Social media platforms, notably Twitter, have emerged as significant sources of information for disaster management and infrastructure resilience. In recent years, researchers have investigated the potential of Twitter data to evaluate the impact of disasters on infrastructure and to comprehend the resilience of critical infrastructure systems. This study provides a comprehensive review of the methods and challenges associated with utilizing Twitter to infer infrastructure resilience. By reviewing the current body of literature, this study synthesizes evidence on the utility of multimodal Twitter data including text, images, and videos for evaluating infrastructure resilience during a disruptive event earthquake held on February 6th 2023. To strengthen methodological rigor, conducted a systematic review of peer-reviewed studies, data extraction focused on analytical techniques, validation approaches, and reported challenges. This study also explores the various methods used to analyze Twitter data, including machine learning, sentiment analysis, network analysis, and topic modelling. Moreover, it addresses the challenges associated with using Twitter for assessing infrastructure resilience, such as issues of data quality, ethical considerations, and suitable data-processing techniques.