8 Best Human Behaviour Datasets for Machine Learning

Human behaviour describes how people behave and interact.

It is based on and affected by a number of elements, including genetic makeup, culture, personal values and attitudes.

In this article, we will look at the 8 Best Human Behaviour Datasets for Machine Learning.

List of the Best Human Behaviour Datasets

1. - This dataset contains information on GDP, life expectancy, and literacy rates for various nations throughout the world. It also includes many economic and social variables.

   
   

2. - This dataset includes a wide range of demographic and economic data such as data on population, employment, income, poverty, housing, education, health, transportation, industry, public policy and consumer spending. It is a widely used dataset for research on demographics and economic trends in the United States.

   
   

3. - This dataset includes data on a variety of topics related to well-being and quality of life, including data on happiness, life satisfaction, and positive and negative emotions.

   
   

4. - This dataset includes data on attitudes and values in countries around the world, including data on political attitudes, social issues, and other topics.

   
   

5. - This dataset includes data on health-related behaviours in the United States, including data on diet, physical activity, and tobacco and alcohol use.

   
   

6. - This dataset includes data on the popularity of baby names in the United States over time, which could be used to study trends in naming conventions and preferences.

   
   

7. - This dataset includes data on consumer spending patterns in the United States, including data on what people buy and how much they spend.

   
   

8. - This dataset includes data on the health and nutrition of people in the United States, including data on diet, physical activity, and other health behaviors.

Common Use Cases for Human Behaviour Datasets

Economic and Social Development

- Common use cases of this dataset include:

• Study of Health: Researchers can use this dataset to examine life expectancy, infant mortality, and access to healthcare statistics for a number of different countries.

  
  

• Comparative Study of Countries: Using this dataset, researchers can examine how different nations have developed economically and socially and pinpoint what elements have contributed to certain of those developments and not others.

• Analysis of Gender Equality: Researchers can use this dataset to examine information on gender equality, including information on women's representation in politics, education, and the labor force.

  
  

• Environmental study: This dataset can be used by researchers to examine information on environmental sustainability, including information on renewable energy, carbon emissions, and resource management.

  
  

• Study of Income Inequality: This dataset can be used by researchers to examine income inequality and evaluate how income and wealth are distributed between and within nations.

  
  

• Study of Financial Inclusion: This dataset can be used by researchers to examine information on the availability of financial services, including information on the number of bank accounts and credit availability.

  
  

• Study of Infrastructure: Researchers can use this dataset to examine information on the development of infrastructure, including information on networks for transportation, communication, and access to energy.

  
  

• Analysis of GDP: This dataset can be used by researchers to examine historical economic growth rates and analyze statistics on the gross domestic product (GDP) for different countries.

  
  

• Analysis of Poverty: Using this information, researchers can examine global trends in poverty as well as its rates and causes.

  
  

• Analysis of Education: Researchers can use this dataset to examine the relationship between education and economic development by looking at literacy rates and educational statistics for different countries.

Demographics and Economic Trends

- Common use cases of this dataset include:

• Geographic Analysis: Researchers can examine patterns and trends in various US regions by using this dataset to analyze data at the state, county, and local levels.

  
  

• Data on employment by industry and profession can be analyzed by researchers using this dataset, which contains data on industry.

  
  

• Analysis of public policy: Researchers can use this dataset to examine information on issues related to public policy, such as welfare, disability, and veteran status.

  
  

• Business and Marketing Analysis: This dataset can be used by researchers, marketers, and businesses to evaluate data on consumer spending, demographics, and market trends to find new customers, target markets, and sales opportunities.

  
  

• Demographic Analysis: Researchers can use this dataset to examine US population statistics like size, age, race, and ethnicity.

  
  

• Economic Analysis: This dataset can be used by researchers to examine economic information, such as information on employment, income, and poverty.

  
  

• Researchers can use this dataset to study information on housing, including information on housing units, occupancy rates, and housing expenses.

  
  

• Analysis of Education Data: Researchers can use this dataset to study education-related data, such as enrollment and educational attainment statistics.

  
  

• Data on health, such as information on access to healthcare and health insurance coverage, can be analyzed by researchers using this dataset.

  
  

• Researchers can use this dataset to evaluate data on transportation, including information on the method of transportation used to commute to work and the amount of time spent doing so.

Well-being and Quality of Life

- Common use cases of this dataset include:

• Comparative Study of Countries: Researchers can use this dataset to compare well-being and quality of life across different countries and identify factors that contribute to well-being.

  
  

• Study of cultural and societal factors: Researchers can use this dataset to study data on cultural and societal factors that may contribute to well-being and compare them with other countries.

• Study of Economic Factors: Researchers can use this dataset to study data on economic factors and how they relate to well-being, such as data on income, job security, and poverty.

  
  

• Study of Political Factors: Researchers can use this dataset to study data on political factors and how they relate to well-being, such as data on political freedom, corruption, and government effectiveness.

  
  

• Study of Subjective Well-being: Researchers can use this dataset to study data on subjective well-being, which is a measure of how people evaluate their lives and happiness.

  
  

• Analysis of Life Evaluation: Researchers can use this dataset to analyze data on how people evaluate their lives and how it varies by country and demographic.

  
  

• Study of Mental Health: Researchers can use this dataset to study data on mental health, depression and well-being, and compare the data with other countries.

  
  

• Study of Social Support: Researchers can use this dataset to study data on social support and compare the data with other countries.

  
  

• Analysis of Happiness: Researchers can use this dataset to analyze data on happiness and life satisfaction in different countries and study the factors that contribute to well-being.

  
  

• Study of Positive and Negative Emotions: Researchers can use this dataset to study positive and negative emotions such as stress, worry, enjoyment, and happiness in different countries.

Attitudes and Values

- Common use cases of this dataset include:

• Study of Political Attitudes: Researchers can use this dataset to examine how people in various nations feel about politics, political leaders, and political systems.

  
  

• Study of Social Issues: Researchers can use this dataset to examine how people in various nations feel about social issues like immigration, LGBT rights, and gender equality.

  
  

• Study of Religious Attitudes: Researchers can use this dataset to examine how people in various nations feel about religion and their religious views.

  
  

• Study of Economic Attitudes: Researchers can use this dataset to examine how people in various nations feel about economic topics including income inequality, employment opportunity, and international commerce.

  
  

• Study of Attitudes Toward China: Using this information, researchers can examine how people in other nations feel about China, including their opinions on its politics, economy, and culture.

  
  

• Study of Attitudes toward Climate Change: Researchers can use this dataset to examine how individuals in various nations feel about environmental issues and climate change.

  
  

• Study of Attitudes toward Globalization: Using this information, researchers can examine how people in various nations feel about globalization, including their opinions on its political, cultural, and economic ramifications.

  
  

• Study of International Relations: This dataset can be used by researchers to research how people feel about international relations, including how they feel about other nations, foreign aid, and international organizations.

  
  

• Study of Attitudes Toward the US: Using this dataset, researchers can examine how individuals around the world feel about the United States, including their opinions on its politics, culture, and foreign policy.

  
  

• Study of Attitudes Toward the European Union: Using this dataset, researchers can examine how individuals in various nations feel about the EU, including their opinions on its institutions, policies, and collaboration.

Health-Related Behaviours

- Common use cases of this dataset include:

• Analysis of Health Behaviours: Researchers can use this dataset to analyze information on health behaviours, including information on measures that promote preventative health, such as immunization, cancer screening and seatbelt use.

  
  

• Investigate of Mental Health: This dataset can be used by researchers to study information on mental health, including information on depression and suicide.

  
  

• Researchers and public health officials can use this dataset to track changes in risk behaviours and health outcomes, as well as to pinpoint the people most at risk for particular diseases or habits.

  
  

• Study of Health Outcomes: Using this dataset, researchers can examine data on health outcomes, such as statistics on morbidity and mortality rates, and contrast them with data at the federal, state and local levels.

  
  

• By comparing the data before and after the program's implementation, researchers can utilize this dataset to assess the efficacy of health promotion and disease prevention initiatives.

  
  

• Health Policy Analysis: By giving information on the prevalence of health behaviours and outcomes and identifying populations that require interventions most, researchers can utilize this dataset to inform public health policies and initiatives.

  
  

• Study of Risk Factors: This dataset can be used by researchers to study factors that increase the risk of developing chronic diseases, such as information on nutrition, exercise, and cigarette and alcohol use.

  
  

• Research on Health Disparities: This dataset can be used by researchers to investigate information on health disparities, such as information on health habits and outcomes among various population groups.

  
  

• Data on self-reported health status, such as information on chronic illnesses and disability, can be analyzed using this dataset by researchers.

  
  

• Study of Health Care Access: This dataset can be used by researchers to research information on health care access, including information on health insurance coverage and the usage of medical services.

- Common use cases of this dataset include:

• Data on environmental exposures, such as information on lead levels, pesticide use, and other harmful chemicals, can be studied using this dataset, according to researchers.

  
  

• Research on Health Disparities: This dataset can be used by researchers to investigate information on health disparities, such as information on health habits and outcomes among various population groups.

  
  

• Data on self-reported health status, such as information on chronic illnesses and disability, can be analyzed using this dataset by researchers.

  
  

• Examine of Health Care Access: Researchers can use this dataset to study information on health care access, including information on health insurance use and service utilization.

  
  

• Study of Physical Activity: This dataset can be used by researchers to research information on levels of physical activity and associated health outcomes.

  
  

• In order to identify populations most at risk for particular health disorders or habits, researchers and public health officials can use this information to track trends in health behaviours and health outcomes.

  
  

• By comparing the data before and after the program's implementation, researchers can utilize this dataset to assess the efficacy of health promotion and disease preventive initiatives.

  
  

• Data on dietary consumption, nutrient levels, and body measurements are just a few examples of the nutritional status information that researchers can analyze using this dataset.

  
  

• Study of Chronic Disease: Researchers can use this dataset to research information on chronic illnesses like diabetes, cancer and cardiovascular disease.

  
  

• Health Policy Analysis: By giving information on the prevalence of health behaviours and outcomes and identifying populations that require interventions most, researchers can utilize this dataset to inform public health policies and initiatives.

Consumer Trends

- Common use cases of this dataset include:

• Data on consumer credit, including information on credit card usage, outstanding debt, and delinquency rates, can be studied using this dataset.

  
  

• Study of Consumer Savings: This dataset can be used by researchers to research information on consumer savings, including information on retirement planning, investment preferences and savings rates.

  
  

• Data on the purchase and ownership of vehicles, appliances, and other durable items are just a few examples of consumer durable products that researchers might analyze using this dataset.

  
  

• Data on consumer services, such as information on spending on healthcare, education, and other services, can be studied using this dataset.

  
  

• Examine of Consumer Spending: This dataset can be used by researchers to study information on consumer spending, including information on what consumers buy, how much they spend and how their spending habits vary over time.

  
  

• Investigate of Income: This dataset can be used by researchers to study information on income, including information on sources of income, income levels and income distribution.

  
  

• Study of Consumer Behaviour: This dataset can be used by researchers to research information on consumer behaviour, such as information on consumer attitudes, preferences and decision-making processes.

  
  

• Data on consumer demographics, including information on age, race, gender, and education level, can be studied using this dataset by researchers.

  
  

• Data on consumer pricing, including information on inflation and the cost of products and services, can be analyzed using this dataset by researchers.

  
  

• Data on consumer spending and income throughout economic expansions and recessions, as well as other data on economic trends, can be studied using this dataset by researchers.

Naming Conventions and Preferences

- Common use cases of this dataset include:

• Analysis of Name Trends: This dataset can be used by researchers to examine information on name trends, including information on the development of new names, the waning popularity of existing names and the impact of popular culture on naming preferences.

  
  

• Examine of Regional Differences: This dataset can be used by researchers to study information on regional differences, such as information on variances in state and regional naming practices.

  
  

• Explore of Naming Patterns: This dataset can be used by researchers to study naming patterns, including naming patterns within families and the impact of a person's ancestry on naming decisions.

  
  

• Research of Naming Traditions: Researchers can use this dataset to study information on naming customs, including information on how religion, culture and ethnicity affect naming decisions.

  
  

• Investigate of Naming Decisions: Researchers can use this dataset to study information on naming choices, including information on the time and effort parents put into naming their children and the naming standards.

  
  

• Study of Naming Trends over Time: Researchers can use this dataset to examine data on naming trends over time, including information on how naming preferences have changed over time and how certain names have grown or declined in popularity.

  
  

• Study of Naming Conventions: Researchers can use this dataset to study data on naming conventions, such as data on the influence of cultural, social, and historical factors on naming choices.

  
  

• Study of Gender and Ethnicity: Researchers can use this dataset to study data on gender and ethnicity, such as data on differences in naming choices between boys and girls and among different ethnic groups.

  
  

• Study of Social and Economic Factors: Researchers can use this dataset to study data on social and economic factors, such as data on the influence of social class, education and occupation on naming choices.

  
  

• Study of Popular Baby Names: Researchers can use this dataset to study data on the popularity of baby names, such as data on the most common names and name trends over time.

Final Thoughts on These Human Behaviour Datasets

Researchers, policymakers, and businesses can all benefit from studying behaviour since it can help them better understand how people behave and how that affects the economy, health and other facets of society.

These datasets are also available for anyone to download and use freely.

More Dataset Listicles:

1. Power Bi Datasets
2. Time Series Datasets
3. Geospatial Datasets