论文标题
一种评估社交媒体数据可靠性进行社交网络分析的方法
A method to evaluate the reliability of social media data for social network analysis
论文作者
论文摘要
为了研究在线社交网络（OSN）活动对现实世界离线事件的影响，研究人员需要访问OSN数据，其可靠性对社交网络分析具有特殊影响。这不仅与任何收集到的数据集的完整性有关，还与从中构建有意义的社会和信息网络有关。在这项多学科研究中，我们考虑了从OSN数据构建传统社交网络的问题，然后提出了一个测量案例研究，以表明OSN数据的可靠性如何影响社交网络分析。为此，我们开发了一种系统的比较方法，我们将其应用于我们从Twitter收集的两个并行数据集。我们发现使用不同工具收集的数据集有很大的差异，并且这些变化显着改变了后续分析的结果。 我们的结果导致了一系列计划的指南，计划收集在线数据流以推断社交网络。
To study the effects of Online Social Network (OSN) activity on real-world offline events, researchers need access to OSN data, the reliability of which has particular implications for social network analysis. This relates not only to the completeness of any collected dataset, but also to constructing meaningful social and information networks from them. In this multidisciplinary study, we consider the question of constructing traditional social networks from OSN data and then present a measurement case study showing how the reliability of OSN data affects social network analyses. To this end we developed a systematic comparison methodology, which we applied to two parallel datasets we collected from Twitter. We found considerable differences in datasets collected with different tools and that these variations significantly alter the results of subsequent analyses. Our results lead to a set of guidelines for researchers planning to collect online data streams to infer social networks.
