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Types of contextual information in the social networks era

机译:社交网络时代的背景信息类型

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摘要

Data analysis always played a crucial role in computer science towards a more efficient understanding of its various trends. Focusing on digital content - generated, shared and consumed within the framework of social networks - this task is getting both more interesting and difficult to tackle. Nowadays social media platforms and networks have provided researchers with tools and opportunities to analytically study social phenomena, but at the same time significant and rather complex computational challenges are yet to be tackled, due to the huge rate of new content and information production imposed by social interactions. The ultimate goal of this position paper is to provide interested stakeholders a state-of-the-art overview of major contextual information types to be identified within the social networks' environment.
机译:数据分析在计算机科学中始终发挥着至关重要的作用,以更有效地理解其各种趋势。专注于在社交网络的框架内生成,共享和使用的数字内容,这一任务变得越来越有趣且难以解决。如今,社交媒体平台和网络已为研究人员提供了分析社会现象的工具和机会,但与此同时,由于社交内容带来的大量新内容和新信息的产生,还需要解决重大且相当复杂的计算难题。互动。该立场文件的最终目标是为感兴趣的利益相关者提供有关在社交网络环境中识别的主要上下文信息类型的最新技术概述。

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