Hate Crime Reporting Trends in the American South (2021–2023)

Introduction

This project examines hate crime trends across seven Southern U.S. states from 2021 to 2023, with a focus on patterns in bias motivation, reporting quality, and demographic context. Using official FBI-reported data, the analysis examines how states differ in both the volume and consistency of hate crime reporting. By combining incident data with state-level population estimates and legal protections, this project highlights gaps in reporting, the diversity of bias types, and potential trends of underreporting. The goal is not only to visualize the scope of hate crimes but also to assess how transparently and thoroughly different states document these incidents.

Figure 1: Total Hate Crimes by State (2021–2023)

This bar chart displays the total number of reported hate crime incidents per year across seven Southern states. North Carolina consistently reported the highest number of incidents each year, while Louisiana, South Carolina, and Tennessee reported substantially fewer. Notably, most states saw a decline in reported incidents from 2021 to 2023, with Georgia and Mississippi showing sharp drops. This could reflect an actual reduction in incidents, but may also suggest inconsistencies or reductions in reporting practices. The wide variation in totals and year-over-year changes highlights the importance of evaluating not just the raw numbers but also the reporting infrastructure behind them.

Figure 2: Top 10 Hate Crime Bias Motivations (2021–2023)

This horizontal bar chart highlights the most common bias motivations for reported hate crimes across seven Southern states from 2021 to 2023. The majority of incidents were motivated by bias against race, ethnicity, or ancestry, accounting for more than double the next most reported category, religion. Sexual orientation was the third most reported bias type, followed by significantly lower numbers of incidents motivated by gender identity, disability, and gender. These findings reflect broader national patterns while also raising questions about the visibility and reporting of less frequently documented forms of bias.

Figure 3: States with the Highest Number of Reported Hate Crimes (2021–2023)

This table shows the three Southern states with the highest total number of reported hate crime incidents over three years. North Carolina leads with 914 incidents, followed by Alabama and Mississippi, each reporting 680 incidents. While these totals may reflect actual differences in hate crime frequency, they may also be influenced by variations in data reporting practices, law enforcement participation, and local legislation. These findings underscore the need to interpret hate crime data within the context of state-level policies and reporting infrastructure.

Figure 4: Hate Crime Bias Motivations Over Time (2021–2023)

This stacked bar chart illustrates how the distribution of hate crime bias motivations has changed over time across Southern states. While the total number of incidents declined each year, the proportion of incidents within each bias category remained largely consistent. Race/ethnicity/ancestry-based incidents consistently made up the majority of reported cases, followed by religion and sexual orientation. Smaller but steady proportions of incidents were motivated by gender identity, disability, and gender. The overall downward trend may reflect either genuine reductions or shifts in reporting practices, but the persistence of racial and identity-based bias suggests that systemic issues remain a significant driver of hate crime in the region.

Figure 5: Bias Motivations by State (2021–2023)

This chart displays the total number of hate crime incidents by bias motivation for each Southern state in the dataset. North Carolina leads with the highest number of reported incidents, followed by Mississippi and Alabama. Across all states, race/ethnicity/ancestry consistently emerges as the most common motivation, with religion and sexual orientation also appearing prominently. Despite variations in total volume, the relative proportions of bias types remain similar from state to state. This consistency suggests that while reporting levels may differ, the types of bias driving hate crimes in the South share common patterns.

Figure 6: Hate Crime Trends in Southern States (2021–2023)

This line chart tracks annual changes in the number of reported hate crimes across seven Southern states. Most states exhibit a general downward trend in total incidents over the three years, with notable declines in Georgia and Mississippi. North Carolina, while showing a slight dip in 2023, maintained the highest incident count overall. Interestingly, South Carolina and Tennessee experienced slight increases in 2023, which contrasts with the overall pattern. These trends may reflect shifts in community reporting, local enforcement practices, or changes in public visibility of bias-related incidents.

Figure 7: Anti-LGBTQIA+ Hate Crimes by State (2021–2023)

This horizontal bar chart ranks Southern states by the total number of reported hate crime incidents motivated by sexual orientation or gender identity bias. North Carolina and Georgia top the list, each reporting over 120 incidents, followed closely by Mississippi and Alabama. In contrast, Louisiana reported significantly fewer such cases. While this may reflect actual differences, it may also be influenced by underreporting, data collection practices, or social and political climate. The prevalence of anti-LGBTQIA+ bias-related crimes across all states underscores the ongoing need for targeted protections and inclusive reporting systems in the South.

Figure 8: Hate Crimes Motivated by Gender Identity (2021–2023)

This chart shows reported hate crime incidents motivated by bias against gender identity across seven Southern states. Mississippi and Alabama reported the highest totals, with 25 incidents each over the three-year period, followed by Georgia. North Carolina, despite leading in overall hate crime totals, reported fewer gender identity-related incidents, suggesting possible underreporting in this specific category. Louisiana reported no incidents, which may indicate reporting gaps rather than the absence of such crimes. These disparities underscore the importance of collecting inclusive and accurate data to ensure visibility and protection for marginalized communities.

Figure 9: Hate Crimes by State, Year, and Bias Motivation (2021–2023)

This multi-panel chart breaks down hate crime incidents by bias motivation, state, and year. Race/ethnicity/ancestry remains the most consistently reported bias across all states and years, while religion and sexual orientation also show significant incident counts. Gender identity, gender, and disability-related incidents are reported far less frequently, but with notable spikes, such as Mississippi’s rise in gender identity incidents in 2023. These fluctuations may indicate either actual increases in incidents or changes in how specific types of hate crimes are tracked and reported. This visualization highlights how trends vary not only by bias type but also by state-level context and year.

Figure 10: Trends in Hate Crimes by Bias Motivation (2021–2023)

This line chart shows how hate crime incidents shifted across different bias motivations over three years. Incidents motivated by race/ethnicity/ancestry experienced a steady decline but remained the most common by a wide margin. Religion and sexual orientation-related incidents also declined slightly, while gender identity-based hate crimes showed a noticeable increase in 2023, contrasting with overall downward trends. The chart highlights persistent disparities in how different forms of bias manifest over time, with race remaining a dominant factor while anti-LGBTQIA+ hate crimes warrant growing concern.

Underreporting and Low Visibility in Hate Crime Data

While this analysis presents clear patterns in hate crime trends across Southern states, it is crucial to recognize the limitations imposed by underreporting. Hate crimes are historically undercounted for a variety of reasons, including fear of retaliation, lack of trust in law enforcement, and inconsistent reporting practices across jurisdictions. Some states or agencies may not report comprehensive data to the FBI, while others may categorize incidents differently or fail to capture identity-based motivations. For example, states with zero or unusually low counts in specific categories (such as gender identity or disability-related bias) may not necessarily reflect safer conditions, but rather, less robust systems for recognizing and documenting these crimes. Understanding these gaps is critical to interpreting hate crime data responsibly and advocating for more inclusive and transparent reporting standards.

Figure 11: Variance-Based Reporting Score by State (2021–2023)

This table introduces a calculated “reporting quality score” based on the variability in hate crime incidents over time across seven Southern states. The score combines the number of unique bias categories reported, years of consistent data, and the variance in incident totals. Higher scores (like Georgia and Louisiana) suggest more dynamic reporting activity, potentially reflecting more complete or responsive data practices. Lower or negative scores (such as North Carolina and South Carolina) may signal flat or inconsistent reporting, rather than a genuine absence of hate crimes. While not definitive, this metric offers one lens for identifying where underreporting may be occurring and where additional investigation or support for data infrastructure is needed.

Figure 12: Low or Missing Hate Crime Reporting by Bias Motivation

This table highlights states with extremely low or missing reported hate crime incidents for specific bias motivations between 2021 and 2023. For example, Louisiana reported zero hate crimes motivated by gender identity, and both South Carolina and Tennessee reported only two or three total incidents related to gender bias. These counts raise concerns about underreporting rather than the actual absence of such crimes. Discrepancies like these are common in hate crime data, often driven by limitations in data collection, lack of training on recognizing identity-based bias, or policy decisions that deprioritize specific categories. Identifying these reporting gaps is essential to building more accurate and inclusive public safety data.

Figure 13: Policy Landscape and Reporting Quality by State

To better understand the relationship between hate crime reporting and policy environment, this table includes each state’s total incidents, population size, the presence of hate crime laws and LGBTQIA+ protections, and calculated incident rates per 100,000 residents. Mississippi stands out with the highest per capita rate (22.96 incidents per 100,000) despite having no statewide hate crime law or LGBTQ protections—suggesting either robust local enforcement or concentrated victimization. In contrast, Georgia shows a relatively low incident rate (5.48), but benefits from both hate crime statutes and LGBTQ protections, which may contribute to improved policy alignment and safer conditions. North Carolina reports the highest total incidents, but its per capita rate remains moderate, perhaps reflecting better data infrastructure. These metrics emphasize how legal protections, population scale, and social climate collectively shape both the visibility and frequency of hate crime reporting across the Southern U.S.

Figure 14: Reporting Quality Score by State

This visualization represents each state’s reporting consistency by calculating a z-scaled score of incident variance across the three years of available data. Higher scores indicate greater year-to-year fluctuation, which may suggest more reactive or inconsistent reporting practices. Georgia and Louisiana top the chart, indicating highly variable reporting that may reflect fluctuations in enforcement or inconsistent local efforts. On the other hand, North Carolina, Tennessee, and South Carolina exhibit lower and even negative scores, suggesting steadier—or potentially underreported—data over time. Notably, North Carolina had the highest total incidents but the lowest consistency score, underscoring a possible disconnect between overall case volume and year-over-year reliability. These scores offer a useful diagnostic for evaluating data quality and reliability in hate crime reporting frameworks.

Figure 15: Total Hate Crimes vs. Population

This scatterplot compares the total number of hate crimes to the population of each Southern state studied. As expected, states with larger populations, such as North Carolina and Georgia, tend to report higher total incident rates. However, some outliers reveal deeper dynamics. Mississippi, despite having one of the smallest populations, reports a high number of incidents, suggesting a disproportionately high rate of hate crimes per capita. Meanwhile, Tennessee, with a moderate population, shows relatively lower incident volume. This visualization reinforces the importance of considering population-adjusted metrics, such as incidents per 100,000 residents, to more accurately assess the relative severity and prevalence of hate crimes in each state.

Figure 16: Hate Crime Incidents per 100,000 People

This bar chart normalizes hate crime data by state population to provide a more equitable comparison of hate crime rates. Mississippi and Alabama stand out with the highest rates, reporting over 20 and 13 incidents per 100,000 residents, respectively. In contrast, larger states like Georgia and Tennessee report much lower per-capita rates, despite having higher total populations. This suggests that raw totals alone can obscure the intensity of hate crimes relative to population size. By viewing data on a per-100K basis, we gain clearer insights into which states are experiencing disproportionate levels of bias-motivated violence, potentially signaling gaps in prevention, community support, or policy enforcement.

Conclusion

The data paints a sobering picture of hate crime trends across the Southern United States. Despite regional, demographic, and policy differences, bias-motivated incidents persist as a deeply rooted and persistent issue. Our analysis reveals not only that Race, Ethnicity, and Ancestry continue to be the most frequent motivations for hate crimes, but also that LGBTQIA+ and Gender Identity-based hate remains alarmingly underreported or overlooked in several states.

Moreover, by normalizing incidents by population and examining reporting consistency, we uncovered critical disparities in data quality and transparency, highlighting that states with low or inconsistent reporting may not necessarily be safer; instead, they may lack sufficient infrastructure, protections, or political will to document hate crimes accurately.

This project serves as both a data-driven snapshot and a call to action, urging the need for improved reporting, enhanced protections, and targeted interventions that address the systemic factors driving these crimes. As data analysts, public servants, and community members, we must continue to surface uncomfortable truths and transform them into evidence-backed advocacy.

Key Takeaways

• Race, Ethnicity, and Ancestry are the leading motivations for hate crimes across all seven Southern states from 2021–2023, accounting for over half of all reported incidents.

• North Carolina reported the highest number of hate crimes, while states like Louisiana and South Carolina reported far fewer—raising questions about underreporting or data collection limitations.

• Anti-LGBTQIA+ hate crimes are significantly underreported in some states. For example, Louisiana reported zero incidents of hate crimes based on Gender Identity over three years.

• When adjusted for population, Mississippi and Alabama had the highest rate of hate crime incidents per 100,000 people, highlighting that smaller states are not immune to high impact.

• A custom reporting quality score revealed wide inconsistencies in data variance and completeness, suggesting potential gaps in how states track and report bias-motivated crimes.

• States without LGBTQIA+ legal protections or comprehensive hate crime laws often coincided with lower reporting or more volatile data patterns.

• Despite overall decreases in reported incidents from 2021 to 2023, certain bias categories like Gender Identity saw an increase, signaling a shifting landscape that demands continued monitoring.

Summary

This project examines hate crime data from seven Southern U.S. states between 2021 and 2023, focusing on the total number of incidents, bias motivations, reporting trends, and the legal context. The analysis reveals that Race, Ethnicity, and Ancestry remain the leading causes of hate crimes, followed by Religion and Sexual Orientation. While states like North Carolina lead in reported incidents, others, such as Louisiana and South Carolina, show signs of underreporting despite similar population sizes.

Further, the data highlights troubling disparities in anti-LGBTQIA+ hate crime reporting, especially in states lacking protective laws. A custom reporting quality score and incident rate per 100,000 people provide additional insight into which states may be underreporting or inconsistently tracking incidents. Ultimately, this analysis underscores the urgent need for more standardized and transparent hate crime reporting practices across the region.

All visualizations were created using R with ggplot2, and all datasets were cleaned and compiled manually using public government resources.