An NLP project that analyses twitter data for sentiment on different celebrities.
create an api with flask holds a lightweight pretrained nlp sentiment model api samples tweets about a figure, returns average sentiment rating, most positive and most negative tweets
resources: sentiment analysis tutorial: https://realpython.com/python-nltk-sentiment-analysis/#getting-started-with-nltk https://huggingface.co/blog/sentiment-analysis-python#2-how-to-use-pre-trained-sentiment-analysis-models-with-python data science project structure: https://towardsdatascience.com/how-to-structure-a-data-science-project-for-readability-and-transparency-360c6716800 flask api tut: https://www.imaginarycloud.com/blog/flask-python/
nlp -celbrities stored in a databse -twitter data involving their name (or a predetermined list of related phrases/names) will be scraped and analyzed for sentiment -deployed in an api or something -maybe involve recent articles written on them
web app -you can search celebrity names -have picture of person -say if they are cancelled -give a percentage or metric of positive vs negative tweets -show example tweets -suggest related celebrities