GitHub - zarashabrina/Sentiment-analysis-using-Twitter-data: Sentiment analysis using Twitter data: A comparative application of lexicon and machine learning-based approach. Qi, Y., Shabrina, Z. Sentiment analysis using Twitter data: a comparative application of lexicon- and machine-learning-based approach. Soc. Netw. Anal. Min. 13, 31 (2023). https://doi.org/10.1007/s13278-023-01030-x

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
Data scraping		Data scraping
datasets		datasets
Data Cleaning.ipynb		Data Cleaning.ipynb
Data analysis for lexicon-based methods.ipynb		Data analysis for lexicon-based methods.ipynb
Further Cleaning and lexicon-based methods.ipynb		Further Cleaning and lexicon-based methods.ipynb
Initial data analysis.ipynb		Initial data analysis.ipynb
README.txt		README.txt
Supervised Approaches.ipynb		Supervised Approaches.ipynb

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1.Data Cleaning.ipynb: The basic steps for data cleaning and data statistics
2.Further Cleaning and lexicon-based method.ipynb: Firstly, tokenization, lemmalization and POS tagging. Secondly, the implementation of three lexicon-based approaches.
3. Initial data analysis.ipynb: Wordcloud and word frequency
4. Data analysis for lexicon-based methods.ipynb:  Statistics of each city, each stage as well as each method.  Complete some data analysis and visualizations.
5.Supervised Approaches.ipynb: The implementation of some supervised classifiers and evaluation

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Sentiment analysis using Twitter data: A comparative application of lexicon and machine learning-based approach. Qi, Y., Shabrina, Z. Sentiment analysis using Twitter data: a comparative application of lexicon- and machine-learning-based approach. Soc. Netw. Anal. Min. 13, 31 (2023). https://doi.org/10.1007/s13278-023-01030-x

Readme