About

     Lets Meet Our People!!

Our project was made possible thanks to the collaborative efforts of the following individuals.

Team Members

Selena Shen

• • Bio: Hi, this is Selena and I am a rising Senior studying in Chemical Engineering with a minor in Data Science at Cal. I enjoy working with data and science, and I love seeing their connections with the real world. With a mindset focused on applying scientific principles to solve practical real problems, I developed the habit of looking and thinking. Besides that, on my free time, I like to spend my time on hiking, skateboarding and play with my two little cats><

  • Responsibilities: Storyboard, Narrative, Data Critique, About Page, Bibliography

Miranda Zhu

• • Bio: Hi! I'm Miranda Zhu, a rising junior majoring in Data Science and Statistics. I love using my programming skills like Python and Java to tackle real-world problems through data analysis. I also have a strong interest in humanities, especially philosophy and history, which is why I'm drawn to the field of data humanities—it beautifully combines my two favorite areas. Moreover, I also enjoy working on various side projects that allow me to explore my interests further. In my free time, I love dancing and singing, which help me express my creativity and provide me an opportunity to meet more people:)

  • Responsibilities: Website build up, Bibliography

Han Yang

• • Bio: Hi, my name is Han Yang. I am a rising junior majoring in Data Science. I have a passion for technology and innovation. Thus, I had my internship at Intel last summer and enjoyed utilizing technology to improve our lives. I have many hobbies, such as soccer, table tennis, and so on. Besides, I like writing poems, and I had my own poetry published when I was in high school.

  • Responsibilities: Visualization, Data Critique, Bibliography

Siqi Tan

• • Bio: Hi, My name is Siqi Tan, and I am a senior at UC Berkeley, majoring in Economics and Data Science. I chose these two fields because they are closely related and complement each other perfectly. When addressing economic problems, I frequently utilize data science skills to find solutions and it always works! I truly enjoy working on projects, as they provide abundant learning opportunities and allow me to learn deeper through continuous research.

  • Responsibilities: Website build up, Bibliography

Huiming Jiang

• • Bio: Hi, My name is Huiming Jiang, I am a rising senior majoring in Data Science UC Berkeley. I have strong skills in Java and Python through my coursework and personal projects. Other than that, what drives me is analyzing data to drive meaningful insights and optimizing algorithms for efficiency. I chose this major because of an interest in how data can be used to solve real-world problems. I enjoy working on personal projects and applying data science techniques to a practical problem. The opportunities ahead excite me, and I am looking forward to learning and collaborating with peers. 

  • Responsibilities: Narrative, Data Critique, Bibliography

Wenyu Duan:

• • Bio: Hi, My name is Wenyu Duan, and I am a third-year student majoring in Data Science. I played a leading role in our group project regarding generating visualizations and data analysis about how different age groups interact with posts from luxury brands on Instagram. I collected and processed large datasets to make sure that it was accurate and had relevance to the objectives of the project. I worked out detailed visual displays concerning available data, pie charts, and bar charts and managed to bring out patterns of interaction across demographics. Furthermore, I contributed to the design of surveys and analyses, integrating quantitative and qualitative data that gave a comprehensive insight into consumer behavior. 

  • Responsibilities: Narrative, Data Critique, Bibliography

Yixiao Yang:

• • Bio: Hello, my name is Yixiao Yang, and I am entering my third year of university. My primary major is Environmental Economics and Policy, and I am considering adding a second major in Data Science. I find Data Science incredibly captivating; the process of visualizing data feels akin to creating art with numbers. My aspiration is to apply data science to environmental issues, contributing to real-world solutions for these pressing problems. In my leisure time, I enjoy dancing, listening to music, and playing badminton.

  • Responsibilities: Website build-up, Bibliography

Each member brought their unique skills and perspectives, making this comprehensive analysis of social media advertising possible. We extend our gratitude to all participants and supporters who contributed to this project.

Acknowledgments

We would like to extend our gratitude to our GSI Hannah Ellis for her support and guidance throughout this project. We also acknowledge the invaluable advice and guidance provided by Professor Scott Caddy, which greatly contributed to the successful completion of this work. Additionally, we appreciate the lectures and assistance from other GSIs, which have been instrumental in our learning process. We would also like to acknowledge the online resource Kaggle for providing the data used in this project.

Technical and Data Decisions

Throughout this project, we made several key technical and data-related decisions to ensure a rigorous and comprehensive analysis:

Topic Shift: Our project initially focused only on the data analysis of one particular brand type and one particular social media platform, which was not comprehensive and could not fully represent the whole community. We switched to a broader scope and included more social media platforms, gender bias, and racial representation to provide a deeper, more impactful analysis.

Data Cleaning: We thoroughly cleaned the data to remove duplicates, inconsistencies, and irrelevant entries and columns from the raw dataset.

Programming Languages: We primarily used Python for data analysis because of its robust libraries and strong community support. Python’s versatility and powerful data analysis libraries made it the preferred choice for our project.

Visualization: We used Matplotlib and Seaborn to create visualizations and present our findings. Initially, we considered using online visualizations and graphs, but we decided to create our own graphs to better suit our analysis. These tools helped us effectively communicate our results in a clear and visually appealing manner.

Assets

The main component of our project was the social media advertisement dataset obtained through Kaggle, an online dataset source website. The softwares we utilized throughout the project were Excel, Python, Google Sites. Academic articles and books on gender studies and critical race theory accessed through UCB Libraries. Online forums and communities for troubleshooting and expert advice on using data analysis tools.

Contact 

Selena Shen: selenashen@berkeley.edu

Miranda Zhu: mirandazhu@berkeley.edu

Han Yang: han.yang@berkeley.edu

Siqi Tan: siqitan347@berkeley.edu

Huiming Jiang: huiming1108@berkeley.edu

Wenyu Duan: xyt0831@berkeley.edu

Yixiao Yang: yixiao04@berkeley.edu