Your SlideShare is downloading. ×
0
Twitter metrics and measure
Why (more than how to) analyse Twitter

Dr Stephen Dann
School of Management
Marketing & Inter...
Why dissect a living
medium?
Metrics
• What gets measured gets done
• What gets done can be measured
• What gets tweeted can be assembled into little
d...
Why bother?
“Okay, so if we’re going to do it, can it be
done well?”
“No?”
“How about medium rare?”
Coding the Streams
Krishnamurthy et al (2008)
•users were classified by
–follower/following counts,
•Numbers and ratios

–...
Coding the Streams
Java et al 2007
1,348,543 tweets
76,177 users
April 01, to May 30, 2007
Four meta-categories
daily chat...
Analysis 2: The
Quickening
Jansen et al (2009)
• tweets with brand name
• expression of brand sentiment
• 13-week period

...
Analysis 3: Oh, those guys
Pear Analytics (2009)
• 2000 tweets
• 11am to 5pm
• 10 working days

Six part classification
• ...
Where’s the party @?
Honeycutt and Herring (2009)

• four one-hour samples
• four-hour intervals
• 6 a.m. to 6 p.m. Easter...
Categories
Naaman, Boase and Lai (2010)
• Sample of 400 tweets
–more than one category was
assigned to a single message.

...
Tweet, Tweet, Retweet
danah boyd
Scott Golder
Gilad Lotan
Microsoft!
Conversational Aspects of
Retweeting on Twitter
• Pro...
The consistent theme
People keep using Twitter for
personal use.
• Discussions of “self”
• Pointless babble
• Conversation...
What Twitter looks like…

…and how are people using Twitter?

‘Sup?

Twitter – www.twitter.com
Recoding the Platform
Let’s do it my way
Theory and Ideology
Useful versus Enjoyable
Bohme (2006) outlines a propensity of society to
classify technology of all fo...
Why do it?
Twitter is not about the aggregate firehose
Twitter is how you use it.
Analysis: what (twitter history) as an i...
Method
Grounded Theory
• Broad categories based
on / supported by six prior
studies
•Sub categories developed
from theory ...
Categories and Results
Doesn’t scale to the public sphere!
Huzzah!
NO MASS GENERALISATION POSSIBLE!
Major Categories
•

Conversational

•

Status

•

Pass along

•

News

•

Phatic

•

Spam

– Uses an @statement to address...
Minor Categories
Conversational
1. Query
2. Referral
3. Action
4. Response
Status
1. Personal
2. Temporal
3. Location
4. M...
Results - @stephendann
Questions
stephen@stephendann.net
Or
@stephendann
Twitter!
(What is it good for?)

•
•
•
•
•
•
•
•
•
•
•

health community (Berger 2009)
public libraries (Cahill 2009, Cudd...
Uses and usage
• casual listening platform
– Crawford 2009

• creating the illusion of physicality
– Hohl 2009

• sense of...
References
Böhme, G (2006) Technical Gadgetry: Technological Development in the Aesthetic Economy, Thesis Eleven, 86 (1): ...
References
Krishnamurthy, B, Gill, P and Arlitt, M (2008) A Few Chirps About Twitter, WOSN'08, August 18, 2008,
19-24
Lari...
This work is licensed under the Creative Commons Attribution-Share Alike 2.5 Australia License.
To view a copy of this lic...
Twitter presenting2010-100205201247-phpapp02
Upcoming SlideShare
Loading in...5
×

Twitter presenting2010-100205201247-phpapp02

29

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
29
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Transcript of "Twitter presenting2010-100205201247-phpapp02"

  1. 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. 2. Why dissect a living medium?
  3. 3. 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
  4. 4. Why bother? “Okay, so if we’re going to do it, can it be done well?” “No?” “How about medium rare?”
  5. 5. 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
  6. 6. 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
  7. 7. 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
  8. 8. 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%).
  9. 9. 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,
  10. 10. 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)
  11. 11. 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
  12. 12. 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
  13. 13. What Twitter looks like… …and how are people using Twitter? ‘Sup? Twitter – www.twitter.com
  14. 14. Recoding the Platform Let’s do it my way
  15. 15. 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
  16. 16. 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)
  17. 17. 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.
  18. 18. Categories and Results Doesn’t scale to the public sphere! Huzzah! NO MASS GENERALISATION POSSIBLE!
  19. 19. Major Categories • Conversational • Status • Pass along • News • Phatic • Spam – Uses an @statement to address another user – An answer to “What are you doing now?”. – Tweets of endorsement of content – Identifiable news content which is not UGC – Content independent connected presence – Junk traffic, unsolicited automated posts, and other automated tweets generated without user consent
  20. 20. 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
  21. 21. Results - @stephendann
  22. 22. Questions stephen@stephendann.net Or @stephendann
  23. 23. 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).
  24. 24. 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
  25. 25. 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
  26. 26. References Krishnamurthy, B, Gill, P and Arlitt, M (2008) A Few Chirps About Twitter, WOSN'08, August 18, 2008, 19-24 Lariscy, R Avery, E J, Sweetser, K and Howes, P 2009 An examination of the role of online social media in journalists’ source mix, Public Relations Review 35 (2009) 314–316 Macintosh, A 2009, The emergence of digital governance, Significance, December, 176-178 Naaman, M, Boase, J and Lai, C-H (2010) Is it Really About Me? Message Content in Social Awareness Streams, CSCW 2010, February 6–10 Parslow, G, 2009, Commentary: Twitter for Educational Networking, BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION Vol. 37, No. 4, pp. 255–256, 2009 Pear Analytics (2009) Twitter Study – August 2009, http://www.pearanalytics.com/wp-content/uploads/2009/08/Twitter-Study-August-2009.pdf Power, R and Forte, D 2008, War & Peace in Cyberspace: Don’t twitter away your organisation’s secrets, Computer Fraud and Security, August, 18-20 Zhao, D and Rosson, M B, How and Why People Twitter: The Role that Micro-blogging Plays in Informal Communication at Work, GROUP’04, May 10–13, 2009, 243-252
  27. 27. This work is licensed under the Creative Commons Attribution-Share Alike 2.5 Australia License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/2.5/au/
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×