Coding<br />Putting the pieces together<br />
Step 1: Cache your data<br />External Timeline<br />Twapperkeeper (eg #smph2011)<br />The Archivist (Desktop)<br />Twitter...
Data Collection Issue<br />Limited back stories<br />Archivist has a limited cache<br />Twitter to PDF has a 3K previous l...
Step 2: Visual first pass<br />Aim: Get a top level sense of the data<br />Hashtags<br />Archivist Visualisations (online)...
The Archiver<br />
Tagxedo<br />
Step 3: The Unpleasant Bit<br />Raw data needs to be processed<br />Manual<br />Automated<br />
Step 4: Coding<br />Benefits of Manual Coding<br />Subjective judgement<br />You learn a lot<br />Accuracy in semantics<br...
Coding Process<br />Clean the data<br />Assign IDs to tweets<br />Add the additional notes columns<br />Time Frames<br />C...
Coding Choice<br />Visual or numerical?<br />Code book versus Code words<br />Currently: Excel with visual<br />
Excel.<br />A valued ally.<br />
Step 3: It’s time to start coding <br />Top Level Coding<br />Pass 1: identify time periods of interest<br />Pass 2: Tag C...
Step 4<br />Sub Category Coding<br />Pass-Along / Conversational<br />Easier to code, relatively stable<br />Phatic / Stat...
Exemplar Category<br />Pass-Along<br />
Pass Along<br />Automated Endorsement<br />Endorsement<br />Retweet<br />Secondary Social Media<br />User Generated Conten...
Knowing is only half the battle. <br />The other half involves strategy<br />
Questions<br />@stephendann | stephen.dann@anu.edu.au<br />
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The Coding Process for Timeline Analysis

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The Coding Process for Analysis timelines: Step by step guides to turning the Dann 2010 article into spreadsheets, code books and numbers.

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The Coding Process for Timeline Analysis

  1. 1. Coding<br />Putting the pieces together<br />
  2. 2. Step 1: Cache your data<br />External Timeline<br />Twapperkeeper (eg #smph2011)<br />The Archivist (Desktop)<br />Twitter Archiver (newish)<br />Internal Timeline<br />Twapperkeeper (own account only)<br />TwitterArchiver (any public account)<br />
  3. 3. Data Collection Issue<br />Limited back stories<br />Archivist has a limited cache<br />Twitter to PDF has a 3K previous limit<br />TwapperKeeper has a background limit<br />Plan in advance, or improvise quickly<br />
  4. 4. Step 2: Visual first pass<br />Aim: Get a top level sense of the data<br />Hashtags<br />Archivist Visualisations (online)<br />Archivist Desktop<br />Summarizer<br />Timelines<br />TweetStats(online)<br />Tagxedo (online)<br />
  5. 5. The Archiver<br />
  6. 6. Tagxedo<br />
  7. 7. Step 3: The Unpleasant Bit<br />Raw data needs to be processed<br />Manual<br />Automated<br />
  8. 8. Step 4: Coding<br />Benefits of Manual Coding<br />Subjective judgement<br />You learn a lot<br />Accuracy in semantics<br />Downsides<br />You learn a lot.<br />Time consuming.<br />
  9. 9. Coding Process<br />Clean the data<br />Assign IDs to tweets<br />Add the additional notes columns<br />Time Frames<br />Categories<br />Sub Category<br />Sentiment (optional)<br />
  10. 10. Coding Choice<br />Visual or numerical?<br />Code book versus Code words<br />Currently: Excel with visual<br />
  11. 11. Excel.<br />A valued ally.<br />
  12. 12. Step 3: It’s time to start coding <br />Top Level Coding<br />Pass 1: identify time periods of interest<br />Pass 2: Tag Conversational (@reply)<br />Pass 3: Identify Pass-Along (RT, http)<br />Pass 4: News / Status / Phatic<br />
  13. 13. Step 4<br />Sub Category Coding<br />Pass-Along / Conversational<br />Easier to code, relatively stable<br />Phatic / Status / News<br />Harder to code<br />Can (or should) move<br />Can be multiple category* <br />New<br />
  14. 14. Exemplar Category<br />Pass-Along<br />
  15. 15. Pass Along<br />Automated Endorsement<br />Endorsement<br />Retweet<br />Secondary Social Media<br />User Generated Content<br />
  16. 16. Knowing is only half the battle. <br />The other half involves strategy<br />
  17. 17. Questions<br />@stephendann | stephen.dann@anu.edu.au<br />

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