Defining Hate to Tackle Hate

We need clear definitions and data to tackle the ecosystems of hate!

Dr Matteo Vergani

COVID-19 has challenged the economic and health systems of communities, and impacted our social structure with hate emerging as a trending topic globally. Human rights organisations and community activists have reported a spike in racist attacks, especially towards Asian Australians (Tan, 2020). Security agencies have reported on organised hate groups exploiting the pandemic to recruit new members (Christodoulou, 2020). Globally, the UN warned that coronavirus sparked a tsunami of hate, including anti-foreigner, anti-Muslim and antisemitic hate (UN, 2020). The rapid spread of hate and misinformation online is making it more difficult to access accurate health information, and inflating fear and anxiety (ADL, 2020).

What is hate, though?

The use of the word hate varies from news article to news article. Hate has been used to describe an emotion, or an attitude towards a group (usually a minority). It has been used when referring to behaviours on and offline, ranging from sharing memes, name-calling, vandalism and aggression to murder and terrorism. However, sharing a racist meme is not the same as carrying out a terrorist attack, and although the back story to these behaviours could be considerably different, we need to understand the relationships between these behaviours. Why? As a society, we can’t have productive public discussions about hate and responses to hate, (including legislative and security responses), if we are not able to understand what hate is. Further, as academics we won’t be able to effectively measure hate, or answer questions like “is hate on the rise?” or “are we succeeding in preventing hate?” without a clear definition.

In the social and psychological sciences, hate is usually defined as a stable emotion of extreme dislike, as opposed to anger, which is a transitionary emotional status (Allport, 1954). Yet, hate is more than an emotional arousal: it is motivated by a worldview that reflects the willingness to exert power, and historical notions of hierarchy about races, religions, sexual and gender identities, bodies and other characteristics. Hate groups define their identity as the norm, and seek to negate, exclude and repress groups that are outside the norm (Perry and Scrivens, 2018). People who hate don’t necessarily need to know their targets personally, and they typically perceive them as inferior, immoral and malicious (Fischer et al., 2018).

Hate can manifest in many different ways, and there are a proliferation of terms to capture the outcomes of hate. Examples of these terms are: vilification, prejudice, discrimination, bias, hate crime, hate speech, violent extremism, terrorism, Islamophobia, antisemitism, racism, ableism, ageism, sexism, misogyny, homophobia, transphobia, among others. This fragmentation of language is one of the main hurdles to the study of hate, and to the coordination of responses to hate. A simple way to think about the different behaviours that form the ecosystem of hate is distinguish between: 1- the targets of the immediate action (individual vs collective), and 2- the types of action (violent vs non-violent). It’s important to acknowledge that, although the targets of immediate action can be individuals, all forms of hate aim to instil fear and intimidation beyond the immediate victim. Also, violence is intended as physical force, but other forms of non-physical violence can significantly hurt victims and bystanders.

The next table synthetizes the different forms of hate that make up the ecosystem of hate.

	INDIVIDUAL TARGET	COLLECTIVE TARGET
NON VIOLENT	E.g., bullying, ridicule, name-calling	E.g., systemic racism, criminal justice disparities, educational discrimination
VIOLENT	E.g., some forms of hate crime, violent extremism and terrorism directed at individual victims	E.g., genocide, massacres, mass murder

Relationships between individual and collective, violent and non-violent targets of hate

What is the relationship between these different forms of hate? Most security and legal practitioners would say that they are different behaviours, offenders, motivations and need different responses. If we look at how police forces and government work, different units independently tackle forms of hate such as terrorism vs hate crimes, racism vs homophobia, ableism vs ageism, and so on. Different agencies address different degrees of severity of hate conduct: usually, human rights organisations deal with less severe incidents regulated by civil laws, and law enforcement agencies deal with more severe incidents regulated by criminal laws.

However, scholars have been suggesting for a long time that phenomena like hate crimes and terrorism cannot be fully understood without looking at the enabling context, which includes more subtle forms of discrimination, hate speech  and poplar, political and media imagery (Perry, 2001; Poynting and Perry, 2007; Perry and Scrivens, 2018).

We need further research into how hate incidents are connected

The reality is that empirical research on the relationships between the different forms of hate that constitute the ecosystem of hate is scarce and limited by a dearth of data and measurement problems. Only a few studies have tested these relationships with either small qualitative samples (see  example Perry and Scrivens, 2018; Syed and Ali, 2020) or narrowly focusing on the relationships between similar forms of hate, such as extremists hate crimes and domestic terrorism (see for example Mills et al., 2017). Why is there this lack of rigorous research on this important topic? The simple answer: we don’t have much data.

An ecosystem of hate in data:

The sources of data about the ecosystem of hate fall into 4 broad categories:

1. Registers of community reports from victims or bystanders;

2. Surveys;

3. Media and other open sources;

4. Intelligence reports and other investigative data.

This fourth source of data is classified. As for the first three sources of data, in Australia, there are significant gaps

First, community reporting registers sit within a high number of government and non-government organisations that do not communicate with each other. Not all police forces collect data about the prejudice motivation of crimes, and those who do, have important methodological flaws (see for example Mason and Stanic, 2019). Second, some Australian researchers have collected survey data focusing on specific research questions, target groups, geographical areas, and forms of hate. However, there is no longitudinal large scale survey that assesses trends of hate and bias motivation of crime in Australia, as opposed to other countries like the United States or Canada (see for example NACJD, 2020). Third, Australia does not have an open-source database of hate crime or terrorism, while many other countries do (Bowie, 2018).

Why do we need to improve the data we have about the ecosystem of hate? It’s not just because some academics want to publish papers with esoteric formulas in journals hidden behind a paywall. We need data for so much more. To advance our understanding of the ecosystem of hate, its evolution and its impact on our democratic system. To inform and evaluate programs, policies and policing responses to different forms of hate. To aid the education of police and legal practitioners. To enhance our ability to prevent serious harm to communities. To advocate for legislation change and victims support programs, and to inform community awareness and education.

Ultimately, we need data to ensure we have a public debate based on evidence, rather than ideological arguments.

Resources

• Allport, G. W. (1954). The nature of prejudice. Reading, MA: Addison-Wesley.
• Anti Defamation League (ADL) (2020) Coronavirus Crisis Elevates Antisemitic, Racist Tropes
• Bowie, N. G. (2018). 30 Terrorism Databases and Data Sets: a New Inventory. Perspectives on Terrorism, 12(5), 51-61.
• Christodoulou, M. (2020) ASIO briefing warns that the far-right is exploiting coronavirus to recruit new members, ABC News
• Fischer, A., Halperin, E., Canetti, D., and Jasini, A. (2018). Why we hate. Emotion Review, 10(4), 309-320.
• Mason, G., and Stanic, R. (2019). Reporting and recording bias crime in New South Wales. Current Issues in Criminal Justice, 31(2), 164-180.


• Mills, C. E., Freilich, J. D., and Chermak, S. M. (2017). Extreme hatred: revisiting the hate crime and terrorism relationship to determine whether they are “Close Cousins” or “Distant Relatives”. Crime and Delinquency, 63(10), 1191-1223


• Perry, B. (2001). In the name of hate: Understanding hate crimes. New York, NY: Routledge.


• National Archive of Criminal Justice Data (NACJD) (2020), The source of data on crime and justice
• Perry, B., and Scrivens, R. (2018). A climate for hate? An exploration of the right-wing extremist landscape in Canada. Critical criminology, 26(2), 169-187.


• Poynting, S., and Perry, B. (2007). Climates of hate: Media and state inspired victimisation of Muslims in Canada and Australia since 9/11. Current Issues in Criminal Justice, 19(2), 151-171.


• Syed, J., and Ali, F. (2020). A Pyramid of Hate Perspective on Religious Bias, Discrimination and Violence. Journal of Business Ethics, 1-16.
• Tan, C. (2020) COVID-19 has prompted a spike in racist attacks. We need to start tracking them better, ABC News
• United Nations (UN) (2020) COVID-19: UN counters pandemic-related hate and xenophobia, Department of Global Communications

Dr Matteo Vergani is Senior Lecturer in Sociology and Senior Research Fellow at the Alfred Deakin Institute for Citizenship and Globalisation. Matteo’s main area of expertise is the study of political violence and hate, with a main focus on the empirical evaluation of prevention and reduction programs in Australia and South East Asia. Matteo is leading a research agenda on the relationships between different forms of hate, including terrorism, hate crime and hate speech. He recently launched the collaborative website www.tacklinghate.org and published over 30 peer-reviewed articles and book chapters on violent extremism and hate.