Using TwitterAPI and tweepy, extract tweets for sentiment analysis. "How do pepople feel about traveling during COVID19?" Tweets were extracted on July 2020. Analyse current customers' trend of 3 different locations (Melbourne, Berlin and New York). sentiment_analysis demonstrates in more details.
- Data extraction
- Exploring and cleaning data
- Feature engneering
- Building models
- Analysing sentiment
The study of tourist behaviour is crucial for travel industory after COVID19. I believe that forcasting customer trend and demand will have a great advantage for a business in tourism.
- data Folder containing data files
- image Images used for sentiment_analysis
- models Models saved for pickle
- utils Utils folder
- data_cleaning_utils.py for cleaning tweets data, used in data_cleaning.py
- data_extraction_utils.py for extracting tweets, used in api_data_retrieval.py
- sentiment_analysis Analysing sentiments and model outcome by using graphs and images
- api_data_retrieval.py Extract tweets (No location specify, it is for training datasets)
- data_cleaning.py Cleaning train dataset using utils
- feature_engneering.py Feature engneering: creating TF-IDF and normalized numeric variables