c.lindgren();

#RSA16 Keyword Cross-Mentions | Chord Diagram

By Chris Lindgren

Back to #RSA16 dataviz index

This chord diagram shows some top overlapping keywords from tweets collected during the 2016 Rhetoric Society of America conference.

A special thanks to Nadieh Bremer's amazing code and tutorial about orientation gradient chord diagrams. Throughout this process, I have learned a lot more about how to develop these diagrams: their data structures, library code methods, and even SVGs (Scalable Vector Graphics). (I still need to rotate those labels vertically, though!)

Other keywords

  • Email me some suggestions based on the word bubble-cloud: lindg250 [at] umn [dot] edu. :-)

Description of the data

  • More general source and processing information can be read in the larger project README.
  • Asterisks indicate multiple words searched under the particular keyword. I used regular expressions to catch plurals, noun or verb forms of a particular keyword. The list of regular expressions used are as follows:
    • Accessibility == (/baccess\S*|\binaccess\S*)
    • Change == (\bchang\S*|\brhetoricandchange\b)
    • Digital == ((\bdig\S*))
    • Disability == (disab\S*)|(\bable\S*))
    • Embodied == ((\bbod\S*)|(embodi\S*))
    • Feminist == (fem\S*)
    • Institution == (institution\S*)
    • Invisible == (invisibl\S*)
    • Machine == (\bmachin\S*)
    • Material == (material\S*)
    • Memory == ((\bmemor\S*))
    • Method == (method\S*)
    • Object == ((\bobj\S*|ooo))
    • Public == (public\S*)
    • Race == ((\brac\S*))
    • Sex == (\bsex\S*|\bbisex\S*|\bheterosex\S*|\bcishet)
  • Keywords were chosen by overall frequency in the total corpus of tweets, as well as a more qualitative munging of the data to check for cross-mentions. The matrix produced is as follows and is located in the chord-diagram-script.js file:
    // rsa16 keyword cross-mentions
    var matrix = [
      [ 0 ,12,0 ,0 ,0 ,0 ,0 ,0 ,6 ,0 ,26,0 ,0 ,0 ,10,6 ,0 ,8 ,0 ,0 ,20,0 ],// material
      [ 12,0 ,30,28,0 ,0 ,21,0 ,0 ,0 ,0 ,41,72,0 ,14,0 ,0 ,0 ,0 ,0 ,0 ,12],// disability
      [ 0 ,30,0 ,30,0 ,0 ,0 ,13,6 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ],// mental
      [ 0 ,28,30,0 ,30,6 ,36,0 ,23,16,13,0 ,0 ,24,0 ,14,0 ,0 ,0 ,0 ,0 ,0 ],// race
      [ 0 ,0 ,0 ,30,0 ,8 ,0 ,0 ,0 ,0 ,6 ,0 ,0 ,6 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ],// black
      [ 0 ,0 ,0 ,6 ,0 ,0 ,8 ,13,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ],// white
      [ 0 ,21,0 ,36,18,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,6 ],// latin/x
      [ 0 ,0 ,6 ,0 ,0 ,13,0 ,0 ,0 ,0 ,0 ,0 ,0 ,18,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ],// invisible
      [ 6 ,0 ,0 ,24,0 ,0 ,0 ,0 ,0 ,42,0 ,0 ,0 ,0 ,22,12,0 ,0 ,0 ,0 ,0 ,0 ],// feminist
      [ 0 ,0 ,0 ,16,0 ,0 ,0 ,0 ,42,0 ,0 ,6 ,0 ,0 ,0 ,8 ,0 ,0 ,0 ,0 ,0 ,0 ],// method
      [ 26,0 ,0 ,13,6 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,34,6 ,0 ,22,0 ,24,0 ,0 ],// embodied
      [ 0 ,48,0 ,0 ,0 ,0 ,0 ,0 ,0 ,6 ,0 ,0 ,50,0 ,27,0 ,0 ,0 ,8 ,28,0 ,0 ],// accessibility
      [ 0 ,72,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,50,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ],// institutional
      [ 0 ,0 ,0 ,23,6 ,0 ,0 ,18,0 ,0 ,0 ,0 ,0 ,0 ,26,0 ,0 ,0 ,6 ,6 ,14,0 ],// public
      [ 10,14,0 ,0 ,0 ,0 ,0 ,0 ,22,0 ,34,27,0 ,26,0 ,0 ,12,0 ,12,6 ,0 ,0 ],// change
      [ 6 ,0 ,0 ,14,0 ,0 ,0 ,0 ,12,8 ,6 ,0 ,0 ,0 ,0 ,0 ,6 ,0 ,0 ,0 ,0 ,0 ],// gender
      [ 0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,12,6 ,0 ,0 ,0 ,0 ,0 ,0 ],// sex
      [ 8 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,22,0 ,0 ,0 ,0 ,0 ,0 ,0 ,8 ,0 ,0 ,0 ],// object
      [ 8 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,22,0 ,0 ,6 ,12,0 ,0 ,8 ,0 ,86,6 ,0 ],// archive
      [ 0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,24,28,0 ,6 ,6 ,0 ,0 ,0 ,86,0 ,12,6 ],// digital
      [ 20,0 ,0 ,0 ,0 ,0 ,6 ,0 ,0 ,0 ,0 ,0 ,0 ,14,0 ,0 ,0 ,0 ,6 ,12,0 ,0 ],// memory
      [ 0 ,12,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,6 ,0 ,0 ],// machine
    ];
                  
  • Keyword files were created individually with my sankey-counter.py script. From there, I qualitatively checked and verified the cross-mentions, which resulted in the above matrix data structure.
  • stopwords were also used in the sankey-counter.py script:
    stopwords = set([ "rt","teh","i","me","my","myself","we","us","#rsa16","rsa16","http","amp","like",
                                    "our","ours","ourselves","you","your","yours","yourself","just","dont",
                                    "yourselves","he","him","his","himself","she","her","hers","wouldn",
                                    "herself","it","its","itself","they","them","their","theirs","ways",
                                    "themselves","what","which","who","whom","whose","this","get",
                                    "that","these","those","am","is","are","also","was","were","be","been",
                                    "being","have","has","had","having","do","does","did","doing",
                                    "will","would","should","can","could","ought","i'm","you're","he's",
                                    "she's","it's","we're","they're","i've","you've","we've","they've",
                                    "i'd","you'd","he'd","she'd","we'd","they'd","i'll","you'll","he'll",
                                    "she'll","we'll","they'll","isn't","aren't","wasn't","weren't","hasn't",
                                    "haven't","hadn't","doesn't","don't","didn't","won't","wouldn't","wont",
                                    "shouldn't","can't","cannot","couldn't","mustn't","let's","that's","who's",
                                    "what's","here's","there's","when's","where's","why's","how's","a","an",
                                    "the","and","but","if","or","because","as","until","while","of","at","by","for",
                                    "with","about","against","between","into","through","during","before","after",
                                    "above","below","to","from","up","upon","down","in","out","on","off","over",
                                    "under","again","further","then","once","here","there","when","where",
                                    "why","how","all","any","both","each","few","more","most","other","some",
                                    "such","no","nor","not","only","own","same","so","than","too","very","say",
                                    "says","said","shall","https","one","presentation","now","way","hey","fri",
                                    "well","yet","friday","2013","since"])
                  
  • Cross-mentions were tallied for each keyword with a >5 minimum.
  • Retweets are counted in the tally.
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