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Computational Social Science (CSS) has emerged as a fast-developing scientific field. Its growth has been driven by the increasing availability of computational power, coordinated digitization, annotation and interoperability efforts, and large-scale data on social activities. computing, data sciences and the social sciences created a loop, opening new fields of inquiry and forming new methodologies, making way for innovative approaches, and potentially leading to fresh discoveries. The papers in this special issue cover a wide range of phenomena using computational methods, such as social media, simulation, creative and cultural industries, as well as infrastructures for CSS. They apply CSS methods including social network analysis, virtual encounter simulations, sentiment and emotion analysis, and corpus linguistics, to case studies ranging from Covid-19 pandemic to electoral behavior, to political charisma, to cultural affinities and value orientation to border regions, to esports networks, to museums, to national and international infrastructures, thus providing a spectrum of possibilities (and limitations) for social scientists.
Skarpelos et al. (Fri,) studied this question.
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