@inproceedings{fed54a1edb694576be22ff7f91ff0ee4,
title = "Analysing the behaviour of online investors in times of geopolitical distress: A case study onwar stocks",
abstract = "In this paper we analysed how the behavior of an online financial community changed in times of geopolitical crises. In particular, we studied the behaviour and communication patterns of online investors before and after a military geopolitical event. We selected a set of 23 key-events belonging to the 2003 US-led invasion of Iraq, the Arab Spring and the first period of the Ukraine crisis, and we restricted our study to a set of eight so called war stocks. We studied the resilience of the community to information shocks by comparing the community composition, its sentiment and users' communication networks before and after an event at different time intervals. We found how community reaction is governed by ordered patterns. Experimental evidence suggested how in the aftermath of an event the community did not lose its information sharing functionality. Communication networks showed a higher in-degree Gini index, connectivity and a rich-club effect. Discussions developed around central users acting as hubs. These backbone users were present both before and after an event, their sentiment were less volatile than other users, and they were previously recognized as local experts of a specific stock. As a further evidence of community resilience, the equilibrium of all the indicators analysed were restored after two weeks.",
keywords = "Behavioral finance, Content analysis, Social media, Web mining",
author = "Pierpaolo Dondio and James Usher",
note = "Publisher Copyright: {\textcopyright} 2017 ACM.; 16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 ; Conference date: 23-08-2017 Through 26-08-2017",
year = "2017",
month = aug,
day = "23",
doi = "10.1145/3106426.3106510",
language = "English",
series = "Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017",
publisher = "Association for Computing Machinery (ACM)",
pages = "275--283",
booktitle = "Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017",
address = "United States",
}