The document summarizes different ways that Twitter data and usage has been analyzed in prior studies. It discusses 6 prior analyses that took different approaches such as removing user information, categorizing tweet content, analyzing brand sentiment, and classifying messages. The document then describes its own coding approach to analyze a sample of the author's Twitter history based on major categories of conversational, status, pass along, news, and spam messages. Results of this analysis on percentages of tweets in each category and subcategory are also presented.

1. Twitter Analytics A user’s guide to interpreting, reinterpreting and misinterpreting the social media service. Dr Stephen Dann School of Management Marketing & International Business, Australian National University @stephendann or stephen.dann@anu.edu.au Siêu thị điện máy Việt Long www.vietlongplaza.com.vn

2. If you’re on Twitter Questions can be sent to @stephendann Siêu thị điện máy Việt Long www.vietlongplaza.com.vn

7. How to dissect a living medium? www.digiworldhanoi.vn

8. Raw Counts Tweetstats – www.tweetstats.com

9. Text Analysis Tweetstats – www.tweetstats.com Wordle – wordle.com

10. Leximancer Leximancer – www.leximancer.com

11. Coded Content Analysis Made up for this set of slides.

12. Same Data set… So many different ways to present the results

13. Coded Content Analysis

15. Prior Analysis

24. Recoding the Platform Let’s do it my way

29. Categories and Results

31. Results- @stephendann phatic

33. Results - @stephendann

35. Conversational Category N % Exemplar Action 77 3% *waves at @USERNAME* Pass-along 66 2% @USERNAME Items under $1000 are exempt. http://is.gd/AV7K Query 480 17% Invading Germany from France. Who's with me? Response 850 30% @USERNAME Beware the polar bears. Category N % Word Count Words/ Sentence >6 letters Dictionary Words Linguistic Inquiry Results Action 77 3% 958 14.74 23.80 67.75 Conjunctions, Inhibition, Inclusive Biological processes Pass-along 66 2% 1020 18.89 21.86 54.31 OtherP, Period Query 480 17% 7032 10.13 21.22 75.33 Impersonal pronouns, Auxiliary verbs, Tentative, Discrepancy, QMark Response 850 30% 13637 17.05 21.97 73.84 3rd pers plural

36. Conversational

39. Status activity 35 1% Playing with the internet in the name of science broadcast 140 5% Diplomacy is the art of saying "Nice doggy" until you find a big enough rock. Captaincy is the timely provision of large enough rocks. location 69 2% Standing in a lecture theatre talking about Marketing Management. mechanical 106 4% Well... I'm in trouble. Used 3829.060MB (62.322%) of your 6GB. You have 22 days remaining personal 221 8% I liked Modest Mouse after they became famous. physical 37 1% It's freezing out there this morning temporal 170 6% Waiting for my 2pm performance review to start. work 196 7% Firing off e-mail after e-mail to clear my to do list (knowing that's a great way to regenerate to do list items doesn't stop me or help me) Category N % Word Count Words/ Sentence >6 letters Dictionary Words Linguistic Inquiry Results activity 35 1% 533 14.41 23.26 76.17 see, Ingestion,Achievement broadcast 140 5% 2119 11.21 22.84 71.21 Friends, Quote location 69 2% 1115 12.67 22.96 78.12 Articles, space mechanical 106 4% 1985 13.88 22.02 70.43 Sadness personal 221 8% 4121 19.35 19.05 80.71 Total function words, Common verbs, Past / Present tense, Adverbs, Cognitive processes, physical 37 1% 658 16.87 23.10 81.91 Perceptual processes, feel, body, health temporal 170 6% 3160 14.11 19.84 79.05 Prepositions work 196 7% 3881 16.59 23.96 80.19 Work

40. Status

42. Pass Along Category N % Exemplar Pass along endorsement 108 4% I'm looking myself up on Publish or Perish (http://rurl.org/iw4) to find a reference to a paper that cited me because I want to cite them RT 48 2% L4D Survivors in Rockband2 singing L7 Pretend We're Dead. http://is.gd/BsVE (HT to @LesbianGamers ). It's seriously amazing. Ugc 122 4% http://twitpic.com/2o1c1 - Bus Slogan Generator Time - http://is.gd/hU2Q Category N % Word Count Words/ Sentence >6 letters Dictionary Words Linguistic Inquiry Results endorsement 108 4% 1777 30.12 21.05 55.71 Parenth, Dash RT 48 2% 893 16.85 24.75 54.31 SemiC Ugc 122 4% 1679 39.98 20.61 52.89 Numbers, leisure

43. Pass Along

45. News Category N % Exemplar News Event 13 0% Between NASA's satellite and autoanalysis of imagery, and Google Map data, scientific proof where there's smoke, there's fires #bcc2 Sport - - - Headlines - - - Category N % Word Count Words/ Sentence >6 letters Dictionary Words Linguistic Inquiry Results News Event 13 0% 192 10.67 22.92 65.62 Negative emotion, Anger Certainty Perceptual processes

47. Phatic Category N % Exemplar Phatic Action 30 1% *wanders through his twitter follower list, blocking all of the automated/spam follower accounts* Fourth wall 49 2% Note to self: Just because you're carrying tiny vials of hypercaffeine is no reason to start calculating remote delivery systems for them. Greeting 17 1% Good morning Twitterverse. How's the world outside? Unclassifiable 7 0% AAAAAAAAAAAAAAARGH Category N % Word Count Words/ Sentence >6 letters Dictionary Words Linguistic Inquiry Results Action 30 1% 456 22.80 26.75 75.22 Anxiety, hear, motion Fourthwall 49 2% 836 12.29 20.69 76.44 Negations, Quantifiers, Social processes, Humans, Affective processes, Causation, Exclusive Greeting 17 1% 208 7.70 29.33 78.37 Future tense, Positive emotion Relativity, time Unclassifiable 7 0% 6 3.00 33.33 33.33 NIL

48. Phatic

51. Future research The Public Timeline versus the Classification Scheme

52. Questions [email_address] Or @stephendann www.digiworldhanoi.vn