The document discusses analyzing Twitter usage through metrics and categorization. It describes prior research that classified tweets by engagement, topics, and addressivity. The document then presents its own analysis of the author's Twitter history from 2007 to 2009, categorizing tweets as conversational, status updates, passing along information, or news based on grounded theory and previous studies. Minor categories and example tweets are provided for each major category.

1. Twitter metrics and measure Why (more than how to) analyse Twitter Dr Stephen Dann School of Management Marketing & International Business, Australian National University @stephendann or stephen.dann@anu.edu.au

2. Twitter! (What is it good for?) health community (Berger 2009) public libraries (Cahill 2009, Cuddy 2009) political campaigns (Cetina 2009, Henneburg et al 2009) business (Dudley 2009; Power and Forte 2008) journalism (Ettama 2009) civil unrest and protests (Fahmi 2009) social activism (Galer-Unti 2009) live coverage of events (Gay et al 2009) eyewitness accounts (Lariscy et al 2009) government (Macintosh 2009) education (Parslow 2009).

3. Uses and usage casual listening platform Crawford 2009 creating the illusion of physicality Hohl 2009 sense of connectedness and relationship Henneburg et al 2009 venue for conversation Steiner 2009

4. Why dissect a living medium?

5. Metrics What gets measured gets done What gets done can be measured What gets tweeted can be assembled into little diagrams with neat colour schemes

7. Why bother? “Okay, so if we’re going to do it, can it be done well?” “No?” “How about medium rare?”

8. Coding the Streams Krishnamurthy et al (2008) users were classified by follower/following counts, Numbers and ratios means and mechanisms of their engagement Web (61.7%), mobile/text (7.5%), software (22.4%) volume of use Tweets per time period http://www.thegreenhead.com/2008/09/slice-solutions-pie-pan-divider-creates-perfect-slices.php

9. Coding the Streams Java et al 2007 1,348,543 tweets 76,177 users April 01, to May 30, 2007 Four meta-categories daily chatter conversations information / URL sharing news reporting http://www.thegreenhead.com/2008/09/slice-solutions-pie-pan-divider-creates-perfect-slices.php

10. Analysis 2: The Quickening Jansen et al (2009) tweets with brand name expression of brand sentiment 13-week period April 4, 2008 to July 3, 2008. 650 reporting episodes 13 x 50 brands 149,472 tweets

11. Analysis 3: Oh, those guys Pear Analytics (2009) 2000 tweets 11am to 5pm 10 working days Six part classification news (3.6%), spam (3.75%), self-promotion (5.85%), pointless babble (40.55%) conversational (37.55%) pass-along value (8.70%).

12. Where’s the party @? Honeycutt and Herring (2009) four one-hour samples four-hour intervals 6 a.m. to 6 p.m. Eastern Standard Time, on January 11, 2008 Sample of 200 tweets coded with grounded methodology 1) Addressivity: Directs a message to another person 2) Reference: Makes reference to another person, but does not direct a message to him or her. 3) Emoticon: Used as part of an emoticon. 4) Email: Used as part of an email address. 5) Locational 'at': Signals where an entity is located. 6) Non-locational 'at': Used to represent the preposition 'at' other than in the sense of location. 7) Other: Uses not fitting into any other category,

13. Categories Naaman, Boase and Lai (2010) Sample of 400 tweets more than one category was assigned to a single message. Sampling frame 125,593 unique user IDs ‘ personal’ Twitter users 10 friends, 10 followers, 10 messages 911 users N = 350 users The Categories Information Sharing Self Promotion Opinions/Complaints Statements and Random Thoughts Me now Question to followers Presence Maintenance Anecdote (me) Anecdote (others)

14. Tweet, Tweet, Retweet danah boyd Scott Golder Gilad Lotan Microsoft! Conversational Aspects of Retweeting on Twitter Process of RT Preservation Shrtn Attribution / Authorship Rationale Amplify Entertain Comment Visible listening Agreement Support AOL/me too Self gain Self archive

15. The consistent theme People keep using Twitter for personal use. Discussions of “self” Pointless babble Conversational All criticisms of the use of twitter for pleasure and personal consumption

16. What Twitter looks like… … and how are people using Twitter? Twitter – www.twitter.com ‘ Sup?

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

18. Theory and Ideology Useful versus Enjoyable Bohme (2006) outlines a propensity of society to classify technology of all forms into “ useful and therefore valuable” “ enjoyable, therefore irrelevant”. Böhme, G (2006) Technical Gadgetry: Technological Development in the Aesthetic Economy, Thesis Eleven, 86 (1): 54-66

19. Why do it? Twitter is not about the aggregate firehose Twitter is how you use it. Analysis: what (twitter history) as an indicator of how (use of the service)

20. Method Grounded Theory Broad categories based on / supported by six prior studies Sub categories developed from theory and data Bunch of different boxes for sorting the letters Personal Twitter History @stephendann 274 Following / 355 Followers 2841 messages Mar 13 2007 to Aug 18 2009 Sujathan (2009) “ Twitter to pdf ” software.

21. Categories and Results Don’t actual scale to the public sphere! Huzzah! NO MASS GENERALISATION POSSIBLE!

22. Major Categories Conversational Uses an @statement to address another user Status An answer to “What are you doing now?”. Pass along Tweets of endorsement of content News Identifiable news content which is not UGC Phatic Content independent connected presence Spam Junk traffic, unsolicited automated posts, and other automated tweets generated without user consent

23. Minor Categories Conversational 1. Query 2. Referral 3. Action 4. Response Status 1. Personal 2. Temporal 3. Location 4. Mechanical 5. Physical 6. Work 7. Activity Pass along 1. RT 2. UGC 3. Endorsement News 1. Headlines 2. Sport 3. Event 4. Weather Phatic 1. Greeting 2. Fourth wall 3. Broadcast 4. Unclassifiable Spam

24. Results - @stephendann

25. Conversational Query Questions, question marks or polls Referral An @response which contains URLs or recommendation of other Twitter users. Action Activities involving other Twitter users Response Catch-all classification for conversation @tweets

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

27. Conversational

28. Status (1 of 2) Personal Positive or negative sentiment in the form of personal opinion or emotional status Temporal References to specific dates, times, statements of temporal nature (waiting) and temporal action (“Time to” ) Location Geographic references and location statements, including statements of traveling, location change

29. Status (2 of 2) Mechanical Technology or mechanical systems Physical Sensory experiences of a physical nature Work Reference to work related activity Activity Direct statements that answer “What are you doing now?”

30. Status 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) 7% 196 work Waiting for my 2pm performance review to start. 6% 170 temporal It's freezing out there this morning 1% 37 physical I liked Modest Mouse after they became famous. 8% 221 personal Well... I'm in trouble. Used 3829.060MB (62.322%) of your 6GB. You have 22 days remaining 4% 106 mechanical Standing in a lecture theatre talking about Marketing Management. 2% 69 location Diplomacy is the art of saying "Nice doggy" until you find a big enough rock. Captaincy is the timely provision of large enough rocks. 5% 140 broadcast Playing with the internet in the name of science 1% 35 activity Work 80.19 23.96 16.59 3881 7% 196 work Prepositions 79.05 19.84 14.11 3160 6% 170 temporal Perceptual processes, feel, body, health 81.91 23.10 16.87 658 1% 37 physical Total function words, Common verbs, Past / Present tense, Adverbs, Cognitive processes, 80.71 19.05 19.35 4121 8% 221 personal Sadness 70.43 22.02 13.88 1985 4% 106 mechanical Articles, space 78.12 22.96 12.67 1115 2% 69 location Friends, Quote 71.21 22.84 11.21 2119 5% 140 broadcast see, Ingestion,Achievement 76.17 23.26 14.41 533 1% 35 activity Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

31. Status

32. Pass along RT Any statement reproducing another Twitter status using the via @ or RT protocol UGC Links to content created by the user Endorsement Links to web content not created by the sender

33. Pass Along http://twitpic.com/2o1c1 - Bus Slogan Generator Time - http://is.gd/hU2Q 4% 122 Ugc L4D Survivors in Rockband2 singing L7 Pretend We're Dead. http://is.gd/BsVE (HT to @LesbianGamers ). It's seriously amazing. 2% 48 RT 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 4% 108 endorsement Pass along Exemplar % N Category Numbers, leisure 52.89 20.61 39.98 1679 4% 122 Ugc SemiC 54.31 24.75 16.85 893 2% 48 RT Parenth, Dash 55.71 21.05 30.12 1777 4% 108 endorsement Linguistic Inquiry Results Dictionary Words >6 letters Words/ Sentence Word Count % N Category

34. Pass Along

35. News Headlines Coverage of breaking news and personal eye-witness accounts of news events Sport Identifiable results of sporting events Event Any tweet which represents the live discussion of an identified or identifiable event Weather Report of weather conditions without commentary

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

37. Phatic Greeting Statements of greetings to the broader Twitter community Fourth wall Textual equivalent of comments made directly to camera in television or cinema Broadcast Textual soliloquy, monologue and undirected statements of opinion Unclassifiable Unclassifiable strings of text

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

39. Phatic

40. Questions Useful Twitter classification approach? Replicable across multiple accounts? Improvements to the heavy duty lifting? Subjective manual coding is a feature Improved data collection

41. Questions [email_address] Or @stephendann

42. References Böhme, G (2006) Technical Gadgetry: Technological Development in the Aesthetic Economy, Thesis Eleven, 86 (1): 54-66 Cetina, K K 2009, What is a Pipe? bama and the Sociological Imagination, Theory, Culture & Society 2009 26(5): 129–140 Crawford, K (2009)'Following you: Disciplines of listening in social media',Continuum,23:4,525 — 535 Dudley, E 2009, Editorial: Lines of Communication, Journal of Librarianship and Information Science 2009; 41; 131-134 Ettama, J 2009 New media and new mechanisms of public accountability, Journalism 2009; 10; 319-321 Fahmi, W S 2009, Bloggers' street movement and the right to the city. (Re)claiming Cairo's real and virtual "spaces of freedom", Environment and Urbanization 2009; 21; 89-107 Galer-Unti, R 2009, Guerilla Advocacy: Using Aggressive Marketing Techniques for Health Policy Change, Health Promotion Practice, 10; 325-327 Gay, P Plait, P, Raddick, J, Cain, F and Lakdawalla, E (2009) "Live Casting: Bringing Astronomy to the Masses in Real Time", CAP Journal, June 26-29 Henneburg, S. Scammell, M and O'Shaughnessy, N (2009) Political marketing management and theories of democracy, Marketing Theory 2009; 9; 165-188 Honeycutt, C and Herring, S C (2009) Beyond Microblogging: Conversation and Collaboration via Twitter, (2009). Proceedings of the Forty-Second Hawai’i International Conference on System Sciences (HICSS-42). Los Alamitos, CA: IEEE Press. 1-10, http://ella.slis.indiana.edu/~herring/honeycutt.herring.2009.pdf Jansen, B, Zhang, M, Sobel, K and Chowdury, A (2009) Twitter power: Tweets as electronic word of mouth, Journal of the American Society for Information Science and Technology, 60(11):2169–2188, 2009 http://ist.psu.edu/faculty_pages/jjansen/academic/jansen_twitter_electronic_word_of_mouth.pdf Java, A, Song, X, Finin, T and Tseng, B (2007) Why We Twitter: Understanding Microblogging Usage and Communities, Joint 9th WEBKDD and 1st SNA-KDD Workshop ’07 , August 12, 2007, p 56-65

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