Communities of attention around journal papersWho is tweeting about scientific publications?Stefanie Haustein, Timothy D. Bowman & Rodrigo Costas@stefhaustein @timothydbowman @RodrigoCostas1

Outline

• IntroductionBibliometrics and altmetrics

• BackgroundTwitter in scholarly communication

• Research Questions and Objectives

• Methods

• Preliminary Results

• Outlook

Introduction: altmetrics• alternative use and visibility of publications

on social media:

more traditional forms of use:

• alternative forms of research output

“study and use of scholarly impact measures based on activity in online tools and environments”

“a good idea but a bad name”

…

…

…

Priem (2014, p. 266)

Rousseau & Ye (2013, p. 3289)

Introduction: bibliometrics

Introduction: altmetrics

Background• social media activity around scholarly articles grows

5% to 10% per month

• Mendeley and Twitter largest sources for mentions of scholarly documents

• Twitter• used by ca. 10% of researchers in a professional context

• 22% of Web of Science journal papers published in 2012

• number of tweets per paper highly skewed

• low correlations with citations

• popularity of humorous and curious topics

• automated diffusion of scientific papers on Twitter

Adie & Roe (2013)

Costas, Zahedi & Wouters (2015)

Haustein, Costas & Larivière (2015)

Haustein, Costas & Larivière (2015)

Rowlands, Nicholas, Russell, Canty, & Watkinson (2011)

Research questions and objectives

• What information about tweeting behavior can be used to distinguish different kinds of Twitter impact of journal articles?

• Who is diffusing scientific journal articles on Twitter?

• What user groups can be distinguished:• regarding engagement with papers and• potential reach and audiences of users?

• How does the tweeting behavior of these user groups differ?

Research questions and objectives• distinguishing between:

exposure = number of followersengagement = dissimilarity between tweet and paper title

Methods• 660,149 original tweets (Altmetric.com up to June 2014)

• 237,222 tweeted documents (WoS 2012 with DOI)

• 125,083 unique users• number of tweets to 2012 papers

• mean tweets per day (all tweets up to April 2015)

• mean relative citation rate of tweeted papers

• mean engagement (dissimilarity between tweet and paper title)

• mean exposure (mean number of followers during tweet)

• mean number of followers (April 2015)

• mean number of following (April 2015)

• tweeted document coupling user network

Methods

exposure

enga

gem

ent

median dissimilarity with paper title

med

ian

num

ber

of f

ollo

wer

s

influencers / brokers

orators / discussing

disseminators / mumblers

broadcasters

tweet text differs from paper title

tweet text is identical to paper title

few followers many followers

Preliminary results

number of users N = 125,083mean tweets to papers tp = 5.3mean tweets per daytpd = 5.9mean relative citation rate mncs = 2.3mean engagement men = 53.3mean exposure mex = 1,382.6mean number of followers mnfers= 2,027.2mean number of following mnfing= 855.6

exposure

enga

gem

ent

N = 29,770tp = 3.2tpd = 10.1mncs = 2.4men = 74.2mex = 2,876.9mnfers= 4,177.3mnfing = 1,327.1

N = 32,768tp = 1.7tpd = 1.8mncs = 2.5men = 75.8mex = 82.7mnfers = 191.4mnfing = 259.0

N = 32,680tp = 11.5tpd = 9.4mncs = 2.1men = 32.7mex= 2,511.2mnfers = 3,396.8mnfing = 1,497.3

N = 29,865tp = 4.4tpd = 1.7mncs = 2.2men = 30.3mex = 84.6mnfers = 178.0mnfing = 267.4

Preliminary results

number of users N = 125,083mean tweets to papers tp = 5.3mean tweets per daytpd = 5.9mean relative citation rate mncs = 2.3mean engagement men = 53.3mean exposure mex = 1,382.6mean number of followers mnfers= 2,027.2mean number of following mnfing= 855.6

exposure

enga

gem

ent

N = 29,770tp = 3.2tpd = 10.1mncs = 2.4men = 74.2mex = 2,876.9mnfers= 4,177.3mnfing = 1,327.1

N = 32,768tp = 1.7tpd = 1.8mncs = 2.5men = 75.8mex = 82.7mnfers = 191.4mnfing = 259.0

N = 32,680tp = 11.5tpd = 9.4mncs = 2.1men = 32.7mex= 2,511.2mnfers = 3,396.8mnfing = 1,497.3

N = 29,865tp = 4.4tpd = 1.7mncs = 2.2men = 30.3mex = 84.6mnfers = 178.0mnfing = 267.4

Preliminary results

number of users N = 125,083mean tweets to papers tp = 5.3mean tweets per daytpd = 5.9mean relative citation rate mncs = 2.3mean engagement men = 53.3mean exposure mex = 1,382.6mean number of followers mnfers= 2,027.2mean number of following mnfing= 855.6

exposure

enga

gem

ent

N = 29,770tp = 3.2tpd = 10.1mncs = 2.4men = 74.2mex = 2,876.9mnfers= 4,177.3mnfing = 1,327.1

N = 32,768tp = 1.7tpd = 1.8mncs = 2.5men = 75.8mex = 82.7mnfers = 191.4mnfing = 259.0

N = 32,680tp = 11.5tpd = 9.4mncs = 2.1men = 32.7mex= 2,511.2mnfers = 3,396.8mnfing = 1,497.3

N = 29,865tp = 4.4tpd = 1.7mncs = 2.2men = 30.3mex = 84.6mnfers = 178.0mnfing = 267.4

Preliminary results

9 57

130 512

708 of 125,083 users (0.6%) tweeting WoS papers published in 2012 (>100)Node size represents number of papers

Network of users tweeting the same papers

Preliminary results

708 of 125,083 users (0.6%) tweeting WoS papers published in 2012 (>100)Node size represents number of papers

Network of users tweeting the same papers

Preliminary results

Preliminary results

Preliminary results

Preliminary results

Outlook• Systematic analysis of users in different groups

• Identifying particular differences in tweeting behavior

• Differentiating between various types of impacts of journal articles on Twitter

• Investigating the motivation behind tweeting scientific papers

Improving scholarly metrics

Thank youfor your attention!Stefanie Haustein, Timothy D. Bowman & Rodrigo Costas@stefhaustein @timothydbowman @RodrigoCostas1

http://www.slideshare.net/StefanieHaustein