Refugees’ social media activities in Turkey: a computational analysis and demonstration method

Refugees’ social media activities in Turkey: a computational analysis and demonstration method

This study performs a data analysis on refugees in Turkey based on their social media activities. In orderto achieve this, we first propose a method to find their relevant public accounts and collect their activities generating adataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topicsand events discussed in social networks. We present the results graphically for ease of understanding and comparison.Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change ofpattern in refugees’ activities through their reflection on social media. Moreover, this dataset facilitates a number offurther and deeper analyses of the refugees in Turkey.

___

  • [1] Stepanova E. The role of information communication technologies in the “Arab Spring”. PONARS Eurasia Policy Memo 2011; 159: 12-16.
  • [2] Haj Ismail S, Çetin R. SWOT Analysis of refugees’ high education in Turkish universities for construction fields. In: Proceedings of Second International Symposium Syrian Refugees between Reality and Expectation; 20–22 October 2017; Adıyaman, Turkey: Adıyaman University. pp. 93-98.
  • [3] Jalili M, Perc M. Information cascades in complex networks. Journal of Complex Networks 2017; 5: 665-693.
  • [4] Helbing D, Brockmann D, Chadefaux T, Donnay K, Blanke U, Woolley-Meza O, Moussaid M, Johansson A, Krause J, Schutte S, Perc M. Saving human lives: what complexity science and information systems can contribute. J Stat Phys 2015; 158: 735-781.
  • [5] Enli G. Twitter as arena for the authentic outsider: exploring the social media campaigns of Trump and Clinton in the 2016 US presidential election. Eur J Commun 2017; 32: 50-61.
  • [6] Martinčić-Ipšić S, Močibob E, Perc M. Link prediction on Twitter. PloS One 2017; 12: e0181079.
  • [7] Jalili M, Orouskhani Y, Asgari M, Alipourfard N, Perc M. Link prediction in multiplex online social networks. Roy Soc Open Sci 2017; 4: 160863.
  • [8] Tumasjan A, Sprenger TO, Sandner PG, Welpe IM. Predicting elections with Twitter: what 140 characters reveal about political sentiment. In: Proceedings of International AAAI Conference on Web and Social Media (ICWSM10); 23–26 May 2010; Washington, USA: AAAI press. pp. 178-185.
  • [9] Sang E, Tjong K, Bos J. Predicting the 2011 dutch senate election results with Twitter. In: Proceedings of the Workshop on Semantic Analysis in Social Media, 23–27 April 2012; Avignon, France: ACL. pp. 53-60.
  • [10] Burnap P, Gibson R, Sloan L, Southern R, Williams M. 140 characters to victory?: using Twitter to predict the UK 2015 General Election. Elect Stud 2016; 41: 230-233.
  • [11] Mascaro C, Agosto D, Goggins SP. The method to the madness: The 2012 United States presidential election Twitter corpus. In: Proceedings of the 7th International Conference on Social Media & Society: ACM, 11–13 July 2016; London, UK: ACM. pp.15.
  • [12] Gayo-Avello D. I wanted to predict elections with Twitter and all I got was this lousy paper–a balanced survey on election prediction using Twitter data. arXiv preprint 2012. arXiv:1204.6441.
  • [13] Kreis R. #refugeesnotwelcome: anti-refugee discourse on Twitter. Discourse & Communication 2017: SAGE Publications Sage UK: London, England; 11: 498-514.
  • [14] Rettberg JW, Gajjala R. Terrorists or cowards: negative portrayals of male Syrian refugees in social media. Feminist Media Studies 2016; 16: 178-181.
  • [15] Magdy W, Darwish K, Abokhodair N, Rahimi A, Baldwin T. #ISISisNotIslam or #DeportAllMuslims?: predicting unspoken views. In: Proceedings of the 8th ACM Conference on Web Science (WebSci’16),22–25 May 2016; Hannover, Germany: ACM. pp. 95-106.
  • [16] Darwish K, Alexandrov D, Nakov P, Mejova Y. Seminar users in the Arabic Twitter sphere. In: Proceedings of International Conference on Social Informatics, 13–15 September 2017. Oxford, UK: Springer. pp. 91-108.
  • [17] Panetta L. UNHCR Turkey: Fact Sheet. Ankara, Turkey: UNHCR, 2017.
  • [18] T.C. İçişleri Bakanlığı Göç İdaresi Genel Müdürlüğü. İdare Faaliyet Raporu. Ankara, Turkey: Göç İdaresi Genel Müdürlüğü, 2017 (in Turkish).
  • [19] Bulbul A, Kaplan C, Ismail SH. Social media based analysis of refugees in Turkey. In: Proceedings of the first International Workshop on Analysis of Broad Dynamic Topics over Social Media: BroDyn, 26 March 2018. Grenoble, France: CEUR-WS. pp.35-40.
  • [20] Dahab MY, Ibrahim A, Al-Mutawa R. A comparative study on Arabic stemmers. International Journal of Computer Applications 2015; 125:38-47.