Dataset: 

The dataset we used for this project is instrumental in analyzing social media advertising, focusing on gender bias and racial representation. It contains detailed information on marketing campaigns, including attributes like Campaign ID, target audience, campaign goal, channel used, location, language, customer segment, company, gender, and race. By examining how brands and companies utilize platforms like Instagram, Facebook, and Twitter, this dataset allows us to uncover patterns of bias and representation. Due to data limitations, we were only able to extract out two races which are White and Hispanic.

Link to dataset:https://docs.google.com/spreadsheets/d/1ccVwWEJgTxkcDeY_8rc9rOuOwKCxIG_RuXEgJPpkGx8/edit?usp=sharing

Link to codes: https://drive.google.com/file/d/1sG60ptwaAdBd0ovWNxR_vUubMdZdlvX4/view?usp=drive_link

Importance of Gender data 

Gender data helps us understand how different genders are portrayed in social media advertisements, crucial for identifying potential biases and stereotypes. By examining gender distribution, we can see which gender is being targeted more by specific brands and platforms, helping to understand marketing strategies. Gender data is also essential for assessing how inclusive advertisements are, particularly regarding non-binary representations.

A strength of using gender data is that it provides a clear picture of gender dynamics in advertising, highlighting disparities and informing efforts to promote gender equality. However, a potential weakness is that it may overlook intersectionality, such as how gender representation intersects with race, age, and other factors.

Importance of Race data

Race data allows us to evaluate the diversity in advertisements and identify which races are underrepresented or overrepresented. It helps in pinpointing racial biases in targeting strategies, which can perpetuate stereotypes and inequality. Ensuring that marketing strategies are inclusive and reflective of a diverse consumer base is another critical aspect of race data.

One strength of using race data is its role in highlighting racial disparities and biases in advertisements, supporting calls for more inclusive marketing practices. However, it might not capture the full spectrum of racial identities and the nuances within racial groups.

Importance of Social Platform data

Social platform data provides insights into the unique user demographics and engagement patterns of different social media platforms. It reveals how advertisements are distributed across platforms, indicating platform-specific strategies and biases. This data is also essential for correlating gender and race data with specific platforms, showing how these factors interact with platform characteristics.

The strength of social platform data lies in its ability to provide a comprehensive view of how different platforms contribute to the overall landscape of social media advertising. However, platform-specific data might not be representative of broader trends and can be influenced by platform algorithms.

Analysis of Map data

The map illustrates the "Delivery Degree" across different cities in the United States. The delivery degree is represented by varying circle sizes and colors, indicating the intensity or volume of ad delivery in each city. For example, New York has a high delivery degree, indicated by a large, dark purple circle, while Los Angeles has a significant delivery degree represented by a large yellow circle. Houston, Miami, and Phoenix show moderate delivery degrees with medium-sized circles in different colors.

This geographic data is important for understanding regional targeting strategies. It provides insights into the geographic distribution of advertisements, highlighting cities with high ad delivery intensity. This helps us understand how social media platforms target users based on their geographic location and whether certain demographics are targeted more in specific locations. A potential weakness of this data is that it lacks detailed demographic information, making it challenging to directly correlate delivery degrees with specific gender or race distributions. Additional data layers showing demographic breakdowns within these cities would enhance the analysis.

Integration of All data type

By integrating gender, race, and social platform data with geographic data, our project aims to uncover patterns and biases in social media advertising. Each data type provides valuable insights into different aspects of advertising practices, helping to identify areas for improvement and fostering more equitable representation. The map adds a geographic dimension to our analysis, revealing how ad delivery varies across different regions. This comprehensive approach promotes inclusivity in social media advertising, ultimately contributing to a better understanding of how digital advertising impacts societal norms and consumer behavior.