The Rise of Online Gambling: What Google Searches Reveal
Viz 1: The Rise of Online Sports Betting Revenue in the U.S.
For this project, I wanted to investigate whether periods of economic stress are associated with increases in gambling activity, measured in revenue. This project blends psychology and behavioral finance by asking whether gambling acts as a risk-seeking response to stress and whether algorithmic betting tools amplify that tendency. The purpose of this first visualization is to establish the context in which online sports betting has grown in recent years. The figure shows monthly U.S. online gambling revenue from 2021 through 2025, showing both short-term volatility and long-term growth. As shown in the graph, monthly revenue in 2022 generally ranges between around $0.25 and $0.75 billion, while by 2024 several months exceed $1.5 billion in revenue. Although month-to-month fluctuations are present, the overall upward trend is clear. This dramatic increase points to the growth of the sports gambling industry. This visualization provides the economic context needed for examining how public search behavior may relate to gambling activity in following visualizations.
Viz 2: Public Sentiment Through Google Search Behavior
In order to accurately capture public sentiment and psychological and economic feelings, I collected data from google trends. By collecting search interest data for terms such as unemployment, investment, side hustle, depression, and other indicators of financial or emotional stress, I can create a more measurable representation of the factors that shape gambling popularity in a given period. This second visualization builds on the national revenue trend shown in Viz 1 by incorporating this search interest data to provide insight into public sentiment over time. Google Trends data are used as a proxy for collective attention and concern, as Google is the most widely used search engine in the United States, processing billions of searches daily. As a result, search behavior can offer a useful view into how people respond emotionally and financially to broader social and economic changes.
The animated charts display monthly search interest for five selected keywords, each representing a different side of public sentiment: depression and substance abuse capture potential emotional distress and coping behaviors; investment and side hustle reflect financial planning and economic pressure; and parlay represents impulsive or risk-oriented gambling behavior. Search interest values are scaled from 0 to 100 within each keyword, allowing trends over time to be examined without implying absolute search volume comparisons across terms.
Viz 2 Animation
Viz 3: Economic Pressure & Risk-Taking Over Time
This third visualization narrows the focus from the broad patterns shown in the previous figures to how economically related search behavior evolves over time. Adding onto the trends introduced in Viz 2, this visualization displays the keywords associated with financial pressure, financial optimism, and risk-taking to provide insight into how economic concerns may align with gambling-related interest.
The figure displays Google search interest over time for three selected terms: side hustle, which reflects potential income pressure or financial strain; investment, which captures financial planning or optimism; and parlay, a betting term often associated with higher-risk gambling behavior. Search interest values are shown on a common scale from 0 to 100, allowing changes within each term to be compared over time without implying differences in absolute search volume across keywords. Periods where increased interest in income-related or financial planning searches coincide with spikes in parlay searches suggest a potential relationship between economic pressure and risk-taking behavior, motivating further state-level and quantitative analysis.
Viz 4: Emotional Stress, Coping, and Gambling Revenue
This visualization shifts the analysis from economic pressure to psychological distress and explores how search interest associated with emotional distress and destructive coping may relate to national gambling revenue levels over time.
The figure compares monthly gambling revenue with Google search interest for depression, representing emotional distress; substance abuse, reflecting potential coping behavior; and parlay, included as a benchmark for risk-oriented gambling interest. Each panel displays a smoothed trend line to summarize the overall association between search interest and revenue. The observed patterns suggest that periods of elevated emotional distress and coping-related search behavior may coincide with higher gambling revenue.
Viz 5: Seasonal Mental Health Patterns
This fifth visualization examines whether mental health related search behavior follows seasonal patterns, providing context for how emotional distress and coping behaviors may change throughout the year. The visualization shows that both depression-related and substance-abuse related searches tend to peak during the spring and fall months, with lower average interest during the summer. This pattern is consistent with prior research suggesting the seasonal influence on mental health. While winter is often associated with emotional distress, the data suggest that transitional seasons may be periods of vulnerability.
Viz 6: Behavioral Vulnerability Index (BVI) Across U.S. States
This sixth visualization brings in the Behavioral Vulnerability Index (BVI). Rather than focusing on individual search terms in isolation, the BVI uses emotional, financial, and behavioral stress to provide a cohesive state-level perspective.
The BVI was constructed using Google Trends search interest with higher values contributing positively to vulnerability. Search interest in investment, which reflects financial planning or optimism, is included as a mitigating factor and is weighted negatively in the index. All components are combined into a single score to capture relative vulnerability rather than absolute risk.
The choropleth map reveals the variation in behavioral vulnerability across states. States with higher scores have higher levels of distress-related, coping-related, and risk-oriented search behavior relative to optimism-related searches, while states with lower scores show the opposite pattern. Importantly, the BVI is a descriptive and exploratory index and shows regional patterns that may help contextualize differences in gambling participation and revenue observed in earlier visualizations.
Viz 7: Plotly
This seventh visualization uses an interactive Plotly scatterplot to further explore the seasonal relationship between emotional distress and gambling activity. This visualization compares average Google search interest for depression with average monthly gambling revenue. By doing this, this visualization allows patterns observed in previous figures to be shown from a different perspective.
The visualization suggests that seasons associated with higher depression-related search interest also tend to correspond with higher average gambling revenue. Additionally, it agrees with earlier findings on seasonal mental health variation and gambling trends, illustrating how emotional distress and economic behavior may align.
Viz 8: Shiny app 1
Shiny App 1: State Gambling & Search Behavior Explorer
The first shiny app allows users to explore how specific gambling-related search behaviors vary across states. The storyboard format lets users select individual keywords and see how their geographic distribution and economic relationships change. Users can choose from a set of search terms, the application then displays a ranked view of states with the highest search interest for the selected term, along with a scatterplot showing the relationship between that search interest and state-level gambling revenue. A narrative interpretation panel updates automatically to summarize key patterns observed in the data. By linking keyword-specific search behavior to economic outcomes at the state level, the application provides a flexible exploratory tool that highlights how emotional, financial, and impulsive tendencies may manifest differently across regions.
Live App Link:
https://katrinag.shinyapps.io/app1/
Viz 9: Shiny app 2
Shiny App 2: Economic & Search Trend Explorer
Live App Link:
https://katrinag.shinyapps.io/app2/
This tool allows users to select an individual U.S. state and view a consolidated profile of its gambling revenue metrics alongside associated search behavior patterns.
For each selected state, the application displays key economic indicators, such as gambling revenue, taxes, and total handle, alongside Google Trends search interest for keywords related to emotional distress, financial motivation, and risk-taking behavior. A generated summary combines these elements into a narrative description. This application lets users move beyond national averages and explore how behavioral and economic patterns differ across local contexts. By presen2ting economic and search-behavior indicators together in a single dashboard, the app highlights the diversity in gambling environments across states. The State Gambling Profile Explorer supports earlier visualizations by backing the idea that gambling behavior and associated stressors are not uniform across the United States.