In 2017, there were over *** cases of cyber crime related to social media across India. This was a marginal spike in crime cases compared to the previous year when there were just over *** cases of social media cyber crime reported in the country.

This case study is part of a series on the ethics of social media data use by third parties.

As of the fourth quarter of 2023, impersonation was the leading cybersecurity threat worldwide, targeting organizations on social media platforms, accounting for 45 percent of reported incidents. Fraud was the second most prevalent threat, making up 28.23 percent of cases, while cyber threats, such as malicious activities like hacking and phishing, made up over 21 percent of the total threats in the examined period.

In the first half of 2023, investment-related scams accounted for the highest share of costs of scams, ** percent, performed on social media. Romance scams ranked second, with ** percent of financial losses from scams performed on social media.

The datasert contains year- and state-wise historiclally compiled data on the number of cyber crimes committed in violation of Indian Penal Code (IPC). The different types of cyber crimes covered in the dataset include Abetment of Suicide - Online, Cyber Stalking or Bullying of Women or Children, Data theft, Cheating, Forgery, Defamation or Morphing (IPC r/w Indecent Representation of Women Act), Fake Profile (IPC r/w SLL), Counterfeiting, Cyber Blackmailing or Threatening, Fake News on Social Media, Other Offences (r/w IT Act), Fabrication of False Evidence/Destruction of Electronic Records for, Evidence, Offences By or Against Public Servant, False Electronic Evidence, Destruction of Electronic Evidence, Crimes of Property or Mark such as Counterfeiting, Tampering, Currency or Stamps, Crimes of Fraud such as Crimes related to Credit or Debit Card, Any Time Machines (ATMs), Online Banking Fraud, OTP Frauds, Crimes of Criminal Breach of Trust or Fraud such as crimes of Credit or Debit card, Crimes of Counterfeiting of Currecy, Stamps and Tampering, etc.

Estimates from Crime Survey for England and Wales (CSEW) on fraud and computer misuse. Also data from Home Office police recorded crime on the number of online offences recorded by the police and Action Fraud figures broken down by police force area.

These tables were formerly known as Experimental tables.

Please note: This set of tables are no longer produced. All content previously released within these tables has, or will be, redistributed among other sets of tables.

Crime Analytics Tool Market Outlook

The global crime analytics tool market size was valued at approximately USD 5.4 billion in 2023 and is projected to reach around USD 12.1 billion by 2032, growing at a CAGR of 9.5% during the forecast period. The substantial growth in the crime analytics tool market can be attributed to the increasing adoption of advanced technologies by law enforcement agencies and the rising incidences of crime globally, which necessitates more sophisticated methods of crime prevention and analysis.

One of the main growth factors driving the crime analytics tool market is the rapid technological advancements in big data analytics and artificial intelligence (AI). These technologies are being increasingly integrated into crime analytics tools, providing law enforcement agencies with powerful capabilities to analyze vast amounts of data quickly and accurately. Additionally, the proliferation of smart city initiatives across the globe is further fueling the demand for these tools, as they play a crucial role in enhancing the security infrastructure of urban environments. The ability of crime analytics tools to predict and prevent criminal activities by analyzing patterns and trends is proving to be invaluable in maintaining public safety.

Another significant driver of market growth is the increasing collaboration between public and private sectors in enhancing security measures. With the rise in cybercrimes and terrorism, both government agencies and private security firms are investing heavily in advanced crime analytics solutions. This collaboration is not only improving the overall effectiveness of crime prevention strategies but also driving innovations within the market. Furthermore, the growing awareness among law enforcement agencies about the benefits of crime analytics tools, such as improved response times and resource allocation, is contributing to the market's expansion.

The integration of Internet of Things (IoT) devices and surveillance systems with crime analytics tools is also propelling the market forward. IoT devices generate massive amounts of data that can be analyzed to gain insights into potential threats and criminal activities. By incorporating data from various sources such as CCTV footage, social media, and other digital platforms, crime analytics tools can provide a comprehensive overview of the security landscape, aiding in more effective decision-making. This holistic approach to crime prevention is becoming increasingly essential in today's interconnected world.

Regionally, North America holds the largest market share due to the early adoption of advanced technologies and the presence of several key players in the region. The strong focus on homeland security and substantial investments in public safety infrastructure are also contributing factors. Europe follows closely, with significant growth driven by stringent regulations and increasing efforts to combat organized crime. The Asia Pacific region is expected to witness the highest CAGR during the forecast period, fueled by rapid urbanization, increasing crime rates, and significant government investments in smart city projects. Latin America and the Middle East & Africa are also expected to see notable growth, driven by improving economic conditions and heightened security concerns.

Component Analysis

The crime analytics tool market is segmented into three primary components: software, hardware, and services. The software component dominates the market, driven by the increasing demand for advanced analytical solutions capable of processing large datasets and generating actionable insights. Crime analytics software includes various applications such as predictive analytics, data mining, and visualization tools that enable law enforcement agencies to identify crime patterns and trends effectively. The continuous advancements in AI and machine learning algorithms are further enhancing the capabilities of these software solutions, making them indispensable tools for modern crime prevention.

Hardware components, although smaller in market share compared to software, play a crucial role in the overall crime analytics ecosystem. This segment includes surveillance cameras, sensors, and other IoT devices that collect real-time data essential for comprehensive crime analysis. The integration of high-definition cameras, facial recognition systems, and biometric devices with crime analytics software is significantly improving the accuracy and efficiency of crime detection and prevention efforts. As the demand for robust security infrastructure continues to rise,

In the United States, a number of challenges prevent an accurate assessment of the prevalence of hate crimes in different areas of the country. These challenges create huge gaps in knowledge about hate crime--who is targeted, how, and in what areas--which in turn hinder appropriate policy efforts and allocation of resources to the prevention of hate crime. In the absence of high-quality hate crime data, online platforms may provide information that can contribute to a more accurate estimate of the risk of hate crimes in certain places and against certain groups of people. Data on social media posts that use hate speech or internet search terms related to hate against specific groups has the potential to enhance and facilitate timely understanding of what is happening offline, outside of traditional monitoring (e.g., police crime reports). This study assessed the utility of Twitter data to illuminate the prevalence of hate crimes in the United States with the goals of (i) addressing the lack of reliable knowledge about hate crime prevalence in the U.S. by (ii) identifying and analyzing online hate speech and (iii) examining the links between the online hate speech and offline hate crimes. The project drew on four types of data: recorded hate crime data, social media data, census data, and data on hate crime risk factors. An ecological framework and Poisson regression models were adopted to study the explicit link between hate speech online and hate crimes offline. Risk terrain modeling (RTM) was used to further assess the ability to identify places at higher risk of hate crimes offline.

In 2024, the Directorate for Investigating Organized Crime and Terrorism in Romania closed ***** cybercrime cases. However, the number of pending cases has increased by **** percent since 2023.       Cybercrime in Romania  Cybercrime poses a significant challenge in Romania, with distinct patterns observed across regions and varying attack methods. The Bucharest-Ilfov region stands out, as **** percent of respondents reported using software programs to limit online activity tracking in 2023, indicating a notable concern for digital privacy. In contrast, the North-West region had a lower adoption rate at *** percent. Regarding malware threats, Trojan.AgentACBD led the charts in 2023, registering ****** attack alerts, closely followed by Trojan.IoT.Mirai and InfoStealer.AGENTTESLA. Phishing attacks fluctuated, peaking at ****** incidents in April 2023 but dropping to ***** in December 2023. This dynamic landscape underscores the need for robust cybersecurity measures nationwide.       Online Video Games  The digital landscape is evolving, marked by notable shifts in women's internet usage. While the overall share of internet users has risen for both genders, the gender gap has significantly narrowed. In 2024, female internet users lagged males by only *** percent, a substantial improvement from the *** percent gap in 2019. Social media usage remained the most popular online activity for women. However, a noteworthy trend is women's substantial use of the internet to gather health-related information, showcasing a diversified gender digital presence.

AI in Crime Prevention Market Outlook

According to our latest research, the global AI in Crime Prevention market size reached USD 6.2 billion in 2024, reflecting robust momentum in adoption across public and private sectors. The market is experiencing significant expansion, driven by the urgent need for advanced security solutions and the rising sophistication of criminal tactics. The compound annual growth rate (CAGR) is estimated at 23.8% from 2025 to 2033. By leveraging this CAGR, the market is forecasted to reach USD 51.6 billion by 2033. This growth trajectory is underpinned by the integration of artificial intelligence in surveillance, predictive policing, and cybersecurity, as organizations globally prioritize proactive crime prevention strategies.

The primary growth factor propelling the AI in Crime Prevention market is the escalating complexity and frequency of criminal activities, both in the physical and digital realms. Traditional crime prevention methodologies are increasingly being outpaced by sophisticated offenders utilizing technology to evade detection. AI-powered tools, such as machine learning algorithms, facial recognition, and behavioral analytics, have emerged as game-changers, allowing for real-time threat identification, predictive analysis, and automated response. The adoption of these technologies is not only enhancing the efficiency of law enforcement agencies but also enabling businesses to safeguard critical assets and sensitive data, thus fueling market expansion.

Another significant driver is the rapid digital transformation across sectors, which has expanded the attack surface for cybercrime and necessitated advanced defense mechanisms. Financial institutions, government agencies, and retailers are particularly vulnerable to fraud, data breaches, and other malicious activities. AI in crime prevention is providing these entities with the ability to detect anomalies, flag suspicious transactions, and respond swiftly to incidents. Furthermore, the proliferation of IoT devices and interconnected infrastructure has increased the demand for AI-based surveillance and monitoring solutions, ensuring that threats are identified and neutralized before they escalate into larger security breaches.

The evolution of regulatory frameworks and public safety initiatives is further accelerating the growth of the AI in Crime Prevention market. Governments worldwide are investing heavily in smart city projects, integrating AI into public surveillance networks, traffic management systems, and emergency response protocols. These investments are fostering collaborations between public agencies and technology providers, leading to the development of innovative, scalable crime prevention platforms. Additionally, growing public awareness about the benefits of AI-driven safety measures is contributing to higher adoption rates, especially in urban centers where crime rates are typically higher.

Regionally, North America continues to dominate the AI in Crime Prevention market, accounting for the largest share in 2024, driven by substantial investments in security infrastructure, advanced technological adoption, and the presence of major market players. Europe follows closely, benefiting from stringent data protection laws and a proactive approach to public safety. The Asia Pacific region is witnessing the fastest growth, fueled by rapid urbanization, government-led digitalization initiatives, and increasing crime rates in densely populated cities. Latin America and the Middle East & Africa are also making strides, albeit at a slower pace, as they progressively modernize their security apparatus and embrace AI-driven solutions.

Component Analysis

The Component segment of the AI in Crime Prevention market is categorized into software, hardware, and services, each playing a pivotal role in the ecosystem. Software solutions form the backbone of AI-driven crime prevention, encompassing advanced analytics, facial recognition, natural language processing, and behavioral analysis platforms. These solutions are designed to process vast volumes of structured and unstructured data, enabling real-time threat detection and predictive insights. The demand for AI software is surging, particularly among law enforcement and financial institutions, as they seek to automate surveillance, monitor social media for threats, and detect fraudulent activities with greater accuracy and speed.

The research project is a subproject of the research association “Strengthening of integration potentials within a modern society” (Scientific head: Prof. Dr. Wilhelm Heitmeyer, Bielefeld) which contains 17 subprojects and is supported by the ministry of education and research. In almost all the economically highly developed countries violent crime increased significantly in the second part of the last century - in contrast to the long term trend of decline of individual (non-governmental) violence since the beginning of modern times. The authors develop an explanatory approach for these facts which is inspired mainly by Norbert Elias´s civilization theory and Emil Durkheim´s theory on society. Detailed time series on the development of different forms of violent crime are presented and set in relation with certain aspects of economic and social structural changes in three countries and also refer to the changes in integration of modern societies. The analysis deals especially with effectivity and legitimacy of the governmental monopoly of violence, the public beneficial security and power system, forms of building social capital, economic and social inequality, precarity of employment, different aspects of increasing economization of society, changes in family structures and usage of mass media and modern communication technologies. Register of tables in HISTAT: A: Crime statistics A.01 Frequency of types of crimes in different countries (1953-2000) A.02 Suspects by crimes of 100.000 inhabitants of Germany, England and Sweden (1955-1998) A.03 Murders, manslaughter and intentional injuries by other persons by sex of 100.000 persons after the statistics of causes of death (1953-2000) A.04 Clearance rate by types of crimes in Germany, England and Sweden (1953-1997) A.05 Prisoners of 100.000 inhabitants of Germany, Great Britain and Sweden (1950-2000) B: Key indicators for economic development in Germany, Great Britain, Sweden and the USA B1: Data on the overall economic framework B1.01 Percent changes in the real GDP per capita in purchasing power parities (1956-1987) B1.02 Percent changes in GDP per capita in prices from 2000 (1955-1998) B1.03 GDP of Germany, Sweden and the United Kingdom in purchasing power parities in percent og the US GDP (1950-1992) B1.04 Labor productivity index for different countries, base: USA 1996 = 100 (1950-1999) B1.05 GDP per hour of labor in different countries in EKS-$ from 1999 (1950-2003) B1.06 Foreign trade - exports and imports in percent of the GDP of different countries (1949-2003) B1.07 GDP, wages and Unit-Labor-Cost in different countries (1960-2003) B2: Unemployment B2.01 Standardized unemployment rate in different countries with regard to the entire working population (1960-2003) B2.02 Share of long-term unemployed of the total number of unemployed in different countries in percent (1992-2004) B2.03 Youth unemployment in different countries in percent (1970-2004) B2.04 Unemployment rate in percent by sex in different countries (1963-2000) B3: Employment B3.01 Employment rate in percent in different countries (1960-2000) B3.02 Share of fixed-term employees and persons in dependent employment in percent in different countries (1983-2004) B3.03 Share of part-time employees by sex compared to the entire working population in different countries (1973-2000) B3.04 Share of un-voluntarily part-time employees by sex in different countries (1983-2003) B3.05 Share of contract workers in different countries in percent of the entire working population (1975-2002) B3.06 Share of self-employed persons in different countries in percent of the entire working population (1970-2004) B3.07 Shift worker rate in different countries in percent (1992-2005) B3.08 Yearly working hours per employee in different countries (1950-2004) B3.09 Employment by sectors in different countries (1950-2003) B3.10 Share of employees in public civil services in percent of the population between 15 and 64 years in different countries (1960-1999) B3.11 Female population, female employees and female workers in percent of the population between 16 and 64 years in different countries (1960-2000) B3.12 Employees, self-employed persons in percent of the entire working population in different countries (1960-2000) B4: Taxes and duties B4.01 Taxes and social security contributions in percent of the GDP (1965-2002) B4.02 Social expenditure in percent of the GDP (1965-2002) B4.03 Social expenditure in percent of the GDP (1960-2000) B4.04 Public expenditure in percent of the GDP in different countries (1960-2003) B4.05 Education expenditure in percent of GDP (1950-2001) B5: Debt B5.01 Insolvencies in Germany and England (1960-2004) B5.02 Insolvencies with regard to total population in different countries (1950-2002) B5.03 Consumer credits in different countries (1960-2002) C: Income distribution in Germany, Great Britain and Sweden C.01 Income inequality in different countries Einkommensungleicheit in verschiedenen Ländern (1949-2000) C.02 Income inequality after different indices and calculations in different countries (1969-2000) C.03 Redistribution: Decline in Gini-Index through transfers and taxes in percent in different countries (1969-2000) C.04 Redistribution: Decline in Gini-Index through transfers and taxes in percent with a population structure as in the United Kingdom in 1969 in different countries (1969-2000) C.05 Redistribution efficiency: Decline in Gini-/ Atkinson-Index through transfers and the share of social expenditure of the GDP in different countries (1969-2000) C.06 Index for concentration of transfers in different countries (1981-2000) C.07 Distribution of wealth in West-Germany (1953-1998) C.08 Distribution of wealth in the United Kingdom (1950-2000) C.09 Distribution of wealth in Sweden (1951-1999) C.10 Relative income poverty in different countries (1969-2000) C.11 Reduction of poverty in different countries (1969-2000) C.12 Neocorporalism index in different countries (1960-1994) D: Perception of safety D.01 Satisfaction with democracy in different countries (1976-2004) D.02 Revenues and employees in the private security sector in different countries (1950-2001) D.03 Decommodification-Score in different countries (1971-2002) E: Demographics E.01 Birth rates: Birth per 1000 women between 15 and 49 years in different countries (1951-2001) E.02 Fertility rate in different countries (1950-2004) E.03 Marriages per 100.000 persons in different countries (1950-2003) E.04 Share of foreigners of the entire population in different countries (1951-2002) E.05 Internal migration in different countries (1952-2001)

Crime Analytics Software Market Outlook

The global crime analytics software market size is poised for robust growth, with projections indicating a rise from USD 2.5 billion in 2023 to an impressive USD 5.8 billion by 2032, reflecting a compound annual growth rate (CAGR) of approximately 9.5%. This substantial growth is driven by the increasing need for sophisticated crime detection and prevention tools in both public and private sectors, spurred by rising security concerns globally.

One of the primary growth factors fueling this market is the escalating incidence of criminal activities worldwide, which necessitates advanced analytical tools for effective crime prevention and investigation. Governments and law enforcement agencies are increasingly investing in advanced technologies to enhance their crime-fighting capabilities. Additionally, the integration of artificial intelligence (AI) and machine learning (ML) in crime analytics software is revolutionizing the way data is analyzed and utilized, leading to more accurate and timely insights.

Furthermore, the advancement in big data analytics is another significant driver for the crime analytics software market. With the exponential growth of data generated from various sources such as social media, surveillance cameras, and sensors, there is a crucial need for systems that can handle and analyze large volumes of data efficiently. Big data analytics enables the extraction of actionable insights from complex datasets, aiding in predictive policing and crime pattern analysis.

Moreover, the growing adoption of cloud-based solutions is contributing significantly to market growth. Cloud-based crime analytics software offers several advantages, including scalability, cost-effectiveness, and enhanced accessibility. These solutions allow organizations to manage and analyze large datasets without the need for substantial investments in infrastructure. As a result, small and medium-sized enterprises (SMEs) and government agencies with limited budgets are increasingly turning to cloud-based solutions.

Regionally, North America holds the largest share of the crime analytics software market due to the early adoption of advanced technologies and the presence of major market players in the region. Additionally, the stringent regulatory framework and high focus on public safety and national security drive the demand for crime analytics solutions in this region. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by the rising focus on smart city initiatives and increasing government investments in security infrastructure.

Component Analysis

The crime analytics software market can be segmented by components into software and services. The software component includes various types of crime analytics platforms and solutions that are used for data collection, analysis, and visualization. These software solutions are designed to provide law enforcement agencies and security organizations with the tools needed to analyze crime data effectively and make informed decisions. The increasing demand for real-time analytics and the integration of advanced technologies like AI and ML are driving the growth of the software segment.

On the other hand, the services segment encompasses a range of support and maintenance services, consulting services, and training programs offered by vendors to ensure the effective deployment and utilization of crime analytics software. These services are crucial for the smooth operation and optimization of crime analytics systems. As organizations look to maximize the value of their crime analytics investments, the demand for professional services is expected to rise. This segment is also driven by the increasing complexity of analytics solutions, which requires specialized expertise for deployment and maintenance.

In the software segment, the adoption of AI-powered crime analytics tools is gaining momentum. These tools leverage machine learning algorithms to identify patterns, predict potential criminal activities, and provide actionable insights. The ability to process and analyze vast amounts of data in real-time is a key factor driving the adoption of such solutions. Additionally, advancements in natural language processing (NLP) are enhancing the capabilities of crime analytics software, enabling it to understand and analyze unstructured data from sources like social media and open-source intelligence.

Furthermore, the services segment is witnessing significant grow

The Public Safety Analytics market, valued at $8.313 billion in 2025, is projected to experience robust growth, exhibiting a compound annual growth rate (CAGR) of 9.1% from 2025 to 2033. This expansion is driven by several key factors. Increasing crime rates and the need for proactive crime prevention strategies are compelling law enforcement agencies to adopt sophisticated analytical tools. Furthermore, the rising demand for improved emergency response times and resource allocation efficiency in firefighting and medical emergency services fuels market growth. The integration of advanced technologies like AI and machine learning enhances predictive policing capabilities, enabling agencies to identify crime hotspots and deploy resources strategically. The shift towards cloud-based solutions offers scalability, cost-effectiveness, and improved data accessibility, further driving market adoption. Growth is also fueled by the increasing availability of diverse data sources, including CCTV footage, social media, and sensor networks, providing richer insights for analytics. The market is segmented by application (Law Enforcement, Medical, Firefighting, Transportation, Others) and deployment type (Cloud-Based, On-Premises), with the cloud-based segment expected to dominate due to its inherent advantages. Geographically, North America currently holds a significant market share, followed by Europe and Asia Pacific, with the latter region poised for substantial growth due to increasing government investments in public safety infrastructure and technology. Significant restraints include the high initial investment costs associated with implementing sophisticated analytics systems and the need for skilled personnel to manage and interpret the complex data. Data privacy and security concerns also pose challenges, requiring robust security protocols and adherence to data protection regulations. However, the long-term benefits of improved public safety and efficient resource management are expected to outweigh these challenges, sustaining the market's overall growth trajectory. The competitive landscape is characterized by a mix of established technology vendors and specialized public safety solutions providers, fostering innovation and competition. This dynamic environment ensures continuous improvement in the quality, efficiency, and affordability of public safety analytics solutions.

The Public Safety Analytics market, valued at $8.313 billion in 2025, is projected to experience robust growth, driven by increasing crime rates, the need for improved emergency response times, and the rising adoption of advanced technologies like AI and machine learning. This growth is further fueled by the increasing availability of data from various sources, including surveillance cameras, social media, and sensor networks, providing valuable insights for predictive policing and resource allocation. Key application segments, such as law enforcement and firefighting, are spearheading this expansion, leveraging analytics for crime prevention, incident response optimization, and resource management. The shift towards cloud-based solutions offers scalability and cost-effectiveness, contributing significantly to market expansion. While data privacy and security concerns pose a challenge, the development of robust security measures and regulatory compliance frameworks are mitigating these risks. The market's geographical distribution shows strong presence in North America and Europe, driven by advanced infrastructure and high adoption rates. However, emerging economies in Asia-Pacific are expected to show significant growth potential in the coming years, driven by increasing government investments in public safety infrastructure and technological advancements. Competition is intense, with established players like IBM, Hexagon, and Cisco vying for market share alongside specialized analytics firms. The market's future growth will be shaped by the continued development of advanced analytical tools, improved data integration capabilities, and the increasing focus on proactive rather than reactive public safety strategies. The forecast period from 2025 to 2033 anticipates a significant expansion of the Public Safety Analytics market, fueled by the continuous integration of big data and advanced analytics techniques. This will lead to improved situational awareness, optimized resource deployment, and enhanced crime prevention capabilities. The increasing adoption of predictive policing models, leveraging historical crime data and real-time information, will further propel market growth. The ongoing development of innovative technologies like IoT sensors and drones will enhance data collection and analysis capabilities. Government initiatives to improve public safety and the rising adoption of cloud-based solutions will also contribute to market expansion. However, factors such as the high cost of implementation and the need for skilled professionals to interpret and utilize the generated insights may present some challenges. The market's competitive landscape will likely see strategic partnerships and mergers and acquisitions among existing players as they strive to expand their market share and offer comprehensive solutions. Ultimately, the Public Safety Analytics market is poised for sustained growth, driven by a constant need for improved efficiency, effectiveness, and proactive strategies in public safety management.

Ponzi schemes that offer absurdly high rates of return by relying on more and more people paying into the scheme have been documented since at least the mid-1800s. Ponzi schemes have shifted online in the Internet age, and some are re-branded as HYIPs or High Yield Investment Programs. This paper focuses on understanding HYIPs' continuous presence and presents various possible reasons behind their existence in today's world. A look into the countries where these schemes purport to exist, we find that 62.89% of all collected HYIPs claim to be in the United Kingdom (UK), and a further 55.56% are officially registered in the UK as a 'limited company' with a registration number provided by the UK Companies House, a UK agency that registers companies. We investigate other factors influencing these schemes, including the HYIPs' social media platforms and payment processors. The lifetime of the HYIPs helps to understand the success/failure of the investment schemes and helps indicate the schemes that could attract more investors. Using Cox proportional regression analysis, we find that having a valid UK address significantly affects the lifetime of an HYIP.

We study whether social media can amplify anti-minority sentiments with a focus on Donald Trump's political rise. Using an instrumental variable strategy based on Twitter's early adopters at the South by Southwest festival in 2007, we find that higher Twitter use in a county is associated with a sizeable increase in anti-Muslim hate crimes after the 2016 presidential primaries. Trump's tweets about Muslims predict increases in xenophobic tweets by his followers, cable news mentions of Muslims, and hate crimes on the following days. These results suggest that social media content can affect real-life outcomes.

Selection of time series of different scientific publications and of publication of the official statistics:

EUROSTAT, European Statistical Office OECD: Organisation for Economic Cooperation and Development; ONS: Office for National Statistics, England; SCB: Statistiska Centralbyran, Sweden; Federal Statistical Office, Wiesbaden. Deutschland; WHO: World Health Organization.

Details related to access to the data

No data user agreement

• Contact person

Corinna Perchtold-Stefan, corinna.perchtold@uni-graz.at, ORCID: https://orcid.org/0000-0002-8334-0574 Christian Rominger, christian.rominger@uni-graz.at, ORCID: https://orcid.org/0000-0003-3195-4555

Overview

Project name: Horror as creative emotion regulation – Can true crime consumption help boost adaptive coping with fear and stress? Years: 01.01.2023 to 31.05.2024 Funding: Country of Styria, 2022 Call “Unconventional Science”, P11928 Ethics vote: University of Graz, Austria, GZ. 39/4/63 ex 2022/23

Relevant behavioral data are available at https://osf.io/phx9d/.

• [ ] Brief overview of the tasks in the experiment

The neuroscience data is part of a larger research project on the psychology and neuroscience of people’s interest in true crime – the narration of real-life crime stories in various media (books, podcasts, movies, TV, news). The main goal of the project is to provide a first, in-depth investigations of cognitive, affective, social, and brain correlates of true crime consumption with a particular focus on motives, traits, and perceptions of true crime consumers as well as potential consequences of true crime consumption with regard to well-being and mental health. Additionally, this study is used as an overarching investigations of aspects influencing behavior and well-being in daily life, including measures of creativity, emotion regulation, the experience of meaningful coincidences, curiosity, also with regard to potential interindividual differences regarding gender, age, or socioeconomic background.

• [ ] Contents of the dataset

• [ ] Variables

All questionnaires were administered in German.  Demographic data (gender, age, education, income, relationship status, living area, psychiatric/neurological diagnosis)  True crime consumption and motivations (McDonald et al., 2021)  Morbid curiosity (Scrivner, 2021)  Big-5 personality (Rammstedt et al., 2013)  Dark triad (Malesza et al., 2019)  Depressive symptoms (Hautzinger & Bailer, 1993)  Trait anxiety (Spielberger, 2001)  Perceived stress (Klein et al., 2016)  Resilience (Chmitorz et al., 2018)  Worry and Paranoid Worry (Freeman et al., 2019)  Aggression (Bryant & Smith, 2001)  Meaningful coincidences (Bressan, 2002)  Likelihood of victimization (Kerestly, 2021)  Media preferences (Scrivner, 2021)  Cognitive emotion regulation (Loch et al., 2011)  Cognitive reappraisal capacity (Weber et al., 2014)  Malevolent creativity (Perchtold-Stefan et al., 2021)

(see https://osf.io/phx9d/)

Methods

Subjects

N = 133 for MRI

Participants were recruited on university campus, through advertisements via press reports, social media, and mailing lists. Participants were recruited for a larger study in true crime consumption, and could in the context of this study also take part in the MRI scan. The only exclusion criteria for study participation was previous experience with the performance tasks (cognitive reappraisal capacity, malevolent creativity).

Task organization

No tasks during MRI – only structural scan sand resting-state scans Tasks outside of MRI: Brief online assessment (~ 10 min), in person behavioral testing at the University (~ 2 hours)

Additional data acquired

See above

Experimental location

University of Graz, Austria, and Technical University of Graz, Austria

Missing data

Since this study was realized in multiple parts, not all data is available from all participants. In total, MRI scans of n = 133 participants were acquired From these participants, data from n = 2 participants had to be removed to due data quality and no behavioral and questionnaire data. Data of n = 101 participants is available for extended demographic data, Big-5 personality, dark triad, worry and paranoid worry, meaningful coincidences, likelihood of victimization, media preferences, and cognitive emotion regulation

The global crime analytics software market is experiencing robust growth, driven by the increasing need for law enforcement agencies and other organizations to leverage data-driven insights for enhanced crime prevention, investigation, and resource allocation. The market's expansion is fueled by several key factors, including the proliferation of readily available data sources (e.g., CCTV footage, social media, sensor data), advancements in artificial intelligence (AI) and machine learning (ML) algorithms for predictive policing, and growing government initiatives promoting public safety. The integration of crime analytics software with existing law enforcement systems is further streamlining operations and improving response times. While challenges such as data privacy concerns, integration complexities, and the high cost of implementation exist, the overall market outlook remains positive, with a projected steady Compound Annual Growth Rate (CAGR) over the forecast period (2025-2033). The market is segmented by software type (predictive policing, crime mapping, investigation support), deployment mode (cloud-based, on-premise), and end-user (law enforcement, government agencies, private security). Competition in the crime analytics software market is intense, with established players like LexisNexis, IBM, and Motorola Solutions competing alongside emerging technology providers such as ShotSpotter and PredPol. These companies are focusing on innovation, strategic partnerships, and mergers and acquisitions to expand their market share and offer comprehensive solutions. The North American region currently dominates the market due to advanced technology adoption and high government spending on public safety. However, other regions, particularly in Europe and Asia-Pacific, are witnessing significant growth driven by increasing urbanization and rising crime rates. The ongoing focus on improving accuracy, reducing bias in algorithms, and ensuring ethical data practices will shape the market's trajectory in the coming years. Future growth will likely be propelled by the increased adoption of advanced analytics techniques, such as real-time crime forecasting and risk assessment, along with the integration of IoT devices and sensor networks into crime analytics platforms.

To identify vulnerabilities in self-regulatory practices, we focused on what we expected to be five social media platforms with a major role in sharenting practices, which were selected considering their demographic distribution among the population, and following a discussion with our non-academic project partners: Facebook; TikTok; Instagram; You Tube; Twitter. Textual data was retrieved from each of these platforms’ relevant self-regulatory documents (mostly terms and conditions, and community standards, even if some additional documents targeting, for instance, specifically parents were identified and considered for the analysis). This data is publicly available online and, after an initial screening, all sections of the documents that could (broadly) be relevant to sharenting, digital harms and crimes, moderation practices, minors and their parents/guardians were selected for the analysis and collated in the file here avilable.

Especially over the past 15 years, the creation of new "online identities" (the social identity that we acquire in cyberspace) and the expansion of the usability of our "digital identity" (the digital storage of our attributed, biographical or even biological identities) have entailed, alongside many advantages, also new and emerging risks and crime vulnerabilities, as identity information can be misused in many ways and create severe harms. Existing research in this context has so far focused on the illegal access to personal information (e.g. through hacking or social engineering techniques) but has overlooked the risky behaviours of individuals willingly sharing identifying (and potentially sensitive) information online. In this context, an area of particular interest that has been particularly overlooked is the one connected to the sharing of identifying and sensitive information of minors, who are often overexposed online in good-faith by parents and guardians in so called "sharenting" practices. Beyond risks due to negative psychological repercussions in ignoring children's desire to having (or not) an online identity, there are concerns regarding the potential for grooming and child abuse, and the potential for identity crimes (such as identity fraud and identity theft), especially keeping in mind that today's children, in a few years, will be those employing digital identities in many aspects of their lives, and will need a clean and curated digital identity to be fully part of many aspects of our society.

The proposed project combines traditional and innovative cross-disciplinary approaches to further this emerging line of inquiry. The project does so by offering a better understanding of sharenting practices, their motivations, and the risks associated with them. It provides a better understanding of the existing technical and regulatory loopholes and gaps enabling potentially harmful sharenting practices. It also develops a better understanding of the perception of the problem by parents and guardians (our "target population"). The project can therefore enable better targeted awareness-raising activities; an improvement of the tools we currently have to study, prevent and mitigate the negative impacts of sharenting practices.

The result of this research will be of significant importance for social media users (and specifically for those in our target population) by raising awareness and promoting sustained behavioural change to minimise cyber risks. The results will also be of relevance for the work of law enforcement in better addressing crimes potentially facilitated by certain sharenting practices such as grooming and identity crimes.

More in general, the proposed approach will improve our understanding of criminogenic opportunities available in social media, supporting new avenues of investigation. By integrating insights and expertise from criminology and computer sciences, the proposed project also has important implications for demonstrating interdisciplinary methodological developments and promoting best practice for ethical online research.

The research project is structured around seven cumulative work-packages to allow the research team to build a solid body of original data (currently not available to researchers) but also to promote engagement and effective communication with a non-academic audience (primarily, law enforcement, and parents and guardians). Throughout the project, we will be supported by our Project Partners (UK Safer Internet Centre; Kidscape; Arma dei Carabinieri); together with Dame Prof. Wendy Hall and other stakeholders, the Project Partners will be also part of our Advisory Board.