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Authentic title: Credible, yet
human sounding subtitle
Authoritative Rank with an everyperson touch
Engagement | Additional Engagement
Australian Political Parties and
social media: uses and attitudes
Dr Stephen Dann, ANU
@stephendann | @drstephendann
Perhaps the only moment of
silence the hashtag gets today…
Context
• Social media use in Australia by political parties
• Suddenly, Senate Re-Election
• The second most fun data collection event ever
• 77 candidates
• 31 Twitter handles
• 27 active(ish) Twitter users
• 20 weeks of data
• 1 very sad state of affairs.
The Spoiler
It’s not authentic communication
The Method
• Content Analysis
• Public Timelines
• Secondary Data
• 20 week capture period
• 10 weeks prior to the election
• 10 weeks post election
• The Plan
• benchmark set of behaviours
• Divide into 5 week blocks
• Code into Content Classification
• Find differences
• Elected/Not Elected
• Election Period / Reality
• Block 1 and Block 4
• Write nifty paper
The Framework
• Content Categorisation
• V.1 Developed in 2009
• Dann (2010)
• V.2 Patched in 2011
• Dann (2011)
• V.3
• Wheels fell off
• V.4 Significant Rebuild
• Dann 2014 / Dann 2015
• Principle Idea
• All tweets come from one of three
options
• Original Content for Twitter
• Reactions within Twitter
• External Content outside of Twitter
• Grounded Theory approach
• Lit.Rev x Content x Coding
• Tweets fit 5 broad categories
Five Categories
Box Single sentence
Conversational Uses an @statement to address another user
News Identifiable newsworthy content
Pass along Tweets as curation of content
Social Presence Messages of connected presence
Broadcast Tweets which express the account holder's experiences
Oh, and spam
Spam Unsolicited content
Conversation jacking @responses based on an automated response to a keyword, brand or
product mention
Trendjacking Spam message containing multiple hashtags and link to a malicious website
“Truthiness” multiple identical tweets from different accounts
WA Twitter Data (20 weeks)
Frequency Percent Valid Percent Cumulative Percent
Pass along 3928 54.6 54.6 54.6
Conversational 2773 38.5 38.5 93.1
News 274 3.8 3.8 96.9
Broadcast 190 2.6 2.6 99.5
Social Presence 34 0.5 0.5 100
Total 7199 100 100
27 Candidates. 20 weeks.
The Pass-along-a-thon
Pass along Tweets as curation of content
Curation Posting of third party content for followers via the Twitter URL (t.co) or other URL.
#Sydney rally to save #Medicare. #auspol #StopAbbott
http://t.co/OWzppqhwIf
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
"I drink Coke because I support their multicultural advertising campaign" this is my
new excuse for drinking too much soft drink.
Retweets Partial or full reproduction of another tweet (RT retweet or MT modified tweet)
RT @PopulationParty: SPP's @Peter_Strachan is glad to have put WA's record population
growth on the political agenda http://t.co/niYRjoK8hJ…WAvotes…auspol
Conversations
Conversational Uses an @statement to address another user
Response Classification for tweets which commence with another user’s name and which do not meet the
requirements of the referral category
@Mark_Butler_MP @margokingston1 Best bang for your buck by far
is to reduce population pressure.
Referral An @response which contains URLs or recommendation of other Twitter users. (Excludes RT @user)
@enviro_al March 1st, Cruelty Free Festival. Subscribe here and I'll email when/if we have
more details. http://t.co/hUHWHAzspP
Rhetorical Presence Activities involving other Twitter users, or tweets which describe the presence of other Twitter users.
I'm voting for @WikiLeaksParty on Saturday. I just added a badge to my profile
picture. Please show your support too!
Presence of Others versus External Content
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
Election Day Tweeting
Election Day Tweeting
Conversational News Pass along Status
Pirate Party 8 3 9 0
Unnamed Ticket 7 2 60 1
The Greens (WA) 6 4 12 0
#Sustainable Population Party 4 0 8 0
The Nationals 4 2 12 1
Australian Labor Party 3 1 12 0
Liberal 1 0 1 1
Socialist Alliance 1 0 2 0
Voluntary Euthanasia Party 0 0 3 0
Total 34 12 119 3
How could we have used Twitter?
• Three character opportunities
• provision of insight into the candidate,
• information for the followers
• direct engagement with an audience.
• Two message opportunities
• Promise management
• Embodying the party values
Social Presence Messages of connected presence
Ceremonial
Greetings
Tweets where the community is addressed indirectly with a greeting
Fourth wall Textual equivalent of comments made directly to camera to an imagined audience
Self-referential “Note to self” “FYI” or “Just for the record” - thought bubble style comments
Unclassifiable Cat-on-keyboard input and pocket tweeting
Broadcast Tweets which express the account holder's experiences
Action The diary of daily life tweets which answer “What are you doing?”
Reflective “What am I thinking?” or “What am I feeling?”
Experience “What am I experiencing?”
Broadcast
Statement
“What am I wanting the world to know?” and “What are my thoughts on a topic?”
Adapting the Hughes and Dann (2007)
Kevin07 Lessons
• Importance of a political product
• Technically impressive Twitter stream is no substitute for acceptable policy
• Political communications travel
• headline delivery – plug Twitter into journalists.
• Social costs of public support are an electoral factor
• Twitter is seen and felt to be visible
• Voter loyalty cannot be assumed or presumed
• Followers are not votes
• Candidates require offline support
The Winner’s Circle (Election Week)
Candidate Conversational News Pass along Social Presence Broadcast
*lindareynoldswa 0 0 6 0 1 7
*SenatorCash 22 1 31 0 0 54
*SenatorLudlam 128 16 178 0 4 326
This was quite depressing.
Twitter and Elections
• More promise than reality
• Potential is not apparently self evident
• May become the worst possible platform for politics-as-usual
• Social media as the insider platform… sort of.
Livetweeting the conference
You don't hear the phrase "we had a dance in Yackandandah" enough in
presentations. #CMPM2014
Key Metrics: Day 1
• 24 Voices
• usual power law distributions
Frequency Percent
Conversational
25 8.8
News 104 36.7
Pass along 87 30.7
Social Presence
5 1.8
Status Broadcast
58 20.5
Spam 4 1.4
Total 283 100.00.00
0.20
0.40
0.60
0.80
1.00
1.20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Ratio
Key Metrics 2
Twitter Frequency
drstephendann 131
stephendann 35
Elias_Hallaj 23
mikesmithqld 22
edwinat 20
JR_Rayner 17
marketingandrew 14
• Livecaster
• drstephendann – play by play
• stephendann - colour commentary
• Commentary Team
• Elias_Hallaj
• mikesmithqld
• edwinat
• JR_Rayner
• marketingandrew
Spam Capture
“Truthiness”
Australian Political Parties and social media: uses and attitudes
Australian Political Parties and social media: uses and attitudes
Australian Political Parties and social media: uses and attitudes
Australian Political Parties and social media: uses and attitudes

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Australian Political Parties and social media: uses and attitudes

  • 1. Authentic title: Credible, yet human sounding subtitle Authoritative Rank with an everyperson touch Engagement | Additional Engagement
  • 2. Australian Political Parties and social media: uses and attitudes Dr Stephen Dann, ANU @stephendann | @drstephendann
  • 3. Perhaps the only moment of silence the hashtag gets today…
  • 4. Context • Social media use in Australia by political parties • Suddenly, Senate Re-Election • The second most fun data collection event ever • 77 candidates • 31 Twitter handles • 27 active(ish) Twitter users • 20 weeks of data • 1 very sad state of affairs.
  • 5. The Spoiler It’s not authentic communication
  • 6. The Method • Content Analysis • Public Timelines • Secondary Data • 20 week capture period • 10 weeks prior to the election • 10 weeks post election • The Plan • benchmark set of behaviours • Divide into 5 week blocks • Code into Content Classification • Find differences • Elected/Not Elected • Election Period / Reality • Block 1 and Block 4 • Write nifty paper
  • 7. The Framework • Content Categorisation • V.1 Developed in 2009 • Dann (2010) • V.2 Patched in 2011 • Dann (2011) • V.3 • Wheels fell off • V.4 Significant Rebuild • Dann 2014 / Dann 2015 • Principle Idea • All tweets come from one of three options • Original Content for Twitter • Reactions within Twitter • External Content outside of Twitter • Grounded Theory approach • Lit.Rev x Content x Coding • Tweets fit 5 broad categories
  • 8. Five Categories Box Single sentence Conversational Uses an @statement to address another user News Identifiable newsworthy content Pass along Tweets as curation of content Social Presence Messages of connected presence Broadcast Tweets which express the account holder's experiences
  • 9. Oh, and spam Spam Unsolicited content Conversation jacking @responses based on an automated response to a keyword, brand or product mention Trendjacking Spam message containing multiple hashtags and link to a malicious website “Truthiness” multiple identical tweets from different accounts
  • 10. WA Twitter Data (20 weeks) Frequency Percent Valid Percent Cumulative Percent Pass along 3928 54.6 54.6 54.6 Conversational 2773 38.5 38.5 93.1 News 274 3.8 3.8 96.9 Broadcast 190 2.6 2.6 99.5 Social Presence 34 0.5 0.5 100 Total 7199 100 100 27 Candidates. 20 weeks.
  • 11. The Pass-along-a-thon Pass along Tweets as curation of content Curation Posting of third party content for followers via the Twitter URL (t.co) or other URL. #Sydney rally to save #Medicare. #auspol #StopAbbott http://t.co/OWzppqhwIf 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 "I drink Coke because I support their multicultural advertising campaign" this is my new excuse for drinking too much soft drink. Retweets Partial or full reproduction of another tweet (RT retweet or MT modified tweet) RT @PopulationParty: SPP's @Peter_Strachan is glad to have put WA's record population growth on the political agenda http://t.co/niYRjoK8hJ…WAvotes…auspol
  • 12. Conversations Conversational Uses an @statement to address another user Response Classification for tweets which commence with another user’s name and which do not meet the requirements of the referral category @Mark_Butler_MP @margokingston1 Best bang for your buck by far is to reduce population pressure. Referral An @response which contains URLs or recommendation of other Twitter users. (Excludes RT @user) @enviro_al March 1st, Cruelty Free Festival. Subscribe here and I'll email when/if we have more details. http://t.co/hUHWHAzspP Rhetorical Presence Activities involving other Twitter users, or tweets which describe the presence of other Twitter users. I'm voting for @WikiLeaksParty on Saturday. I just added a badge to my profile picture. Please show your support too!
  • 13. Presence of Others versus External Content 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. Election Day Tweeting Conversational News Pass along Status Pirate Party 8 3 9 0 Unnamed Ticket 7 2 60 1 The Greens (WA) 6 4 12 0 #Sustainable Population Party 4 0 8 0 The Nationals 4 2 12 1 Australian Labor Party 3 1 12 0 Liberal 1 0 1 1 Socialist Alliance 1 0 2 0 Voluntary Euthanasia Party 0 0 3 0 Total 34 12 119 3
  • 16. How could we have used Twitter? • Three character opportunities • provision of insight into the candidate, • information for the followers • direct engagement with an audience. • Two message opportunities • Promise management • Embodying the party values
  • 17. Social Presence Messages of connected presence Ceremonial Greetings Tweets where the community is addressed indirectly with a greeting Fourth wall Textual equivalent of comments made directly to camera to an imagined audience Self-referential “Note to self” “FYI” or “Just for the record” - thought bubble style comments Unclassifiable Cat-on-keyboard input and pocket tweeting Broadcast Tweets which express the account holder's experiences Action The diary of daily life tweets which answer “What are you doing?” Reflective “What am I thinking?” or “What am I feeling?” Experience “What am I experiencing?” Broadcast Statement “What am I wanting the world to know?” and “What are my thoughts on a topic?”
  • 18. Adapting the Hughes and Dann (2007) Kevin07 Lessons • Importance of a political product • Technically impressive Twitter stream is no substitute for acceptable policy • Political communications travel • headline delivery – plug Twitter into journalists. • Social costs of public support are an electoral factor • Twitter is seen and felt to be visible • Voter loyalty cannot be assumed or presumed • Followers are not votes • Candidates require offline support
  • 19. The Winner’s Circle (Election Week) Candidate Conversational News Pass along Social Presence Broadcast *lindareynoldswa 0 0 6 0 1 7 *SenatorCash 22 1 31 0 0 54 *SenatorLudlam 128 16 178 0 4 326 This was quite depressing.
  • 20. Twitter and Elections • More promise than reality • Potential is not apparently self evident • May become the worst possible platform for politics-as-usual • Social media as the insider platform… sort of.
  • 21. Livetweeting the conference You don't hear the phrase "we had a dance in Yackandandah" enough in presentations. #CMPM2014
  • 22. Key Metrics: Day 1 • 24 Voices • usual power law distributions Frequency Percent Conversational 25 8.8 News 104 36.7 Pass along 87 30.7 Social Presence 5 1.8 Status Broadcast 58 20.5 Spam 4 1.4 Total 283 100.00.00 0.20 0.40 0.60 0.80 1.00 1.20 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Ratio
  • 23. Key Metrics 2 Twitter Frequency drstephendann 131 stephendann 35 Elias_Hallaj 23 mikesmithqld 22 edwinat 20 JR_Rayner 17 marketingandrew 14 • Livecaster • drstephendann – play by play • stephendann - colour commentary • Commentary Team • Elias_Hallaj • mikesmithqld • edwinat • JR_Rayner • marketingandrew