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title: Project Ideas

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# **Project Ideas for Comparative Politics**

## 1. Frugal Life, Frugal Politics: Political Economy Origins of Political Views

### Research Question
Why do some individuals strongly support minimal government and fiscal responsibility? What are the underlying factors that shape these political views, and how do lifestyle, religion, and historical political economy contribute to these ideologies?

### Data and Methods

**1. Frugal Consumption and Lifestyle**

**Hypothesis:** People who lead frugal lifestyles (e.g., minimal spending, budgeting) are more likely to support minimal government intervention and fiscal conservatism.

**Data:** Surveys on consumption habits, spending patterns, and political views, as well as demographic data (e.g., income, education level).

**Methods:** Regression analysis to explore correlations between frugal consumption habits and political preferences for limited government.
Machine learning models to predict fiscal conservatism based on lifestyle choices (e.g., saving vs. spending habits).

**2. Religious Components**

**Hypothesis:** Certain religions that advocate for a simple, frugal lifestyle (e.g., Protestantism) may shape political views that favor minimal government and fiscal responsibility.

**Data:** Religious affiliation data, surveys on lifestyle, and political views, combined with historical records of religious teachings on frugality.

**Methods:** Comparative analysis to identify how religious groups with frugal teachings differ in their political preferences from other groups. Causal inference to assess how religious adherence to frugal principles influences support for minimal government.

**3. Historical Political Economy Reasons**

**Hypothesis:** Historical events such as famines, migration, and economic hardship have instilled a culture of frugality, influencing modern political views on government spending and intervention.

**Data:** Historical records of famines, migration patterns, and economic crises, combined with current political views in regions affected by these events.

**Methods:** Historical analysis to track how events like economic crises or migration shaped the political ideologies of affected populations.Econometric models to explore the long-term impact of historical frugality on modern political economy views.

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## 2. The Artistic Expressions of Political Sentiments

### Research Question
Does art influence political sentiments, or do political sentiments shape artistic expressions first?

### Data and Methods

#### 2a. Art and Conflict Prediction

**Data:** Database of artworks from museums and galleries, including metadata on colors, themes, and periods.

**Methods:** Machine learning techniques (e.g., convolutional neural networks) to analyze visual elements in art and predict conflict scenarios based on the presence of certain features (e.g., black for war, white for peace).

#### 2b. Nationalism in Art

**Data:** Digital databases of artworks from regions with nationalist movements, such as Spain, Catalonia, the Basque Country, Kosovo, and other areas with significant political and cultural tensions.

**Methods:** Computer vision algorithms to detect nationalist symbols or colors in visual art. This analysis would identify patterns in the use of specific colors, symbols, or themes that subtly convey political messages in art from regions experiencing nationalist movements. Case studies could include the use of nationalist imagery in Catalonia, the Basque Country, or Kosovo.

#### 2c. Replicate Peng Peng’s Findings with Art Data

**Data:** Scrap poems and other artistic expressions from literary databases or national archives.

**Methods:** Natural language processing (NLP) to detect nationalist themes in poems and artistic texts, using keyword analysis (e.g., "Zhungguo" in Chinese) to identify patterns of nationalism across regions.

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## 3. Hear Me Out: Music and Political Outcomes

### **Research Question**
Can musical preferences, such as genre, tempo, and rhythm, be used to predict political behavior or affiliations? How do regional patterns in music consumption correlate with electoral outcomes, and what do these patterns reveal about the cultural-political landscape?

#### **3a. Musical Characteristics and Political Sentiments**
   - **Data**: Music charts data, including tempo, rhythm, and genre information. Data from streaming platforms (e.g., Spotify, Apple Music) or public music charts.
   - **Methods**: Use machine learning techniques (e.g., clustering, classification algorithms) to analyze the correlation between musical characteristics (e.g., tempo, rhythm) and political sentiments. Investigate whether certain music trends align with political movements, similar to the art analysis in Proposal 2.

#### **3b. Predicting Political Preferences Based on Music**
   - **Data**: Streaming data or music preference data from specific regions (e.g., counties), along with political voting outcomes from elections (e.g., Democrat vs. Republican votes in U.S. counties).
   - **Methods**: 
     - **Machine learning**: Train a classification model (e.g., logistic regression, random forests) using music preference data to predict the political color of a region. For example, you could use data from St. Louis County on music listening habits and voting records, then test the model on other regions to see if it correctly predicts political party preferences.
     - **Analysis**: Explore whether patterns in music preferences (e.g., genre, lyrics, tempo) can serve as predictors for political leanings at a county level.

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## 4. The Politics of Fans: How Sports Shape Nationalism, Policy, and Identity

### Research Question

How do the performances of sports teams, both national and local, influence political outcomes such as nationalism, policy changes, political pride, and public attitudes toward ethnic groups?

### Data and Methods
**1. National Team Success and Political Outcomes**

**Description:** Examines how the success of national teams, particularly in football, affects nationalism, election outcomes, and public opinion on policy changes, with special attention to fan reactions.

**Data:** National team performance data (e.g., match results, tournament outcomes) and political metrics (e.g., election results, surveys on patriotism and anti-immigration sentiment).

**Methods:**
Regression analysis to explore the relationship between team success and shifts in political opinions.
Machine learning to predict changes in political sentiments (e.g., nationalism) based on fan engagement with national team success.

**2. Sports and Nationalism in Conflict Periods**

**Description:** Investigates whether strong national team performances during politically tense times correlate with increased nationalism and support for war, focusing on how fans contribute to the nationalistic fervor.

**Data:** Historical football team performance data and public records on war support, e.g. WWII (?).

**Methods:** Causal inference techiniques Difference-in-Differences (DiD?) to analyze whether sports success led to increased nationalist attitudes and war support among fan bases.

**3. Local Sports Teams and Political Pride**

**Description:** Explores how the success of local sports teams across various sports affects political pride and support for incumbents, particularly in close elections, highlighting the influence of local fan bases and their mood swings.

**Data:** Local team performance data (e.g., game results, attendance) and political data (e.g., incumbent re-election results).

**Methods:** Geospatial analysis to determine whether regions with higher fan engagement show greater political pride and support for incumbents.

**4. Star Athletes and Ethnic Sentiments**

**Description:** Analyzes whether the ethnicity of star players affects public attitudes toward immigrants and ethnic groups, focusing on how fans react to ethnically diverse athletes.

**Data:** Social media sentiment analysis and/or surveys on ethnic or immigrant groups, combined with data on the ethnic backgrounds of star players.

**Methods:** Sentiment analysis using NLP to track how fan reactions to star athletes of different ethnicities influence public attitudes.

## 5. Happy Lungs, Happy Citizens: Exploring the Impact of Air Quality on Political Attitudes

### **Research Question**
To what extent does air quality impact political attitudes, and how do these effects vary across regions or demographic groups?

### **Data and Methods**

#### **Version 1: Public Opinion Surveys**
   - **Data**: 
     - **Pollution levels**: Satellite imagery (NASA) and monitoring stations (AQICN).
     - **Surveys**: World Values Survey, Gallup, national opinion surveys.
   - **Methods**: Analyze correlations between air quality and political attitudes. Predict political sentiment using ML models.
   - **Causal inference**: Difference-in-Differences and/or synthetic control methods.

#### **Version 2: Social Media Platforms**
   - **Data**: 
     - **Pollution levels**: Same as Version 1.
     - **Social media**: Web scraping from platforms like Twitter, Reddit.
   - **Methods**: Web scraping, NLP.

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