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This project aims to harness the power of social media data to explore sentiment analysis, comparing various natural language processing (NLP) techniques and machine learning embeddings to assess their ability to detect sentiment in free-form text.
The project seeks to understand how different methodologies can be effectively utilized to interpret the underlying sentiments expressed in social media content, with a focus on interpreting context and the detection of nuanced expressions such as sarcasm. You will get exposed to working with APIs, data processing, storage, and querying along with information display and visualization. Students will create a repository that will contain well-documented code, a README detailing the project's purpose, how to set up and run the code, and examples of the analysis performed. The project aims to provide a practical example of sentiment analysis from start to finish, including the challenges faced and how they were addressed. This project represents the tasks you do working as a software engineer in a data-driven field.
Get to know the Project Leader and other students, ask questions about the project requirements, prepare your workspace.
Explore the basics of sentiment analysis using Python in Jupyter Notebooks, and complete a guided example to understand vector space models.
Utilize public APIs to collect social media data, and learn to parse this data into structured formats using Python libraries like Pandas.
Identify your final project deliverables by selecting and scoping your research question, then outline your approach using a project management tool like GitHub Projects.
Begin your final project by setting up a GitHub repository, establishing a project structure, and starting data collection and analysis based on your scoped research question.
Continue developing your project, focusing on data analysis and interpretation using Python in Jupyter Notebooks, and collaborate with the Project Leader for feedback and guidance.
Finalize your project by incorporating feedback from the Project Leader, polishing your code, and completing your documentation and README in GitHub.
Polish your project deliverables and present them to the Project Leader and other students in the final group session.
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My name is Sam Richards, and I'm a Software Engineer at AdeptID, an API-first startup in Boston that works on matching and skill-based hiring AI in the HR tech space. I grew up on the south coast of England, where I studied Physics, Computer Science, and Math for A levels (the final 2 years of high school).
From a young age, I was fascinated by technology, especially the satisfaction that came from fixing things. This early interest evolved into a passion for computer science, as I discovered the joy in unraveling complex problems and finding elegant solutions.