Explaining Animosity Towards the Roma: a Case Study of Twitter Communication in Italy During the Refugee Crisis

Explaining Animosity Towards the Roma: a Case Study of Twitter Communication in Italy During the Refugee Crisis

City University of New York (CUNY) CUNY Academic Works All Dissertations, Theses, and Capstone Projects Dissertations, Theses, and Capstone Projects 5-2018 Explaining Animosity Towards the Roma: A Case Study of Twitter Communication in Italy during the Refugee Crisis Mayuko Nakatsuka The Graduate Center, City University of New York How does access to this work benefit ou?y Let us know! More information about this work at: https://academicworks.cuny.edu/gc_etds/2707 Discover additional works at: https://academicworks.cuny.edu This work is made publicly available by the City University of New York (CUNY). Contact: [email protected] EXPLAINING ANIMOSITY TOWARDS THE ROMA A CASE STUDY OF TWITTER COMMUNICATION IN ITALY DURING THE REFUGEE CRISIS by MAYUKO NAKATSUKA A master’s thesis submitted to the Graduate Faculty in Liberal Studies in partial fulfillment of the requirements for the degree of Master of Arts, The City University of New York 2018 © 2018 MAYUKO NAKATSUKA All Rights Reserved ii Explaining Animosity towards the Roma A Case Study of Twitter Communication in Italy during the Refugee Crisis by Mayuko Nakatsuka This manuscript has been read and accepted for the Graduate Faculty in Liberal Studies in satisfaction of the thesis requirement for the degree of Master of Arts. Date Till Weber Thesis Advisor Date Elizabeth Macaulay-Lewis Acting Executive Officer THE CITY UNIVERSITY OF NEW YORK iii ABSTRACT Explaining Animosity toward the Roma A Case Study of Twitter Communication in Italy during the Refugee Crisis by Mayuko Nakatsuka Advisor: Till Weber Italy is known for hostile treatment of the Roma, one of the largest ethnic minority groups in Europe. This paper seeks to understand what is causing Italians to talk negatively about the Roma on Twitter. Statistical analysis is performed utilizing the data mined from Twitter along with other variables. The study finds that Roma population, foreign population, and number of refugees all have significant effects on the total number of tweets or the average negative sentiment of tweets. The results indicate that native Italians may group minority groups all together and regard them as “others”. Although the research design has some flaws in the data mining and sentiment analysis process, the study shows promise. I suggest that social scientists utilize social media data to analyze social or cultural phenomena. iv TABLE OF CONTENTS Introduction ........................................................................................................................................................ 1 Chapter 1. The Roma ........................................................................................................................................ 4 1.1 History of the Roma People .................................................................................................................................. 4 1.2 Current Situation of the Roma People .............................................................................................................. 5 Chapter 2 ............................................................................................................................................................. 7 2.1 Methodology .............................................................................................................................................................. 7 2.1.1 Data Mining Method ........................................................................................................................................................ 7 2.1.2 Sentiment Analysis ............................................................................................................................................................ 9 2.2 Current Issues ........................................................................................................................................................ 10 2.2.1 Difficulties in Data Collection ................................................................................................................................... 10 2.2.2 Gap in Literature ............................................................................................................................................................. 11 Chapter 3 Analysis and Results ................................................................................................................... 16 3.1 InfluenCe of the Roma and Foreign Populations on Twitter ACtivity ................................................. 16 3.1.1 Linear Model, Regression, and Hypothesis Rejection ................................................................................... 16 3.1.2 Number of Tweets ........................................................................................................................................................... 19 3.1.3 Sentiment of Tweets ...................................................................................................................................................... 21 3.2 InfluenCe of Refugee Arrivals on Twitter ACtivity ..................................................................................... 25 3.2.1 Linear Model, Regression, and Hypothesis Rejection ................................................................................... 28 3.2.2 Number of Tweets ........................................................................................................................................................... 31 3.2.3 Sentiment of Tweets ...................................................................................................................................................... 33 3.2.4 Auto-correlation Study ................................................................................................................................................ 35 Conclusion ......................................................................................................................................................... 40 Opportunities for Future Research ............................................................................................................ 42 Bibliography ..................................................................................................................................................... 44 v LIST OF FIGURES Figure 1, p. 28: Evolution of Refugee Arrivals, Number of Tweets, and Sentiment Figure 2, p. 32: Yearly Modulation for Number of Tweets Figure 3, p. 34: Yearly Modulation for Sentiment of Tweets Figure 4, p. 37: Yearly Modulation for Number of Tweets (auto-correlation) Figure 5, p. 39: Yearly Modulation for Sentiment of Tweets (auto-correlation) vi \ LIST OF TABLES Table 1, p. 20: Number of Tweets Explained Table 2, p. 22: Average Sentiment of Tweets Explained Table 3, p. 23: Correlation between the Percentage of the Roma Population and the Percentage of Foreign Population Table 4, p. 24: Mean Sentiment of Tweets by City Table 5, p. 27: Overview Table 6, p. 31: Number of Tweets in Time Series Explained Table 7, p. 33: Sentiment of Tweets in Time Series Explained Table 8, p. 35: Number of Tweets in Time Series Explained (Auto-correlation) Table 9, p. 37: Sentiment of Tweets in Time Series Explained (Auto-correlation) vii Introduction According to a recent study published by Pew Research Center (2016), 82% of Italians have negative opinions about the Roma, one of the largest ethnic minority groups in Europe. This is the highest percentage out of all the countries surveyed; Greece, Hungary, France, Spain, Poland, the United Kingdom, Sweden, Germany, and the Netherlands. The median was 48% (Pew Research Center 2016). Greece and France, the two countries known for open hostility toward the Roma, scored 67% and 61%, respectively, well below what Italy did (Pew Research Center 2016). The same study also found that Italians are most critical of Muslims, with 63% of them possessing negative opinions (Pew Research Center 2016). Although 63% seems like a high percentage at a first glance, it is considerably smaller than 82%, the percentage of Italians who have negative opinions about the Roma (Pew Research Center 2016). Why does such a large percentage of Italians possess negative views on the Roma? How are their views influenced by the arrival of refugees, the number of immigrants and the number of Roma living in their city? Do their views differ from one city to another? These research questions will be addressed on the basis of a quantitative analysis of communication on Twitter. Social media has become part of many people’s lives since Twitter, Facebook, and Instagram were introduced and gained popularity all over the world. Even those who do not use social media are exposed to social media through other forms of media, such as television and newspapers. As of January 1, 2018, Twitter has about 330 million active users (Aslam 2018). Around one third of them tweet every day, and a little over 80% of them use their mobile devices to send and read tweets (Aslam 2018). About 11% of the Italian population uses Twitter (Russo 2017). The platform is very easy to navigate and 1 makes it possible for anyone with internet access to express their thoughts in a couple of short sentences and share them with a large audience. They write freely and interact with other users by retweeting1 replying and favoriting2. Retweeting exposes tweets to more people and spreads their content beyond the user’s followers. Many users do not seem to shy away from expressing

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