Becker Model

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Numerous studies have been carried out on the various factors of Hate crimes, focusing on different aspects such as, minority groups, social domains, and ability/inability in reporting hate crimes and case outcomes. However, contradictory results are suggested within this research topic because only certain aspects are investigated, such as, religious motivated bias crimes. Byers and Jones (2007), Hanes and Machin (2014), and Walfield, Socia and Powers (2017) focus on Muslim populations and the arise of various terror attacks, while Awan (2014) Awan and \ Zempi (2013) study focuses on the online/offline perspective of hate crimes. To further study how hate crimes arise, all forms and types of hate crimes should be studied.

Literature Review
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(2002) and the Becker model (1968). The Becker which provides apparent predictions about deterrence effects crime. Through the original Becker model the harm towards any individual is said to be the inadvertent reaction of the perpetrators response, which goes to say is not the best model. Gale et al. (2002) is used to best describe this study as the further enhanced the economic crime model lets us understand the uprising of hate crimes as a consumption good which generates utility. Utility in this case being caused by factors which alter desire, for example, shock, bad coverage of certain populations, previous experiences, prejudice. (pp. 249)

Analogous to Hanes and Machin’s (2014), Byers and Jones (2007) research study takes Allport’s (1979) theory of prejudice and the reduction of hate crimes due to common experiences into account and considers expectations which can result in hate crimes. Including factors such as color or noticeable differences (wearing a hijab, or talking in a foreign language). (pp. 46) Which provides a breakdown of factors which can induce the effect of the causation of hate
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Data was used from before and after 9/11 and the 7/7 London bombings. The main goal was to analyze the trend within hate crimes prior to after these after these attacks occurred through the NCRS (pp. 252). This method was somewhat flawed because there was more data available for 7/7 attack through the database.

Awan (2014) utilized a mixed method containing quantitative and qualitative data within the grounded theory (based on the analysis of data). In this study tweets throughout an interval of a year were inspected, specifically those using hashtags closely related to the study. According to Awan (2014) hashtags enabled the examination of Muslim populations pre-and post-Woolwich suggesting it enables the collection of a random sample (pp.141) However this approach can seem problematic as using hashtags can create bias since all the negative tweets will have shown up rather than positive

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