Affordance Use Differences Between Personal and Professional Scholarly Tweets

Timothy D. Bowman, Ph.D. Candidate | 2014 ASIST SIG/MET Workshop, Seattle, WA, USA

CRC.EBSI.UMONTREAL.CA

WHAT ARE AFFORDANCES?

• affordance - derived from afford,

meaning to make available or provide

naturally (Merriam-Webster, n.d.)

• Gibson (1977) affordance is the

perception of functional attributes of

objects by an agent in its environment

• affordances can vary depending both

on the context (time & space) they are

observed and by the agent doing the

observing

Figure 5: Tree affordance to bird, person, monkey,

and squirrel


AFFORDANCES AND SOCIAL MEDIA

• groups gain experience in digital contexts with

affordances and norms develop that enable interaction

(Bradner, 1999)

• feedback loop of personal and social use of affordances

creates consistent behaviors (Chalmers, 2004)

• interaction is moving from space-time constraints to

affordance-based constraints (Hogan, 2008)

• architecture of a particular environment matters; social

media architecture is shaped by their affordances (boyd,

2010)


WHY CONSIDER “ALTMETRICS” OR “INFLUMETRICS” OR SIMPLY

“SOCIAL MEDIA METRICS”?

- “Altmetrics” is the measure of scholarly communication and

dissemination within social media contexts (Priem & Hemminger,

2010; Priem, Taraborelli, Groth & Neylon, 2010)

- Perhaps a better term is Influmetrics (Rousseau & Ye, 2013) or

simply “social media metrics”?

- Social media indicators may measure immediate assessment of

academic impact and social impact (Thelwall, Haustein, Larivière

& Sugimoto, 2013)

- “Products,” not “publications” (Piwowar, 2013)


AFFORDANCES IN TWITTER

Twitter claims over 200 million active users who create over

400 million tweets each day (Wickre, 2013);

The four widely known affordances in Twitter are:

• @ mention– used to mention, direct messages at, and/or to

reply to user(s)

• # hashtag – used to contextualize or categorize the message

• URL link – used to connect tweet to another information

source

• ReTweet (RT) – used to resend another's tweet


SCHOLARS USING TWITTER

- 43% scholars at 2012 STI Conference used

Twitter; it was used privately and professionally,

to distribute professional information, and to

improve visibility (Haustein et al., 2013)

- 80% DH scholars ranked Twitter as relevant for

consumption and 73% for dissemination of DH

information (Bowman et al., 2013)

- differences by discipline found regarding the

way scholars used Twitter (Holmberg &

Thelwall, 2014)


RESEARCH QUESTIONS

1. Which affordances are scholars using?

2. Do personal or professional tweets vary

regarding affordance use?

3. To what extent do scholars use

affordances?

4. Does Twitter activity influence

affordance use?


PHASE ONE: SURVEY

- 16,862 scholars - associate, assistant, and full professors

from 62 AAU-member universities

- in physics, biology, chemistry, computer science, philosophy,

English, sociology, or anthropology departments

- 60 of the 62 universities rank in top 125 of 2014 CWTS Leiden

Ranking

- survey sent January and February 2014 with a response rate

of 8.5%

- 32% (613) reported having at least one Twitter account

- 289,934 tweets of 585,879 from 445 Twitter accounts (391

scholars) were found and harvested

PHASE ONE: 1,910 RESPONDENTS W/TWITTER ACCOUNT ARE:

33%29%

40%

25%29%

50%

28%

0%

10%

20%

30%

40%

50%

60%

AmericanIndian /Native

American(n=6)

Asian(n=79)

Black /African

American(n=52)

Hispanic /Latino(n=40)

White /Caucasian(n=1580)

PacificIslander

(n=2)

Other(n=50)

by ETHNICITY

38%

45%

38%34% 36%

30%27%

20%16%

5%2%

0%

10%

20%

30%

40%

50%

By SCHOLAR AGE

28% 28%

37% 37%

21%

50%

29%24%

0%

10%

20%

30%

40%

50%

60%

by ACADEMIC DEPT

43%

36%39%

41%

25%

40%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Less than 1Year (n=68)

1 to 3 Years(n=151)

4 to 6 Years(n=144)

6 to 9 Years(n=196)

10 Years ofMore

(n=1262)

NotAcademic

(n=5)

by ACADEMIC AGE

5%10% 10%

15%

59%

Less than1 Year

1 to 3Years

4 to 6Years

6 to 9Years

10 Yearsof More

PHASE ONE: WHO MAKES UP THE 613 ACCOUNT HOLDERS?

7%

15%

5%

24%

17%

6%

10%

15%

Anthropology (n=49)Biology (n=101)Chemistry (n=35)Computer Science (n=160)

42%

22%35% 28%

19%

55%44%

25%

33%

49%39%

37% 60%

21%25%

41%

24% 29% 26%34%

22% 24% 31% 34%

Personal Both Professional

by ACADEMIC DEPTby PROFESSIONAL TITLE

by ACADEMIC AGE

SELF-REPORT

29% 29%

42%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

AssistantProfessor

AssociateProfessor

Professor

PHASE ONE: MEAN TPD OF 391 SCHOLARS

1.06

0.53

1.96

1.41

0.670.52

0.73

1.18

by DEPARTMENTby GENDER

0.80

1.02

Other Female Male

N=232

SD=2.3

N=122

SD=2.1

N=3

0.89

1.11

1.39

0.670.85

I'm Not 10 Yearsor More

7 to 9Years

4 to 6Years

1 to 3Years

Lessthan 1Year

by ACADEMIC AGE

N=2N=207

SD=2.4

N=53

SD=2.2

N=35

SD=2.6

N=39

SD=0.9

N=21

SD=1.1

0.92

0.98

1.03

Professor AssociateProfessor

AssistantProfessor

by PROFESSIONAL TITLE

N=116

SD=2.1

N=116

SD=1.7

N=156

SD=2.9


PHASE TWO: CATEGORIZATION IN AMT

- scholars were divided into 10 groups based on their mean TPD

- stratified sample of 75,000 tweets from these 10 groups

- six random tweets were combined with a control question for a total of

12,056 AMT HITs

- three turkers were asked to categorize each tweet as either:

Personal for example using incomplete thoughts/sentences, profanity, everyday

events/language, personal opinions, excessive punctuation, informal

Professional for example using academic/scientific/business language or subjects,

correct punctuation, mention job title, referencing professional

organization, formal

Unknown from the text it is impossible to categorize as personal or professional

Non-English the text is not written in English

GROUP 1: 0 < 0.5 | GROUP 2: 0.5 < 1 | GROUP 3: 1 < 1.5 | GROUP 4: 1.5 < 2 | GROUP 5: 2 < 2.5

GROUP 6: 2.5 < 3 | GROUP 7: 3 < 4 | GROUP 8: 4 < 5 | GROUP 9: 5 < 8 | GROUP 10: > 8

PHASE TWO: PERSONAL TWEETS CORRELATION TABLE

PHASE TWO: PROFESSIONAL TWEETS CORRELATION TABLE

PHASE TWO: PERSONAL & PROFESSIONAL TWEETS WITH AFFORDANCES

67%

15% 17% 17%

56%

69%

28%

37%

0%

10%

20%

30%

40%

50%

60%

70%

Mentions URLs Hashtags Retweets

Personal Tweets Professional Tweets

AGREEMENT (3/3)

65%

38%

24%

30%

61% 62%

27%

38%

0%

10%

20%

30%

40%

50%

60%

70%


Personal Professional

PARTIAL AGREEMENT (2/3)

66%

23%20% 22%

59%65%

28%

38%

0%

10%

20%

30%

40%

50%

60%

70%



AGREEMENT + PARTIALAGREEMENT

Personal Tweets: 27,264

Professional Tweets: 6,810

PARTIAL AGREEMENT



DISAGREEMENT

Personal Tweets: 942

Professional Tweets: 833

PHASE TWO: FREQUENCY OF AFFORDANCES USED IN PERSONAL & PROFESSIONAL TWEETS

1.38

1.02

1.291.43

1.03

1.46

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

Mentions URLs Hashtags


1.48

1.03

1.401.45

1.03

1.47

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60



1.41

1.03

1.341.44

1.03

1.47

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60



AGREEMENT (3/3)PARTIAL AGREEMENT (2/3)

AGREEMENT + PARTIAL AGREEMENT



PARTIAL AGREEMENT



DISAGREEMENT

Personal Tweets: 942

Professional Tweets: 833

PHASE TWO: FREQUENCY OF AFFORDANCE USE BY IV GROUP

0

0.1

0.2

0.3

0.4

0.5

0.6

1 2 3 4 5 6 7 8 9 10

Hashtags

Personal

Professional

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 2 3 4 5 6 7 8 9 10

URLs

Personal

Professional

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1 2 3 4 5 6 7 8 9 10

User Mentions

Personal

Professional

13%

11%

15%

7%8% 8% 8% 8%

9%

15%

22%

10%

17%

9%8%

9%

7%5%

9%

5%

0%

5%

10%

15%

20%

25%

1 2 3 4 5 6 7 8 9 10

% Retweets

Personal

Professional

GROUP 1: 0 < 0.5 | GROUP 2: 0.5 < 1 | GROUP 3: 1 < 1.5 | GROUP 4: 1.5 < 2 | GROUP 5: 2 < 2.5

GROUP 6: 2.5 < 3 | GROUP 7: 3 < 4 | GROUP 8: 4 < 5 | GROUP 9: 5 < 8 | GROUP 10: > 8

PHASE TWO: FREQUENCY OF AFFORDANCE USE BY IV GENDER

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

Female Male

Hashtags

Professional

Personal

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Female Male

URLs

Professional

Personal

0.7

0.75

0.8

0.85

0.9

0.95

Female Male

User Mentions

Professional

Personal

23%

68%

23%

66%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Female Male

% Retweets

Personal

Professional

PHASE TWO: FREQUENCY OF AFFORDANCE USE BY IV DEPARTMENT

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

Hashtags

Personal

Professional 0.000.100.200.300.400.500.600.700.800.901.00

URLs

Personal

Professional

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

User Mentions

Personal

Professional

7%

11%

2%

18%

33%

7% 7%

14%

5%

20%

2%

23%20%

5%7%

17%

0%5%

10%15%

20%25%30%35%

40%

% Retweets

Personal

Professional


SUMMARY

• scholars are making use of all the primary affordances of Twitter and there does seem to be

consistency in their practices

• gender, department affiliation, communication type, and time spent on Twitter seems to have a

small impact on affordance use

• URL use is different in personal and professional tweets; there are many more professional

tweets with URLs, but the frequency of URLs used is similar between personal and professional

tweets

• #hashtag use shows variation by department for both personal and professional tweets;

• #hashtag use shows an upward trend as tweet activity increases for professional tweets and a

downward trend for personal tweets as tweet activity increases;

• #hashtag use shows variation by department for both personal and professional tweets;

• #hashtag use shows an upward trend as tweet activity increases for professional tweets and a

downward trend for personal tweets as tweet activity increases;

• @user mentions vary by gender with males using much less mentions in professional tweets

than females

• @user mentions vary by gender with males using much less mentions in professional tweets

than females


ONGOING WORK

• validity for tweet categorization is being checked currently by

surveying 90 most active scholars using Twitter and asking

them to self-categorize their own tweets

• using linguistic tools, the text of 289,934 tweets will be used to

compare terms used in tweets with scholar’s article titles at the

level of the scholar and discipline

• social network analysis using mentions at the scholarly and

discipline levels

• analysis of particular affordance usage


THANK YOU FOR LISTENING

QUESTIONS?

REFERENCESBradner, E., Kellogg, W., & Erickson, T. (1999). The Adoption and Use

of “BABBLE”: A Field Study of Chat in the Workplace. In ECSCW’99

(pp. 12–16). Copenhagen, Denmark: Kluwer Academic Publishers.

Retrieved from http://link.springer.com/chapter/10.1007/978-94-011-

4441-4_8

Bowman, T. D., Demarest, B., Weingart, S. B., Simpson, G. L.,

Lariviere, V., Thelwall, M., & Sugimoto, C. R. (2013). Mapping DH

through heterogeneous communicative practices. In Digital

Humanities 2013. Lincoln, NE.

danah boyd. (2010). "Social Network Sites as Networked Publics:

Affordances, Dynamics, and Implications." In Networked Self: Identity,

Community, and Culture on Social Network Sites (ed. Zizi

Papacharissi), pp. 39-58.

Chalmers, M. (2004). A Historical View of Context. Computer

Supported Cooperative Work (CSCW), 13(3-4), 223–247.

doi:10.1007/s10606-004-2802-8

Gibson, J. J. (1977). The Theory of Affordances. In R. Shaw & J.

Bransford (Eds.), Perceiving, Acting, and Knowing: Toward an

Ecological Psychology (pp. 127–143). Lawrence Erlbaum.

Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Shema, H., &

Terliesner, J. (2013). Coverage and adoption of altmetrics sources in

the bibliometric community. arXiv, 1–12. Digital Libraries. Retrieved

from http://arxiv.org/abs/1304.7300

Holmberg, K., & Thelwall, M. (2014). Disciplinary differences in Twitter

scholarly communication. Scientometrics. doi:10.1007/s11192-014-

1229-3

Letierce, J., Passant, A., Decker, S., & Breslin, J. G. (2010).

Understanding how Twitter is used to spread scientific messages. In

Web Science Conference. Raleigh, NC.

Merriam-Webster. (n.d.). Afford- Definition and More from the Free

Merriam-Webster Dictionary. In Free Merriam-Webster Dictionary.

Merriam-Webster: An Encyclopedia Britannica Company. Retrieved

from http://www.merriam-webster.com/dictionary/afford

Moran, M., Seaman, J., & Tinti-Kane, H. (2011). Teaching, learning,

and sharing: How today’s higher education faculty use social media.

Piwowar, H. (2013). Altmetrics: Value all research products. Nature,

493(159). doi:10.1038/493159a

Priem J., & Hemminger B.M. (2010) Scientometrics 2.0: Toward new

metrics of scholarly impact on the social web. First Monday 15.

Available:

http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2

874/257. Accessed 2011 December 7.

Priem, J., Taraborelli, D., Groth, P., Neylon, C. Alt-metrics: a

manifesto. 2010. Available from http://altmetrics.org/manifesto/

Priem, J. (2014). Altmetrics. In B. Cronin & C. R. Sugimoto (Eds.),

Beyond bibliometrics: Harnessing multidimensional indicators of

scholarly impact (pp. 263–288). Cambridge, Mass.: MIT Press.

Rousseau, R., & Ye, F. (2013). A multi-metric approach for research

evaluation. Chinese Science Bulletin, 58(3290), 1–7.

doi:10.1007/s11434-013-5939-3

Thelwall M., Haustein S., Larivière V., Sugimoto, C.R. (2013) Do

Altmetrics Work? Twitter and Ten Other Social Web Services. PLoS

ONE 8(5): e64841. doi:10.1371/journal.pone.0064841

Wickre, K. (2013, March 21). Celebrating #Twitter7. Retrieved

September 01, 2013, from https://blog.twitter.com/2013/celebrating-

twitter7

http://arxiv.org/abs/1304.7300


APPENDIX: 62 AAU-MEMBER UNIVERSITIES

Boston University, Brandeis University, Brown University, California Institute of Technology, Carnegie Mellon University, Case Western Reserve University, Columbia University, Cornell, Duke University, Emory University, Georgia Institute of Technology, Harvard, Indiana University, Iowa State, Johns Hopkins, McGill, Michigan State University, MIT, New York University, Northwestern, Princeton University, Purdue University, Rice University, Rutgers, The State University of New Jersey, Stanford University, Stony Brook University-State University of New York, Texas A&M University, The Ohio State University, The Pennsylvania State University, The University of Chicago, Tulane University, University at Buffalo, The State University of New York, University of Arizona, University of California, Berkeley, University of

California, Davis, University of California, Irvine, University of California, Los Angeles, University of California, San Diego, and University of California, Santa Barbara ,The University of Iowa, The University of Kansas, The University of North Carolina at Chapel Hill, The University of Texas at Austin, The University of Wisconsin-Madison, University of Colorado Boulder, University of Florida, University of Illinois at Urbana-Champaign, University of Maryland, University of Michigan, University of Minnesota, University of Missouri-Columbia, University of Oregon, University of Pennsylvania, University of Pittsburgh, University of Rochester, University of Southern California, University of Toronto, University of Virginia, University of Washington, Vanderbilt University, Washington University in St. Louis, Yale University

APPENDIX: 10 GROUPS OF TWEETERS

Group Name Mean Tweets/Day Total Tweets Percentage Required Member Totals

TEN 8 to 24 29,064 10.02% 9

NINE 5 to 8 25,863 8.92% 8

EIGHT 4 to 5 19,321 6.66% 6

SEVEN 3 to 4 24,532 8.46% 10

SIX 2.5 to 3 25,508 8.80% 10

FIVE 2 to 2.5 22,195 7.66% 10

FOUR 1.5 to 2 23,018 7.94% 13

THREE 1 to 1.5 43,831 15.12% 29

TWO 0.5 to 1 30,463 10.51% 33

ONE < 0.5 46,139 15.91% 317

289,934 100.00% = 75,000 445

APPENDIX:

DESIGN OF

AMT HIT

Affordance Use Differences Between Personal and Professional Scholarly Tweets

Education