Tyler Procko, Mohammad Alali and Zachary Hancock
Embry-Riddle Aeronautical University
The use of social media as a form of humanitarian computing is a relatively novel area in the realm of technology. Probably the most prevalent use for social media with respect to humanitarian purposes is that of crisis analysis and intervention. In present society, social media platforms are implemented for almost every purpose, including times of crisis. Coordination of humanitarian relief during a crisis can be executed more effectively with the use of social media by gauging the affected population’s overall sentiment. Modern people frequent their favorite social media platforms, …show more content…
Seeing the mass prevalence of this topic, we have decided to include a large section in the paper dedicated to the background and analysis of the subject.
Social media is extremely popular in modern society; most of the world’s people spend some amount of time each day looking through their favorite platforms and connecting with other people- even those that may be thousands of miles away. For this very reason, social media is very useful during a crisis or natural disaster. For humanitarian aid and rescue teams, a steady source of live, accurate information is essential to their plan of action. With the sheer amount of messages and posts sent each day, monitoring social media during a crisis can prove an essential part of any good crisis management plan. Because there are so many active users on different social media platforms, messages and posts can happen within minutes of a crisis- quicker than what a news team can boast. “As an example, social media was extensively used for such purposes in the aftermaths of the 2011 Tohoku earthquake, where the first tweet on the topic was written less than two minutes after the epicenter of the earthquake” (Johansson, Brynielsson & Quijano 2012). It is this instant updating capability from persons directly in the zone of the crisis that makes social media a greatly …show more content…
For instance, accurate prediction of the stock market has long been a difficult task. Using NLP algorithms, investor sentiment from newsletters, blogs and other forms of social media can be taken, measured and calculated, then factored into some predictive analysis model to form a more accurate prediction of the direction of a particular stock or index. Of course, prediction of such a multi-level, non-linear event is much more complicated, but investor sentiment often drives prices, so adding in a way to measure this variable may prove effective in more accurate prediction of price movement. Building on this topic, artificial neural networks (ANNs) could be implemented to perform these complex analysis techniques automatically. Past data of the target stock or index could be used to train the ANN, so the output(s) it gives may be more accurate in its prediction. Some will argue that prediction of stock prices is not an issue of humanitarian computing. But, the stock market is a direct indicator of a country’s wealth and growth, so prediction of one’s country’s well-being is by all means a humanitarian effort. Also, we believe that social media can be used to better inform the younger generation of prevalent issues in society, like presidential elections and debates, which most millennials would rather