Twitting bad rumours - the grexit case

摘要

In this paper, we use methods from social network analysis to investigate patterns in data regarding the spreading of rumours regarding serious economic situations. More specifically, we use data acquired from Twitter during a period of time regarding keyword grexit . We then investigate a number of parameters regarding these data, such as their volume over time and their time relevance according to news feeds. We proceed by using methods from social network analysis (SNA) in order to create networks of tweets. These networks are comprised of persons or institutions that circulated globally our keyword of interest. The networks are then analysed according to well established methods and metrics from SNA. A certain approach tries to distinguish twitters from Greece and all other countries, when possible. Nodes are also clustered in communities, followed by another discussion on the way they interact and/or influence each other. Finally, we try to create a second class of network, regarding the semantics of the tweets' content. Again, an SNA type analysis is applied in these semantic networks.