#ANZMAC2014 Presentation on the use of the Dann (2015) (forthcoming) Content Classification Framework

1. Twitter!
TWITTER CONTENT ANALYSIS FRAMEWORK: CLASSIFICATION AND
CODING OF TWITTER CONTENT

2. Dr Stephen Dann
 You may remember me from…
 Dann (2010) Twitter Content Classification Framework
 That special session last year

3. The Plan
 Announce the update patch for Dann (2.0.15) from Dann (2.0.10)
 Show some data
 Ask an awkward question
 Questions (yours)

4. The Patch Notes
 Dann (2015)
 Grounded Theory Strikes Again
 Moved “Broadcast” from “Social Presence” to “Status”
 Collapsed several sub domains
 Bringing the focal point of the coding to a 3 level domain
 Create
 Communicate
 Curate

5. Words.

6. The Five Domains
1. Conversational
 replies
2. News
 Messages of factual / external commentary
3. Pass along
 Existing content shared or Retweeted
4. Social Presence
 Connectivity via ritual textual behaviour
5. Broadcast
 Opinions and experience

7. There’s a lot of literature
 Response: Tweet that commence with the @ symbol to indicate a
directed response to another Twitter user (Cahill 2009; Ratkiewicz 2010;
Steiner 2009; Wilson 2008). Further sub-classification of response is not
included.
 Referrals: Any tweet that would fit as pass-along which is directed to
another Twitter user (Efron 2011; Honeycutt and Herring, 2009; Naaman,
Boase and Lai, 2010). Here, the purpose of the tweet is to provide
Twitter-external content link directly to the respondent, rather than to all
followers of the account.
 Rhetorical Presence (previously action) is the use of the @username to
acknowledge physical, social or temporal connection (Cranefield and
Yoong, 2009; Efron 2011; Hohl 2009; Jansen et al. 2009). Rhetorical
Presence can be attribution of content, acknowledgment of physical
co-location or introductions of a Twitter user to another’s timeline
followers.

8. Conversational Identified by a @statement to address another user
Response Any tweets which commence or finish with another user’s name and which
do not meet the requirements of the referral category
Referral @responses containing URLs or recommendation of other Twitter users.
(Excludes RT @user)
Rhetorical Presence Activities involving other Twitter users, or tweets that describe the presence
of other Twitter users.
News Identifiable newsworthy content
Journalism Coverage of live events including factual, descriptive recounts or opinion
and social commentary
Real-Time Event Live discussion of an identifiable event such as a conference, live television
or live event collected with or without a consistent #hashtag.
Press Release Identifiable announcement of a forthcoming event without URLs to an
external source such as timetable announcements, schedules and session
start times
Sport Identifiable results of sporting events or discussions of sporting performances
Transport Traffic, transport, flight, road or rail related announcements including
accidents and delays
Weather Report of prevailing weather conditions inclusive of extreme weather events
and natural disasters

9. Pass along Tweets as curation of content
Annotated Media Tweets that are captions for media hosted on Twitter
Curation Posting of third party content for followers via the Twitter URL (t.co) or other
URL.
Offline source Tweet that contains a reference in APA, Oxford or Harvard format, or a
statement in inverted commas to denote a quotation from a third party,
speaker or source material
Retweets Partial or full reproduction of another tweet marked with “RT”, “retweet”,
“MT” or “modified tweet”
Social Presence Messages of connected presence
Ceremonial Greetings Tweets where the community is addressed indirectly as a whole with the
greeting or statements of gratitude
Fourth wall Textual equivalent of comments made directly to the camera for an
imagined audience
Self-referential commentary Tweets directed by the author to themselves through “Note to self” “FYI” or
“Just for the record” and function as thought bubble style comments
Unclassifiable Catch-all category for cat-on-keyboard input and unclassifiable strings of
text

10. Broadcast Tweets that express the account holder's experiences
Action The diary of daily life tweets which answer “What are you doing?”
Reflective Statements that address cognitive or emotive responses that answer “What
am I thinking?” or “What am I feeling?”
Experience Tweets that relay the physical experience as an answer to “What am I
experiencing?” – includes location, physical sensations, temporal experience
and interaction
Statement Observation of life, stated opinions and streams of consciousness “What do I
want the world to know?” and “What are my thoughts on a specific topic?”

11. Not just classifications
 Via
 Source of the Tweet
 96 different software clients (thus far)
 Timestamp
 Day of the Week
 Time of day
 Office hours | morning / evening

12. Via
(WA Reelection Candidates)
ID Platform N %
63 Web 901 35.0%
54 Twitter for iPhone 668 26.0%
51 Twitter for Android 469 18.2%
6 Echofon 91 3.5%
40 Tweet Button 86 3.3%
42 Tweetbot for iOS 66 2.6%
7 Facebook 55 2.1%
53 Twitter for iPad 51 2.0%
16 iOS 45 1.8%
10 Google 42 1.6%
15 Instagram on iOS 38 1.5%

13. Sample Data
(WA Reelection Candidates)
Preelection Block Election Block Post Election1 Post Election 2
Conversational 615 954 461 743
News 50 97 58 69
Pass along 884 1444 701 899
Social Presence 5 13 4 12
Broadcast 38 63 36 53
1592 2571 1260 1776

14. Sample Data
Pre-election
Election
Block
Post
Election1
Post
Election 2
n
Presence of Others
Conversational - Response 394 643 367 612 2016
Conversational - Rhetorical Presence 60 75 40 56 231
Pass along - Retweets 694 1092 465 617 2868
1148 1810 872 1285 5115
External Content
Conversational - Referral 161 236 54 75 526
Pass along - Curation 189 351 231 282 1053
350 587 285 357 1579
Ratio: Internal to External 3.28: 1 3.08: 1 3.05: 1 3.60: 1 3.24: 1

15. Monday Tuesday Wednesday Thursday Friday Saturday Sunday N
Web 86 172 158 133 174 123 55 901
Twitter for iPhone
95 70 66 135 94 128 80 668
Twitter for Android
49 81 74 42 92 75 56 469
Echofon 12 21 18 3 4 3 30 91
Tweet Button 11 12 16 13 10 12 12 86
Tweetbot for iOS 11 7 3 5 7 22 11 66
Facebook 3 20 22 2 3 4 1 55
Twitter for iPad 7 6 6 12 8 6 6 51
iOS 3 9 8 7 7 9 2 45
Google 6 6 11 3 8 2 6 42
Instagram on iOS
3 3 3 7 7 9 6 38
TweetCaster for Android
1 2 1 3 4 5 14 30
TweetDeck 0 0 3 4 5 0 0 12
Other 2 5 1 3 1 3 2 17
289 414 390 372 424 401 281 2571

16. The Question
 Expressed preference choice data
 Content | Curate | Communicate
 Time series
 Hours | Days | Time blocks
 Device specific data
 mobile | desktop | other
 Where’s the formula?

17. The (in)tractable problem
 If Twitter use is an expressed choice, and we have data that records
that expressed choice, can we model and predict?
 Can we extract the necessary calculations?