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A small command line tool and set of functions for studying coordination networks in Twitter and other social media data.

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a feasible function for converting Twitter dataset (Twitter CSV format converted by twarc2) to the acceptable format in preprocess.py might be necessary ``` def csv2csv(df): mydf = df[['id', 'author.id', 'author.username',...

Apologies if this has been covered in your documentation and I have missed it. Is there a function to output the specific tweets from each profile which lead them to...

I'm seeing a big difference between two outputted networks when I preprocess a .csv file with and _without_ tweets which contains urls. When I preprocess a .csv file which contains...

Handle common file formats like GZIP and ZIP - in this case of the latter, it would be great to work with multi-file archives.

Develop a workflow for common tasks that involve adding new node attributes to coordination networks, e.g., adding community clusters or compliance check status codes (e.g., checking for suspended/deleted accounts).

enhancement

Implement workflow to construct line graphs from the newly available 'liking users' tweet-level data, where such graphs exploit the sequential order of accounts liking a given tweet, and are connected...

enhancement

Writing these down for our future selves @timothyjgraham 1. Co-temporal-hashtag network, which is not to be confused with the other type of co-hashtag network. As we've seen people coordinate (loosely...

Thoughts to be considered off the top of my head? - What does it mean to create multigraphs - do we need to keep track of which graphs have been...

@timothyjgraham - this prompts me to think that we could also add message _edge_ attributes, which are sampled from the actual coordinated activity between those accounts. _Originally posted by @SamHames...

enhancement

Bit of an oversight not to include what the actual networks are in the documentation :)

documentation