Computational Social Science Capstone Project

University of California, Davis via Coursera

Go to Course: https://www.coursera.org/learn/css-capstone

Introduction

### Course Review: Computational Social Science Capstone Project on Coursera The **Computational Social Science Capstone Project** is the crowning achievement of a comprehensive specialization that immerses learners in the intersection of social science and computational analysis. This course not only consolidates the vast array of skills acquired throughout the previous modules but also provides an engaging and hands-on experience to synthesize knowledge into practical outputs. Here's a detailed review of the course structure, milestones, and personal recommendations for those considering enrolling. #### Overview Upon enrolling in this capstone project, students are celebrated for reaching an educational milestone that equips them with the capability to undertake complex tasks within the realm of computational social science. The course intricately guides learners through a structured workflow, enabling them to scrape, analyze, and visualize data from social media platforms—specifically YouTube—while utilizing state-of-the-art analytical tools and techniques. #### Syllabus Breakdown The capstone project is designed around four pivotal milestones, each building on analytical and technical proficiencies in a meaningful way: 1. **Getting Started and Milestone 1**: - Here, learners embark on a web scraping exercise where they collect data from two designated YouTube channels. Unlike previous assignments where students scraped featured videos, this task focuses on retrieving data through search results involving their names and the channels. It’s a clever twist that encourages personal engagement and reflection on the data collected. 2. **Milestone 2: Social Network Analysis (SNA)**: - In the second milestone, students delve into social network analysis using Gephi, a powerful tool for visualizing social data. Learners analyze relationships and interactions within the data collected, facilitating a deeper understanding of social dynamics. This is an exciting opportunity to see how connections play out in real-time, providing valuable insights into information spread and community interactions. 3. **Milestone 3: Natural Language Processing (NLP)**: - Building on the previous analyses, learners select two key videos to perform sentiment analysis on their comment sections. Utilizing IBM Watson's NLP capabilities, students explore emotions and sentiments, a critical skill in understanding public perceptions and narratives. This milestone truly emphasizes the relevance of computational methods in gauging public opinion. 4. **Milestone 4: Agent-Based Computer Simulations**: - Students conclude the project by applying all their previous findings to create agent-based simulations. This innovative approach allows learners to model the diffusion of ideas within a constructed artificial society. Participants develop a bottom-up understanding of social phenomena, bridging theory with practical implementation through technological tools. #### Recommendations The **Computational Social Science Capstone Project** is highly recommended for individuals who: - Have a foundational knowledge of computational methods in social science. - Seek to gain practical experience with real-world data from social media platforms. - Are curious about the implications of data analysis and visualization in understanding societal trends. - Want to enhance their skills in scraping data, performing social network analysis, sentiment analysis, and simulating social processes. Given the course's comprehensive structure and practical applications, it caters not only to students in social science disciplines but also to professionals eager to leverage computational tools to analyze social phenomena. Moreover, the program’s emphasis on hands-on projects results in an enriching learning experience that provides tangible skills applicable in various fields, including marketing, social research, and data journalism. ### Conclusion In summary, the **Computational Social Science Capstone Project** on Coursera offers a rigorous and enriching experience, guiding learners through the full cycle of computational social science workflows. As you culminate your studies, you will not only depart with knowledge but also with practical skills that are immensely valuable in today’s data-driven society. If you're ready to transform your theoretical understanding into impactful real-world applications, this capstone project is a fantastic opportunity to do just that.

Syllabus

Getting Started and Milestone 1

For this milestone, you will again web scrape videos from two YouTube channels. You will be assigned two channels to scrape. In contrast to the previous version of this exercise, you will NOT scrape the featured videos of the specified news channel, but the search results of the name of the news channel in combination with your name.

Milestone 2: Social Network Analysis

In this milestone, you will analyze a social network with help of the software Gephi.

Milestone 3: Natural Language Processing

In this milestone of our Integrative Lab, you will select two of the key videos identified with help of our SNA, and analyze the sentiment and emotions contained in the comment sections of the videos. We use NLP from IBM Watson for this.

Milestone 4: Agent-Based Computer Simulations

In this milestone, you will take all the data you created in the previous milestones and use a two-step flow model and discover how ideas can diffuse into society. Through this exercise you will grow your own artificial society from the bottom-up.