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Identifying Different Types of Social Ties in Events from Publicly Available Social Media Data

机译:从公开可用的社交媒体数据中识别不同类型的社交关系

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Tie strength is an essential concept in identifying different kind of social ties - strong ties and weak ties. Most present studies that evaluated tie strength from social media were carried out in a controlled environment and used private/closed social media data. Even though social media has become a very important way of networking in professional events, access to such private social media data in those events is almost impossible. There is very limited research on how to facilitate networking between event participants and especially on how to automate this networking aspect in events using social media. Tie strength evaluated using social media will be key in automating this process of networking. To create such tie strength based event participant recommendation systems and tools in the future, first, we need to understand how to evaluate tie strength using publicly available social media data. The purpose of this study is to evaluate tie strength from publicly available social media data in the context of a professional event. Our case study environment is community managers' online discussions in social media (Twitter and Facebook) about the CMAD2016 event in Finland. In this work, we analyzed social media data from that event to evaluate tie strength and compared the social media analysis-based findings with the individuals' perceptions of the actual tie strengths of the event participants using a questionnaire. We present our findings and conclude with directions for future work.
机译:领带强度识别不同类型的社会关系的一个重要概念 - 强关系和弱关系。目前大多数的研究,从社会化媒体评估关系强度均在受控环境中进行,使用私人/关闭社交媒体数据。尽管社交媒体已经成为专业活动联网的一个非常重要的方式,获得这样的私人社交媒体数据,这些事件几乎是不可能的。有关于如何促进活动参与者之间,特别是关于如何自动在使用社交媒体活动这一网络方面的网络非常有限的研究。利用社交媒体将成为自动化网络的这一过程中的关键关系强度评估。在未来创造这样的关系强度基于事件的参与者推荐系统和工具,首先,我们需要了解如何使用公开可用的社交媒体数据来评估关系强度。这项研究的目的是从公开可用的社交媒体数据以专业的事件的环境评估关系强度。我们的案例研究环境是社区管理者大约在芬兰CMAD2016事件的社交媒体(Twitter和Facebook)的在线讨论。在这项工作中,我们从这个事件来评估关系强度分析社交媒体数据,并与个人采用问卷事件参与者的实际领带优势的看法社交媒体分析为基础的结果。我们提出我们的调查结果,并为今后的工作方向得出结论。

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