Types of contextual information in the social networks era

Phivos Mylonas
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引用次数: 3

Abstract

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.
社交网络时代的语境信息类型
数据分析在计算机科学中一直扮演着至关重要的角色,以更有效地了解其各种趋势。专注于数字内容——在社交网络框架内生成、共享和消费——这一任务变得越来越有趣,也越来越难以解决。如今,社交媒体平台和网络为研究人员提供了分析研究社会现象的工具和机会,但与此同时,由于社交互动带来的新内容和信息生产的巨大速度,重大而相当复杂的计算挑战尚未得到解决。本意见书的最终目标是为感兴趣的利益相关者提供在社交网络环境中识别的主要上下文信息类型的最新概况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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