@inproceedings{4db3c76972fe4206a9b7ce5aa893eb87,
title = "An analysis of online twitter sentiment surrounding the european refugee crisis",
abstract = "Using existing natural language and sentiment analysis techniques, this study explores different dimensions of mood states of tweet content relating to the refugee crisis in Europe. The study has two main goals. The first goal is to compare the mood states of negative emotion, positive emotion, anger and anxiety across two populations (English and German speaking). The second goal is to discover if a link exists between significant real-world events relating to the refugee crisis and online sentiment on Twitter. Gaining an insight into this comparison and relationship can help us firstly, to better understand how these events shape public attitudes towards refugees and secondly, how online expressions of emotion are affected by significant events. Copyrightc 2016 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.",
keywords = "Refugee Crisis, Sentiment Analysis, Social Media Analysis",
author = "David Pope and Josephine Griffith",
year = "2016",
doi = "10.5220/0006051902990306",
language = "English",
series = "IC3K 2016 - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management",
publisher = "SCITEPRESS",
pages = "299--306",
editor = "Ana Fred and Jan Dietz and David Aveiro and Kecheng Liu and Jorge Bernardino and Joaquim Filipe and Joaquim Filipe",
booktitle = "KDIR 2016 - 8th International Conference on Knowledge Discovery and Information Retrieval",
note = "8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2016 ; Conference date: 09-11-2016 Through 11-11-2016",
}