RT_changes

Computes a ranking of authors who receive retweets on specific time intervals.

Requirements

Twarc-count requires Python 3.7 or greater and pip.

Installation

You need to clone this repository.

git clone https://github.com/DataPolitik/rt_changes.git

And then, move to the folder rt_changes. Then, install all modules required by the script:

pip install -r requirements.txt

Usage

changes.py <INFILE> <OUTFILE> [-f [FIELDS] ]

• -g | - -granularity: The time interval. You can use any offset alias for Pandas time series.
• -a | - -alpha: An inertia parameter that weighs retweets received in the previous time intervals (default = 0.005).
• -t | - -threshold: Removes users whose sum of scores are below the specific threshold.
• -i | - -interval: Specify a date period to process.

Interval parameter

The paramenter -i waits for two dates separated by a comma (eg: start_time,end_time) the format should be according YYYY-MM-DD-HH:MM:SS.

Granularity

Some allowed values are:

• H: Hours
• M: Minutes
• Y: Years
• W: Weeks
• S: Seconds

A complete description of allowed aliases can be found at: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases

Examples

Computes a simple ranking

changes.py examples\results.json output.csv

Computes a weekly ranking

changes.py examples\results.json output.csv -g W

Removes all user under 50 points

changes.py examples\results.json output.csv -t 50

Compute data from an specific date interval

changes.py examples/results.json output -i 2021-10-18,2022-10-18

Example of use

Crowdosourced elite during the first wave of Covid19 in Spain