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  • Method

    How to Use Visual Media Analysis for Social Media Research

    How-to guide that describes four recipes for visual media analysis, including key software tools that enable the analysis
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  • TrainingMaterial

    Social Network Analysis @MasterBigData2022

    This course introduces students to the theories, concepts, and measures of Social Network Analysis (SNA), which is aimed at characterizing the structure of large-scale Online...
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  • Method

    Fast and scalable likelihood maximization for Exponential Random Graph Models

    Exponential Random Graph Models (ERGMs) have gained increasing popularity over the years. Rooted into statistical physics, the ERGMs framework has been successfully employed...
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  • Method

    How to Make Meme Collections

    How to guide to make meme collections by querying and extracting memes from four key sites: the meme database Know Your Meme, the web search engine Google Images, the meme...
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  • TrainingMaterial

    Ego network analysis, information-driven social links and impact on informati...

    Slide from the Summer School on Computational Misinformation Analysis 2019 lesson
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  • JournalArticle

    Big other Surveillance capitalism and the prospects of an information civiliz...

    This article describes an emergent logic of accumulation in the networked sphere, ‘surveillance capitalism,’ and considers its implications for ‘information civilization.’ The...
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  • TrainingMaterial

    Compressed and Learned Data Structures Seminar

    In this seminar cycle, students are guided in the direct usage of a powerful C++ library implementing many state-of-the-art compressed data structures for big data. Other than...
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  • JournalArticle

    Explaining misclassification and attacks in deep learning via random forests

    Artificial intelligence, and machine learning (ML) in particular, is being used for different purposes that are critical for human life. To avoid an algorithm-based...
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  • ConferencePaper

    Efficient detection of Byzantine attacks in federated learning using last lay...

    Federated learning (FL) is an alternative to centralized machine learning (ML) that builds a model across multiple decentralized edge devices (a.k.a. workers) that own the...
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  • JournalArticle

    Conformity a Path-Aware Homophily measure for Node-Attributed Networks

    Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached...
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  • ConferencePaper

    Fair detection of poisoning attacks in federated learning

    Federated learning is a decentralized machine learning technique that aggregates partial models trained by a set of clients on their own private data to obtain a global model....
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