How can natural language processing (NLP) be used to analyze public sentiment on social media about animal rights?
Context and Relevance:
Analyzing public sentiment on social media using Natural Language Processing (NLP) can offer valuable insights into public attitudes and opinions about animal rights. This six-month student project aims to explore how NLP techniques can be applied to social media data to understand sentiment trends and patterns. By developing NLP models to categorize and interpret posts, this research could provide actionable insights for animal rights advocacy and campaign strategies.
Potential Research Approach:
NLP Model Development: Develop and train NLP models to analyze social media posts related to animal rights, focusing on sentiment analysis and topic categorization.
Data Collection: Collect a representative sample of social media posts from various platforms to ensure a comprehensive analysis of public sentiment.
Trend Analysis: Identify and analyze trends and patterns in public sentiment over time, including the impact of specific events or campaigns on public opinion.
Additional Questions:
What are the most common themes and sentiments expressed in social media discussions about animal rights?
How do sentiment trends correlate with major animal rights events or advocacy campaigns?
What are the limitations of NLP in accurately capturing and interpreting nuanced public opinions on social media?