Social Media Aggregator Using a focused Crawler and a Web & Android UI

Today we live in a digital age, with almost each and every one of us having at least one social media account. With things as trivial as what one had for breakfast to the happenings of the world, everything is discussed about on these social media accounts. This paper intends to suggest using this social media as a policing solution, as in contrast to other traditional media such as television and print media, social media offers velocity, veracity, variety, real-time and a large volume of information. A focused web crawler is used to crawl the internet and to stick to the relevant and required topics only. This crawler is integrated with a database to store the information and the information is projected on an android application as well as a web application for the user’s perusal

Machine Learning and Social Media in Crisis Management: Agility vs Ethics

One of the most used sources of information for fast and flexible crisis information is social media or crowdsourced data, as the information is rapidly disseminated, can reach a large amount of target audience and covers a wide variety of topics. However, the agility that these new methodologies enable comes at a price: ethics and privacy. This paper presents an analysis of the ethical risks and implications of using automated system that learn from social media data to provide intelligence in crisis management. The paper presents a short overview on the use of social media data in crisis management to then highlight ethical implication of machine learning and social media data using an example scenario. In conclusion general mitigation strategies and specific implementation guidelines for the scenario under analysis are presented