Identifying Key Influencers in Disaster Management: a Sentiment Analysis of Twitter Data for Fundraising and Awareness Campaigns

Taking advantage of the rapid growth of social media usage in influencing people in recent era can impact a wide scale of people through tweets and posts. Utilising social media especially twitter, during disasters and calamities can help the victims and sufferers to get relief by getting immediate interactions with government authorities and organisations. But larger impact would be created if it is posted by the high influencers even with low followers. However, there are many challenges as the influencers depend on various factors and their influence keeps on changing dynamically. Here, comes the role of Social Networking Analysis for finding out the most influenced users on twitter in a preferable way for dealing with disasters. This paper briefs about finding out the influencers that affect major people even with less followers, likes or tweets just depending on the impact they create on the social media using Sentimental Analysis and connecting them through Social Networking Analysis helps to configure the twitter users where each node represents an influencer by building a graph, the most famous influencers are identified using Sentimental Analysis. This would make our job easier by spreading awareness rapidly and serving the victims in massive proportions.