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Semantic Analysis of a Social Media
Sam Richards
Sam Richards
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Semantic Analysis of a Social Media

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.

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Tuesdays
 at
11:00
A.M.
 ET /
8:00
A.M.
PT
8 weeks, 2-3 hours per week
Intermediate
No experience required
No experience required
Some experience required
Degree and experience required

Description

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.

Session timeline

  • Applications open
    March 11, 2024
  • Application deadline
    April 7, 2024
  • Project start date
    Week of July 8, 2024
    Week of
    April 22, 2024
  • Project end date
    Week of

What you will learn

  • Use pandas to import data from formats like CSV, JSON, or SQL into DataFrames for analysis. Explore datasets with .head(), .describe(), and cleaning functions to prepare the data.
  • Apply NLP libraries (e.g., NLTK, spaCy) to generate word embeddings, turning text into numerical vectors for machine learning tasks like sentiment analysis and text classification.
  • Use cosine similarity to perform searches based on vector similarity, identifying texts most semantically similar to a query, useful for document retrieval and recommendation systems.
Build Projects are 8-week experiences that operate on a rolling basis. Selected participants engage in weekly live workshops with a Build Fellow and 2-15 other students.

Project workshops

1
Project Introduction & Setup
2
Sentiment Analysis Fundamentals
3
API Data Collection
4
Project Scoping Workshop
5
Project Kickoff & Planning
6
In-depth Project Work
7
Project Review & Feedback
8
Final Presentations & Review

Prerequisites

  • Knowledge of APIs and data collection tools
  • Familiarity with Python and Jupyter Notebooks
  • Skills in documentation and code repository management (git)

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About the expert
Sam Richards
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Sam
's Linkedin

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.

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