https://github.com/oniani/ira-analysis
Code for the Paper "Textual and Statistical Analysis of Russian IRA Facebook Advertisements"
https://github.com/oniani/ira-analysis
Last synced: 11 months ago
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Code for the Paper "Textual and Statistical Analysis of Russian IRA Facebook Advertisements"
- Host: GitHub
- URL: https://github.com/oniani/ira-analysis
- Owner: oniani
- License: mit
- Created: 2019-07-13T23:58:11.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2022-09-02T07:33:13.000Z (almost 4 years ago)
- Last Synced: 2025-08-30T16:53:14.651Z (11 months ago)
- Language: Python
- Homepage:
- Size: 29.5 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Textual and Statistical Analysis of Russian IRA Facebook Advertisements
## Organization
```zsh
.
├── LICENSE # A license for the project
├── data # Data storage
├── koppel11 # Implementation of the paper "koppel11"
├── nlp-model # NLP model for binary classification of IRA ad texts
├── paper # Paper
├── pdf-scraping # Tools for PDF scraping
├── visualization # Programs and scripts for statistical visualizations
└── web-app # Web application using the pre-trained NLP model
```
## Working with Data
The recommended way of working with the CSV data is using the `pandas` library.
`pandas` provides a user-friendly environment for working with data in the
tabular format. See an example below. Alternatively, one could also use
Python's built-in `csv` module (or other programming language of preference and
its tools).
```python3
Python 3.7.3 (default, Mar 27 2019, 09:23:15)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.5.0 -- An enhanced Interactive Python. Type '?' for help.
In [1]: import pandas as pd
In [2]:
In [2]: data = pd.read_csv("./data/csv/year-2015/2015-Quarter-2.csv", na_filter=False, thousands=",")
In [3]:
In [3]: data.columns
Out[3]:
Index(['Ad ID', 'Ad Text', 'Ad Landing Page', 'Ad Targeting Location',
'Excluded Connections', 'Age', 'Language', 'Placements',
'People Who Match', 'Friends of Connections', 'Ad Impressions',
'Ad Clicks', 'Ad Spend', 'Ad Creation Date', 'Ad End Date'],
dtype='object')
In [4]:
In [4]: data.dtypes
Out[4]:
Ad ID int64
Ad Text object
Ad Landing Page object
Ad Targeting Location object
Excluded Connections object
Age object
Language object
Placements object
People Who Match object
Friends of Connections object
Ad Impressions int64
Ad Clicks int64
Ad Spend object
Ad Creation Date object
Ad End Date object
dtype: object
```
## References
- [Authorship attribution in the wild](https://www.researchgate.net/publication/220147732_Authorship_attribution_in_the_wild)
- [Who Wrote the Web? Revisiting Influential Author Identification Research Applicable to Information Retrieval](https://www.researchgate.net/publication/309025021_Who_Wrote_the_Web_Revisiting_Influential_Author_Identification_Research_Applicable_to_Information_Retrieval)
- [Authorship Attribution of Micro-Messages](https://www.aclweb.org/anthology/D13-1193)
- [Design and Implementation of a Machine Learning-Based Authorship Identification Model](https://www.hindawi.com/journals/sp/2019/9431073/)
- [Exposing Russia’s Effort to Sow Discord Online: The Internet Research Agency and Advertisements](https://intelligence.house.gov/social-media-content/)
- [The Tactics & Tropes of the Internet Research Agency](https://disinformationreport.blob.core.windows.net/disinformation-report/NewKnowledge-Disinformation-Report-Whitepaper.pdf)
- [How Russian Trolls Used Meme Warfare to Divide America](https://www.wired.com/story/russia-ira-propaganda-senate-report/)
- [Racist cop Facebook posts are a public safety problem | Editorial](https://www.inquirer.com/opinion/editorials/philadelphia-police-facebook-posts-plain-view-project-racist-20190605.html)
- [Facebook Ad Library](https://www.facebook.com/ads/library)
## License
[MIT License](LICENSE)