A Python package for collecting and spatio-temporal analysis of social media contents
- GitHub repo: https://github.com/MahdiFarnaghi/geoso
- PyPI: https://pypi.org/project/geoso/
- Documentation: https://MahdiFarnaghi.github.io/geoso
- Free software: MIT license
geoso is a Python library, being developed to facilitate collection, cleansing, and spatial and spatio-temporal analysis of social media data.
The vision is that the library provided the possibility to download geo-tagged social media content into a database, e.g., PostgreSQL, preprocess the stored data, retrieve, and analyse the data.
- Twitter
- Download tweets from Twitter Streaming API and save them into either a database or JSON Lines text files.
- Import tweets that were from JSON Lines text files into the database.
- Export tweets to CSV file.
- Clean tweets text in the database.
- Retrieve tweets from the database as pandas DataFrame.
- Twitter
- Clean tweets text in the database.
- Detect tweets that were published by bots.
If you are using this library, the following scientific publications could be of your interest.
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Farnaghi, M., Ghaemi, Z., & Mansourian, A. (2020). Dynamic Spatio-Temporal Tweet Mining for Event Detection: A Case Study of Hurricane Florence. International Journal of Disaster Risk Science, 11, 378-393.
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Ostermann, F. O. (2021). Linking geosocial sensing with the socio-demographic fabric of smart cities. ISPRS international journal of geo-information, 10(2), 1-22. [52].
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Zahra, K., Imran, M., Ostermann, F. O. (2020). Automatic identification of eyewitness messages on twitter during disasters. Information processing & management 57 (1), 102107
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Ghaemi, Z. & Farnaghi, M. 2019. A Varied Density-based Clustering Approach for Event Detection from Heterogeneous Twitter Data. ISPRS International Journal of Geo-Information, 8 (2).
- spaCy is used for cleaning texts.
- Tweepy is used to develop Twitter data retrieval functionalities.
- This package was created with Cookiecutter and the giswqs/pypackage project template and instructions from Python Packages book.