JASIST@Mendeley Revisited Judit Bar-Ilan

Department of Information Science

Bar-Ilan University

Research objectives:

To study:

• Mendeley’s coverage of JASIST articles over time

• Readership counts over time

• Why JASIST?

2

Data collection

• All JASIST articles published between 2001 and 2011 and indexed by Web of Science were retrieved

• Info on a few missing articles was filled in manually

• Missing DOIs were supplied

• Citation data from WOS, Scopus and GS were collected twice, once in 2012 and once in 2014

3

Mendeley searches

• In April 2012 and August 2013 all the searches were conducted manually through the website

• Title searches

• Special characters excluded

• ? “ : & …

• Search results matched against full title and author

• Seemingly wrong publication source was double checked (DOI or abstract)

• Readership counts of multiple records for a given article were combined

4

Mendeley searches (2)

• In 2014 we used Mike Thelwall’s Webometric Analyst (http://lexiurl.wlv.ac.uk/) for title searches

• Carefully compared with manual searches

6

JASIST 2001-2011 • 1645 articles

7

# articles on Mendeley % of total (1645) Total readers

Apr-12 1,600 97.3% 16,436

Aug-13 1,540 93.6% 24,851

Apr-14 1,453 88.3% 32,968

May-14 1,607 97.7% 39,635

05,000

10,00015,00020,00025,00030,00035,00040,00045,000

Ap

r-1

2M

ay-1

2Ju

n-1

2Ju

l-1

2A

ug-

12

Sep

-12

Oct

-12

No

v-1

2D

ec-1

2Ja

n-1

3Fe

b-1

3M

ar-1

3A

pr-

13

May

-13

Jun

-13

Jul-

13

Au

g-1

3Se

p-1

3O

ct-1

3N

ov-

13

Dec

-13

Jan

-14

Feb

-14

Mar

-14

Ap

r-1

4M

ay-1

4

Total readers

1,350

1,400

1,450

1,500

1,550

1,600

1,650A

pr-

12

May

-12

Jun

-12

Jul-

12

Au

g-1

2Se

p-1

2O

ct-1

2N

ov-

12

Dec

-12

Jan

-13

Feb

-13

Mar

-13

Ap

r-1

3M

ay-1

3Ju

n-1

3Ju

l-1

3A

ug-

13

Sep

-13

Oct

-13

No

v-1

3D

ec-1

3Ja

n-1

4Fe

b-1

4M

ar-1

4A

pr-

14

May

-14

# articles on Mendeley

Readership counts – closer look

• For 1102 out of the 1645 articles (67%) readership counts increased monotonously

• Only 6 articles were never located

• All six were cited more than once

• 543 non-monotonous cases

• Maximum decrease in readership count: 240 • “The link-prediction problem for social networks”

• Identical title in conference proceedings and in JASIST

• Wrong source attribution is sometimes the source of large changes in readership counts

• Other case: found through title search in April 2014, not retrieved in May 2014, but found through URL saved in April – retrieval problems?

• All items not located in April or May 2014 were double and triple checked

9

April 2012 vs. May 2014 • April 2012: 1600 out of 1645 articles

• May 2014: 1607 out of 1645 articles

• Are the same articles missing from both sets?

• Only 6 identical articles!

• The six that were never retrieved

• The 45 articles not found in April 2012:

• 320 readers in May 2014

• Most read article is from 2010 with 63 readers in May 2014

• The 38 articles not found in May 2014

• 325 readers in April 2012

• Most read article is from 2007 with 44 readers in April 2012 and 67 readers in August 2013

10

What happens with readership counts over time?

• Users who bookmark the specific item and include it in their Mendeley library

• What happens when the user deletes her account?

• What happens when the user deletes an item from her library? • And if she later bookmarks the same item again???

• How do these actions influence the readership counts?

• The clustering process run from time to time by Mendeley also affects readership counts

• Attribution of publication source

11

Two approaches

1. Once a reader always a reader

– This should result in non-decreasing readership counts

2. Only current readers are readers

– This can explain fluctuations in the counts

• A mixture of the two is also possible

– Deleted account deletes all records

– Deleted items in an existing account do not decrease reader counts

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Suggested solution • Provide the number of readers of the item per month

• Total number of unique readers who bookmarked the item

• This would greatly increase Mendeley’s value as an altmetric

• Easier to report the number of Mendeley readers with a timestamp

• Allow to study interest trends, assuming that users delete items they do not find interesting

• In any case a transparent and consistent solution is needed

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