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Tweet2Graph

Fast and easy social graphs from tweets

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Installation

To install using pip, use

pip install tweet2graph

Usage

  • Import the library:
from tweet2graph import Tweets2Graph
  • Choose which interaction between users are relevant for you:
backend = Tweets2Graph(interactions=["retweet","quote","reply"], #relevant interactions
                          username="screen_name")                #name of the nodes
  • Load dataset
#load a single .csv/.json file
backend.from_file("examples/csv/1614874276.csv")

#load a folder 
backend.from_folder("examples/csv/")

#load from a mongodb collections
backend.from_mongo(connection_string='<CONNECTION_STRING>',
                    database='<DB_NAME>',
                    collection='<COLLECTION_NAME>')
                    
#or from a pandas dataframe
backend.from_dataframe(dataframe)
  • Fit/Transform

    #organize data
    backend.fit()
    
    #create graph
    graph = backend.transform()
    
    #or simply
    graph = backend.fit_transform()
  • Show and save

    import networkx as nx
    nx.draw(graph,with_labels=False,node_size=5,font_size=5,font_color="red",node_color="black")
    nx.write_adjlist(G=graph)

graphs

TODO:

  • add connected component
  • .from_user('<USER_NAME>') method
  • Add metadata to tweet
  • Insert mentions in possible interactions
  • Add custom error and better explanation
  • Add speed benchmark and figures
  • Add .from_stream(id="<hashtag>") method
  • Update .from_stream(id="<hashtag>") with two distinct processes
  • Dockerfile

License

MIT

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Trasform tweet in social graph effortlessy

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