical taxonomy-based framework for AI trends analysis</dc:title>
    <dc:creator>Sondre Sørbø</dc:creator>
    <dc:creator>Shanshan Jiang</dc:creator>
    <dc:creator>Phil Tinn</dc:creator>
    <dc:creator>Mihai Gheorghe</dc:creator>
    <dc:creator>Roberto Avogadro</dc:creator>
    <dc:creator>Dumitru Roman</dc:creator>
    <dc:subject>Temporal trend analysis</dc:subject>
    <dc:subject>Metrics for trend analysis</dc:subject>
    <dc:subject>Multi-source trend analysis</dc:subject>
    <dc:subject>Trend exploration tool</dc:subject>
    <dc:subject>AI trends analysis</dc:subject>
    <dc:date>2026-7-3</dc:date>
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    <rss:title>Autoregressive mutual-information networks for detecting and forecasting nonequilibrium regimes in oil–equity markets</rss:title>
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    <rss:description>Authors: Arash Sioofy Khoojine, Lin Xiao, Hao Chen, Qing Li and Qinyi Zhou.&lt;br /&gt;EPJ Data Science Vol. 15 , page 80&lt;br /&gt;Published online: 3/7/2026&lt;br /&gt;
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       Mutual information ; Financial networks ; Chaos ; Permutation entropy ; Lyapunov exponent ; Regime shifts ; PMFG ; Network autoregression ; Systemic risk.</rss:description>
    <dc:title>Autoregressive mutual-information networks for detecting and forecasting nonequilibrium regimes in oil–equity markets</dc:title>
    <dc:creator>Arash Sioofy Khoojine</dc:creator>
    <dc:creator>Lin Xiao</dc:creator>
    <dc:creator>Hao Chen</dc:creator>
    <dc:creator>Qing Li</dc:creator>
    <dc:creator>Qinyi Zhou</dc:creator>
    <dc:subject>Mutual information</dc:subject>
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    <rss:title>Correction: AGECovP: identifying ageism and analyzing COVID-19 discourse on older adults in YouTube</rss:title>
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    <rss:description>Authors: Amira Ghenai, Keshav Nath and Aarat Satsangi.&lt;br /&gt;EPJ Data Science Vol. 15 , page 83&lt;br /&gt;Published online: 24/9/2026</rss:description>
    <dc:title>Correction: AGECovP: identifying ageism and analyzing COVID-19 discourse on older adults in YouTube</dc:title>
    <dc:creator>Amira Ghenai</dc:creator>
    <dc:creator>Keshav Nath</dc:creator>
    <dc:creator>Aarat Satsangi</dc:creator>
    <dc:date>2026-9-24</dc:date>
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    <rss:title>IGWO-MRC: optimization-guided multimodal fake news detection via residual collaboration</rss:title>
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    <rss:description>Authors: Guangyu Mu, Jiaxiu Dai, Xiuying Ma, Zhihui Liu and Jiaxue Li.&lt;br /&gt;EPJ Data Science Vol. 15 , page 84&lt;br /&gt;Published online: 7/7/2026&lt;br /&gt;
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       Fake News Detection ; Grey Wolf Optimizer ; Residual Gated Fusion ; Multimodal Residual Collaboration.</rss:description>
    <dc:title>IGWO-MRC: optimization-guided multimodal fake news detection via residual collaboration</dc:title>
    <dc:creator>Guangyu Mu</dc:creator>
    <dc:creator>Jiaxiu Dai</dc:creator>
    <dc:creator>Xiuying Ma</dc:creator>
    <dc:creator>Zhihui Liu</dc:creator>
    <dc:creator>Jiaxue Li</dc:creator>
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    <dc:subject>Grey Wolf Optimizer</dc:subject>
    <dc:subject>Residual Gated Fusion</dc:subject>
    <dc:subject>Multimodal Residual Collaboration</dc:subject>
    <dc:date>2026-7-7</dc:date>
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