Online social networks (OSNs) such as Facebook, Instagram and Twitter provide a unique channel of communication between individuals, groups and organizations. This communication is valuable to individuals as it allows for reaching increasingly wide audiences of diverse populations and has proven to be particularly useful for distributed problem solving and collective action, particularly during crisis events. The advancement of social networks for personal communication as well as collective intelligence and collective action also increases their value to researchers interested in gaining fundamental insights related to individuals and communities. Twitter, in particular, provides a unique perspective as the social network is widely adopted, user-driven, and network-based. These properties of the Twitter platform make it a valuable source of data for understanding the dynamics within large communities of individuals. In this paper, we motivate the use of Twitter as a viable source of data in understanding communities, with specific emphasis on a community's resilience to natural disasters and crisis events. Here, we discuss the literature on the use of social media for resilience analytics. We describe how social media can complement and improve current methods for evaluating community resilience by creating datasets based on flexible temporal and spatial scales, as well as allowing for the ability to quantify system transformation. We also provide a detailed tutorial on how to access, process and analyze twitter data, and discuss the platform's limitations in the spirit of improved transparency in research at the nexus of social media and community resilience. Finally, we propose future directions for research at the intersection of community resilience and social media.

诸如Facebook，Instagram和Twitter之类的在线社交网络（OSN）提供了个人，团体和组织之间独特的沟通渠道。这种交流对个人而言很有价值，因为它可以接触到越来越多的不同人群，并且对分散解决问题和采取集体行动特别是在危机事件期间特别有用。用于个人交流以及集体智慧和集体行动的社交网络的进步，也增加了它们对有兴趣获得有关个人和社区的基本见识的研究人员的价值。随着社交网络被广泛采用，用户驱动和基于网络，特别是Twitter提供了独特的视角。Twitter平台的这些属性使其成为了解大型个人社区内动态的重要数据来源。在本文中，我们鼓励使用Twitter作为了解社区的可行数据源，特别强调社区对自然灾害和危机事件的应变能力。在这里，我们讨论使用社交媒体进行弹性分析的文献。我们描述了社交媒体如何通过基于灵活的时间和空间尺度创建数据集以及允许量化系统转换的能力来补充和改进当前的评估社区适应力的方法。我们还提供了有关如何访问，处理和分析Twitter数据的详细教程，并讨论了平台的 在社交媒体和社区适应力之间提高研究透明度的精神上存在局限性。最后，我们在社区适应力和社交媒体的交叉点上提出了未来的研究方向。