Investigating the Use of Affordances and Framing

Techniques by Scholars to Manage Personal and Professional

Impressions on TwitterTimothy D. Bowman, Ph.D. Candidate, Indiana

UniversityResearch Professional, Université de Montréal

MO

TIVA

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LTS

MOTIVATION

CONTROLLING IMPRESSIONS

CONTROLLING IMPRESSIONS

CENSO

RED

SUSP

ENDED

RESCIN

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• Twitter use is increasing (Brenner & Smith, 2013)

• Around 10% of scholars on Twitter with variation by field(Ponte & Simon, 2011; Rowlands et al., 2011)

• 20% of scientific articles shared on Twitter (Haustein et al., 2014; Holmberg and Thelwall, 2014).

TWITTER

Brenner & Smith, 2013

• Few people examining impression management of scholars in Twitter

• Studies of scholars tend to focus on social media in the classroom or on scholarly output (altmetrics)

• Populations of scholars on Twitter tend to be limited

LITERATURE GAP

THEORIES & QUESTIONS

The Presentation of Self in Everyday Life (Goffman, 1959)

PRESENTATION OF SELF

BACKSTAGEINFORMAL

TALKRELAXED

ROLE

BARRIER

GIVE OFFGIVE

DRAMATIC INTERACTION

FRONT STAGE

SIGNS

PROPSBARRIER

IMPRESSIONMANAGEMENTExpressing certain information in order to impress certain ideas upon an audience during social interaction

Frame Analysis: An Essay on the Organization of Experience (Goffman, 1974)

FRAME ANALYSIS

FRAME RIM

PRIMARY FRAME

KEYING

FABRICATION

SIGNS/SYMBOLS

BRACKETS

ROLES

EXPERIENCE

ENGROSSABLES

The Theory of Affordances. (Gibson, 1977)

AFFORDANCE

CONTEXT

SOCIAL RULES

EXPERIENCE

PERCEPTION

1. In what ways do scholars utilize affordances to manage impressions on Twitter?

2. In what ways do scholars frame interactions to manage impressions on Twitter?

3. What are the differences in the use of framing strategies and affordances by scholars for managing the presentation of their professional and personal selves on Twitter?

RESEARCH QUESTIONS

METHODS & RESULTS

Phase One Online survey of full, associate, & assistant professors

Phase Two Tweet categorization in Amazon’s Mechanical Turk (AMT)

Phase Three Follow-up survey and tweet categorization withmost active professors on Twitter

RESEARCH METHODS

• 62 Association of American Universities (AAU) Member Schools (2 Canadian)

• 16,862 Full, Associate, and Assistant Professors

• 8 Departments – Anthropology, Biology, Chemistry, Computer Science, English, Philosophy, Physics, and Sociology

PHASE ONE: SAMPLING

• 19 questions

• Five sections

• Matrix questions

• Likert-scale questions

• 8.5% response rate

PHASE ONE: INSTRUMENT

χ2 (7, n=1,910) = 0.182, p = .0005, Cramér’s V = 0.182

PHASE ONE: TWITTER USE

Computer ScienceEnglish

SociologyAnthropology

BiologyPhilosophy

PhysicsChemistry

50.0%37.5%36.9%

29.0%27.5%27.1%

24.3%20.7%

68% 32%

NO YES

(n=613)(n=1,297)

(n=224)

(n=299)

(n=271)

(n=169)

(n=367)

(n=144)

(n=267)

(n=169)

(N=1,910)

(N=1,910)

Non-White

White

45%

41%

PHASE ONE: TWITTER USE

Male

Female

38%

49%(n=615)

(n=1,200)

6 Years or Less

7 to 9 Years

10 Years or More

39%

41%

25%(n=1,262)

(n=196)

(n=363) 35 and Under

36 to 45

46 to 60

61 and Over

44%

36%

28%

11%(n=271)

(n=841)

(n=517)

(n=194)

(n=229)

(n=1,580)

χ2 (2, n=1,821) = 0.217, p = .0005, Cramér’s V = 0.217) χ2 (3, n=1,823) = 0.125, p = .0005, Cramér’s V = 0.125.

χ 2 (2, n=1,824) = 0.066, p = .018, Cramer’s V = 0.18

PHASE ONE: SOCIAL MEDIA USE

ScilinkEpernicus

BioMedExperts.comMySpace

ScribdSlideShare

TumblrOther

BloggerPinterest

MendeleyInstagramWordPressWikipedia

Academia.eduResearchGate

YouTubeTwitter

Google+LinkedIn

Facebook

0.4%0.7%0.9%2.0%2.7%2.9%

4.8%5.2%5.7%7.2%7.3%7.4%

15.4%16.7%

21.5%26.2%27.8%

32.0%50.2%

57.8%69.9%(N=1,63

9)

Professor (n=253)

Associate (n=177)

Assistant (n=178)

42%

29%

29%

PHASE ONE: TWITTER USERS

English

Computer Science

Biology

Sociology

Physics

Anthropology

Philosophy

Chemistry

18.3%

18.3%

16.5%

16.3%

10.6%

8.0%

6.0%

6.0%

(n=112)

(n=112)

(n=101)

(n=100)

(n=65)

(n=49)

(n=39)

(n=35)

PHASE ONE: TWITTER USERS

< 1 year

1 to 2 years

2 to 3 years

3 to 4 years

4 to 5 years

5 to 6 years

> 6 years

22%

28%

21%

15%

6%

3%

5%

Male

Female

62%

37%

29%

42%

29%

PHASE ONE: ACCOUNT TYPE

BOTH PROFESSIONALPERSONAL

PHASE ONE: ACCOUNT TYPE

Philosophy (n=33)Biology (n=93)

English (n=102)Sociology (n=88)Chemistry (n=31)

Computer Science (n=102)Anthropology (n=45)

Physics (n=59)

55%22%19%25%

35%28%

42%44%

21%49%60%

41%39%

37%33%

25%

24%29%

22%34%

26%34%

24%31%

PersonalBothProfessional

PHASE ONE: AFFORDANCE USE

Add PhotoAdd Location

Address Message AtMention Someone

Use HashtagsEmbed URLs

Delete a tweetFavorite a tweetReply to a tweetRetweet a tweet

19%5%5%

29%26%

34%34%26%

34%27%

80%94%93%

68%68%

58%58%

61%53%48%

3%6%8%8%13%14%

25%

Mostly or Always Sometimes Rare or Never

PHASE ONE: AFFORDANCE USE

Profile PictureBio information

Apps Allowed Access to TwitterPrivacy SettingsHeader Picture

Twitter Sends EmailLanguage Specified

Twitter Connected to FacebookCountry

Time ZoneTheme

Geo TaggingTwitter Sends Text MessagesTwitter Personalizes Interface

Widget(s) CreatedPhone Number Specified

Sleep Settings

60.3%52.1%

43.3%40.8%

38.0%24.9%24.6%23.5%22.9%

19.8%14.4%

8.2%6.8%5.1%4.8%

2.5%1.7%

87.3% 87.3%

16.2%

PHASE ONE: FINDINGS

• Age, academic age, department, and gender associated with having Twitter account

• The majority of professors indicated using their Twitter account for both personal and professional communications

• There were differences in perceived affordance use

Phase One Online survey of full, associate, & assistant professors

Phase Two Tweet categorization in Amazon’s Mechanical Turk (AMT)

Phase Three Follow-up survey and tweet categorization withmost active professors on Twitter

RESEARCH METHODS

• 445 Twitter accounts

• 289,934 tweets collected

• 75,000 tweets in AMT

PHASE TWO: DATA COLLECTION

PHASE TWO: DATA COLLECTION

Group Name Average Tweets

per Day (TPD)Total Scholars

in GroupTotal Tweets

CollectedPercentage of

Total TweetsTweets Used

in AMTTEN

(intense) 8 to 24 9 29,064 10.02% 7,518

NINE 5 to 8 8 25,863 8.92% 6,690EIGHT 4 to 5 6 19,321 6.66% 4,998SEVEN 3 to 4 10 24,532 8.46% 6,346

SIX 2.5 to 3 10 25,508 8.80% 6,598FIVE 2 to 2.5 10 22,195 7.66% 5,741FOUR 1.5 to 2 13 23,018 7.94% 5,954THREE 1 to 1.5 29 43,831 15.12% 11,338TWO 0.5 to 1 33 30,463 10.51% 7,880ONE

(infrequent) < 0.5 317 46,139 15.91% 11,935

  445 289,934 100.00% *75,000

*Confidence Interval 0.4 at 99% Confidence Level

0.0

5.0

10.0

15.0

20.0

25.0

• 12,056 Human Intelligence Tasks (HIT)

• 7 tweets per HIT

• 1 control question per HIT

• 3 Turkers per HIT

PHASE TWO: INSTRUMENT

Anthro Bio Che

mComp

Sci Eng Philo Phys Soc Average

HASHTAGS 4.4% 5.5% 5.2% 5.2% 4.9% 4.6% 6.4% 7.4% 5.5%

URLs 0.7% 1.2% 0.3% 1.1% 0.5% 1.7% 0.8% 1.1% 0.9%

MENTIONS 11.6% 16.3% 12.9% 9.2% 13.4% 10.6% 13% 20% 13.4%

RETWEETS 241 273 137 244 291 171 124 205 211

PHASE TWO: AFFORDANCES

Philosophy

English

Anthropology

Sociology

Biology

Computer Science

Physics

Chemistry

1.96

1.41

1.18

1.06

0.73

0.67

0.53

0.52Female Male

0.801.02

PHASE TWO: TWEET ANALYSIS

Mean tweets per day

PHASE TWO: AMT RESULTS

PERSONAL

PROFESSIONAL

UNKNOWN

NON-ENGLISH TOTAL

Full Agreement (3/3) 27,264 6,810 129 766 34,969

(47%)Partial Agreement (2/3)

19,403 15,692 1,993 262 37,355 (49%)

No Agreement 2,674 (4%)96% agreement for 2 out of 3 Turkers on all tweets

Hashtags URLs User Mentions Retweets

17% 15%

67%

17%28%

69%

56%

36%

Personal Professional

χ 2 (1, n=34,074) = 0.187, p = 0.0005, Cramer’s V = 0.187

χ 2 (1, n=34,074) = -0.089, p = 0.0005, Cramer’s V = 0.089 χ 2 (1, n=34,074) = 0.491, p = 0.0005, Cramer’s

V = 0.491

χ 2 (1, n=34,074) = 0.112, p = 0.0005, Cramer’s V = 0.112

PHASE TWO: AMT RESULTS

PHASE TWO: FINDINGS

• URLs, retweets, and hashtags occurred more often in professional tweets

• User mention was the only affordance to occur more in personal tweets

• There were also differences across personal and professional tweets by academic title, age, gender, department and Twitter activity

Phase One Online survey of full, associate, & assistant professors

Phase Two Tweet categorization in Amazon’s Mechanical Turk (AMT)

Phase Three Follow-up survey and tweet categorization withmost active professors on Twitter

RESEARCH METHODS

• 95 Most Active Scholars on Twitter

• 5 Tweets to Categorize – 2 Personal, 3 Professional

PHASE THREE: DATA COLLECTION

• 6 questions

• 5 tweets: 2 Personal, 3 Professional

PHASE THREE: INSTRUMENT

PHASE THREE: AFFORDANCE USE

Mentions URLs

Retweets Hashtags

Directed messages Punctuation, caps, etc.

MediaEmoticons

OtherNot used in this way

54.2%42.4%

44.1%42.4%

54.2%32.2%

55.9%30.5%

5.1%10.2%

84.7%84.7%

79.7%78.0%

61.0%61.0%

54.2%13.6%

6.8%3.4%

Professional Personal

PHASE THREE: AFFORDANCE USE

Description

Profile Image

Theme

Header (banner) Image

Location

Colors

Other

Not used in this way

25%

21%

6%

13%

8%

6%

2%

19%

77%

60%

32%

30%

23%

17%

11%

11%

Professional Personal

PHASE THREE: TWEET CATEGORIZATION

PERSONAL PROFESSIONAL TOTAL AGREEMENT

TURKERS (3/3) 102 153 255SCHOLAR 44 125 169

43% Agreement

82% Agreement 69% Agreement

OBSERVED TURKERS EXPECTED TURKERS

Personal

Professional

Personal

Professional

Personal 44 28 Personal 29 43Professional

58 125 Professional

73 110

Cohen’s Kappa = 0.26

Turker and Scholar Agreement

Turker and Scholar Coding: Cohen’s Kappa

PROF

ESSO

R

PROF

ESSO

R

TURKER: PersonalPROFESSOR: Professional

TURKER: ProfessionalPROFESSOR: Personal

INCORRECTLY CATEGORIZED TWEETS

CORRECTLY CATEGORIZED TWEET

TURKER: ProfessionalPROFESSOR: Professional

#citsci What motivates you to take part in @the_zooniverse or citizen science projects. Help us find out!. http://t.co/2tth5RVpmN

TURKER: PersonalPROFESSOR: Personal @k_garten @bashartak @sig_chi we should just

form CHI University and all hang out together all the time. #chi2013

PHASE THREE: FINDINGS

• It is difficult for audience members to distinguish between personal and professional tweets

• The framing of tweets are associated with specific affordances

• Professional tweets are perceived as containing more hashtags, URLs and are retweets

• Personal tweets are perceived as containing more user mentions

IMPLICATIONS & CONCLUSION

PERSONAL

PROFESSIONAL

SOCO-TECHNICAL FRAMEWORK

•Sample Population•Survey Response Rate/Design•Low Cohen’s Kappa

LIMITATIONS

• Distinguishing between personal and professional tweets is difficult• Framing of tweets by audience members depends on many

factors, one of which may be affordances• There are differences in tweeting behavior by various demographic

characteristics• One of the largest studies on U.S. professors on Twitter to date• Unique use of Amazon’s Mechanical Turk• Provides foundation for altmetrics research• Social media use is a hot topic

SUMMARY

1.Analyze events in online social media

2.Utilize theories and methods from multiple disciplines

3.Use quantitative and qualitative methods

FUTURE DIRECTION

Thank You

Timothy D. Bowman, Ph.D. Candidate, Indiana UniversityResearch Professional, Université de Montréal