相关论文: The Ethical Risks of Analyzing Crisis Events on So…

This study examines machine learning methods used in crisis management. Analyzing detected patterns from a crisis involves the collection and evaluation of historical or near-real-time datasets through automated means. This paper utilized…

Social media are more than just a one-way communication channel. Data can be collected, analyzed and contextualized to support disaster risk management. However, disaster management agencies typically use such added-value information to…

The accelerated development of social media websites has posed intricate security issues in cyberspace, where these sites have increasingly become victims of criminal activities including attempts to intrude into them, abnormal traffic…

In recent years, social media has become one of the most popular platforms for communication. These platforms allow users to report real-world incidents that might swiftly and widely circulate throughout the whole social network. A social…

This paper highlights an important, if under-examined, set of questions about the deployment of machine learning technologies in the field of disaster risk management (DRM). While emerging tools show promising capacity to support scientific…

Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders, decision makers, and the public can use this information…

Crisis situations are characterised by their sudden occurrence and an unclear information situation. In that context, social media platforms have become a highly utilised resource for collective information gathering to fill these gaps.…

Social media has emerged as a valuable resource for disaster management, revolutionizing the way emergency response and recovery efforts are conducted during natural disasters. This review paper aims to provide a comprehensive analysis of…

Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among millions of posts being posted every day can be difficult, and developing a data…

The ethics of Machine Learning has become an unavoidable topic in the AI Community. The deployment of machine learning systems in multiple social contexts has resulted in a closer ethical scrutiny of the design, development, and application…

The computer science research community has became increasingly interested in the study of social media due to their pervasiveness in the everyday life of millions of individuals. Methodological questions and technical challenges abound as…

In recent years, the availability of massive data sets and improved computing power have driven the advent of cutting-edge machine learning algorithms. However, this trend has triggered growing concerns associated with its ethical issues.…

Social media has become an important tool to share information about crisis events such as natural disasters and mass attacks. Detecting actionable posts that contain useful information requires rapid analysis of huge volume of data in…

Extreme weather events driven by climate change, such as wildfires, floods, and heatwaves, prompt significant public reactions on social media platforms. Analyzing the sentiment expressed in these online discussions can offer valuable…

Individuals on social media may reveal themselves to be in various states of crisis (e.g. suicide, self-harm, abuse, or eating disorders). Detecting crisis from social media text automatically and accurately can have profound consequences.…

Social media platforms are now a key source of information for a large segment of the public. As such, these platforms have a great potential as a means to provide real-time information to emergency management agencies. Moreover, during an…

Population-level societal events, such as civil unrest and crime, often have a significant impact on our daily life. Forecasting such events is of great importance for decision-making and resource allocation. Event prediction has…

Social media such as tweets are emerging as platforms contributing to situational awareness during disasters. Information shared on Twitter by both affected population (e.g., requesting assistance, warning) and those outside the impact zone…

Social media analysis of disaster events is a critical task in crisis informatics research. It involves analyzing social media data generated during natural disasters, crisis events, or other mass convergence events. Due to the large data…

The prevalence of social media platforms and their use across the globe makes them attractive options for studying large groups of people, particularly when some of these platforms provide access to large amounts of structured data.…