An Analysis of Online Twitter Sentiment Surrounding the European Refugee Crisis

David Pope, Josephine Griffith

2016

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.

References

  1. (2016). Syria regional refugee response inter-agency information sharing portal. [Online Website: Accessed: 2016-06-15].
  2. Asur, S. and Huberman, B. (2010). Predicting the future with social media. Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference.
  3. Bollen, J., Mao, H., and Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science.
  4. Caragea, C., Squicciarini, A., Stehle, S., Neppalli, K., and Tapia, A. (2014). Mapping moods: Geo-mapped sentiment analysis during hurricane sandy. 11th International Conference on Information Systems for Crisis Response and Management.
  5. Coletto, M., Lucchese, C., Muntean, C., Nardini, F. M., Esuli, A., Renso, C., and Perego, R. (May 2016). Sentiment-enhanced multidimensional analysis of online social networks: Perception of the mediterranean refugees crisis. Under Review.
  6. Gilbert, E. and Karahalios, K. (2009). Widespread worry and the stock market. 4th International AAAI Conference on Weblogs and Social Media.
  7. Kramer, A. (2010). An unobtrusive behavioral model of “gross national happiness.” Proc. of SIG CHI Conference on Human Factors in Computing Systems.
  8. Li, J., Wang, X., and Hovy, E. (2014). What a nasty day: Exploring mood-weather relationship from twitter. Proc. of 23rd ACM International Conference on Conference on Information and Knowledge Management.
  9. Pennebaker, J., Boyd, R., Jordan, K., and Blackburn, K. (August 2015a). The development and psychometric properties of liwc201578.
  10. Pennebaker, J., Chung, C., Ireland, M., Gonzales, A., Booth, R., and Francis, M. (2007). The development and psychometric properties of liwc2007.
  11. Pennebaker, J., Roger, J., Booth, R., Boyd, L., and Francis, M. (August 2015b). Linguistic inquiry and word count: Liwc2015, operator manual.
  12. Scally, D. (2016). Media under scrutiny over slow response to cologne attacks. The Irish Times Newspaper.
  13. Thelwall, M., Buckley, K., and Paltoglou, G. (2011). Sentiment in twitter events. Journal of the American Society for Information Science and Technology, 62.
  14. Tumasjan, A., Sprenger, T., Sandner, P., and Welpe, I. M. (2010). Predicting elections with twitter: What 140 characters reveal about political sentiment. 4th International AAAI Conference on Weblogs and Social Media.
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Paper Citation


in Harvard Style

Pope D. and Griffith J. (2016). An Analysis of Online Twitter Sentiment Surrounding the European Refugee Crisis . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016) ISBN 978-989-758-203-5, pages 299-306. DOI: 10.5220/0006051902990306


in Bibtex Style

@conference{kdir16,
author={David Pope and Josephine Griffith},
title={An Analysis of Online Twitter Sentiment Surrounding the European Refugee Crisis},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)},
year={2016},
pages={299-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006051902990306},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, (IC3K 2016)
TI - An Analysis of Online Twitter Sentiment Surrounding the European Refugee Crisis
SN - 978-989-758-203-5
AU - Pope D.
AU - Griffith J.
PY - 2016
SP - 299
EP - 306
DO - 10.5220/0006051902990306