#theterrormood: Studying world mood after the terror attacks of Paris and Bruxelles

The use of social media has become an increasingly significant phenomenon in contemporary society due to the huge and rapid advances in information technology. People are using social media on a daily basis to communicate their opinions with each other about a wide variety of subjects and general events. Social media communications include Facebook, Twitter, and many others. Twitter is one of the most widely used social media sites and has become an important tool for the assessment of public opinion on various different issues. Recently, several approaches for the evaluation of Twitter messages have been developed, identifying the relationships between words and sentiments associated with relevant keywords or hashtags. In this work, through Twitter, we examine people's reactions to two tragic international events, namely the Paris and Bruxelles terror attacks. Specifically, we have collected comments on Twitter of users from various countries after the attacks. The data were collected using the "twitteR" package in the R programming language; all tweets that contained hashtags like #notinmyname, #Paris, #PrayForParis, #PrayForTheWorld, #PrayForFrance and #JeSuisParis from 27 November to 4 December 2015 and all tweets that contained hashtags like #notinmyname, #PrayForBruxelles, #PrayForBelgium, #Bruxelles and #PrayForTheWorld from 5 to 13 April 2016 were considered. The textual information was analyzed through techniques of Text Mining and Network Analysis in order to detect some important structures of people's communications understanding their mood from these threads. Using some R packages, the data were cleaned and analyzed, to classify the tweets into different types of emotion.