Flying to the Top, One Tweet at a
Time:
Using Social Media to Rank
Online Search Results
Robyn B. Reed, MA, MLIS
Co
-
authors:
Carrie L. Iwema, PhD, MLS
Ansuman Chattopadhyay, PhD
Health Sciences Library System
University of Pittsburgh
Workshops
Website
Software
Licensing
Consultations
Molecular Biology Information Service
Online Bioinformatics Resources Collection
(OBRC)
http://www.hsls.pitt.edu/obrc/
Resources displayed by keyword ranking
http://www.hsls.pitt.edu/obrc/
Challenges:
Many tools exist and increasing in number
User may retrieve several resources
Common question
–
How do I know which one(s) to use?
Goal:
Provide up
-
to
-
date ratings of most highly
regarded resources in bioinformatics
Objectives:
Using social media, design ranking system
of OBRC resources
Determine if social media results reflect
opinions of bioinformatics experts
Why use the social media??
•
No official rankings of bioinformatics tools
•
Opinions of several people
•
Social media data has many applications
http://beta.socialguide.com/
Methodology
Wrote 5 research questions
Common bioinformatics queries
Each question listed 3 possible resources
to accomplish that task
Resources were
ranked using social
media data
Experts (2)
independently
ranked resources
Methodology
Research questions
Methodology
–
Social Media Ranking
Sources used for data collection
Google Blogs
Google Discussions
Google Discussions includes
•
Forums
•
Groups
•
Comments
www.google.com
Twitter considered and removed
•
50% of the resources had zero Tweets
•
20% captured non
-
specific Tweets
Facebook not included
•
Concern over private settings
Methodology
–
Data Sources
Methodology
–
Social Media Ranking
Searched “all time”
Optimized for most accurate retrieval
•
Resource in quotes
•
Increased specificity, decreased noise
•
Fewer hits
[(“ucsc genome browser”) AND ( bioinformatics | genome |
genetics | genomics | computer | algorithm | software |
server | database | computer model | protein | proteomics |
proteome | gene | DNA | RNA | sequence | alignment |
interactions | structure | modeling | prediction |
biochemistry | molecular biology | systems biology |
computational biology)]
•
Put all OBRC resources in bioinformatics context
•
Automate the searches
Example of search of UCSC genome browser
Methodology
–
Search Filter
Results
Bioinformatics Tools
Blogs + Discussion
Raw Numbers
Social Media
Rank
Expert 1
Rank
Expert 2
Rank
CPHmodels
49
2
2
2
3
-
D protein prediction
ESypred3D
17
3
3
3
SWISS
-
MODEL
228
1
1
1
IDT SciTools
4
2
2
2
PCR primer design
Primer3
728
1
1
1
Primer Design Assistant
0
3
3
3
DIANA
-
microT
12
1
1
2
microRNA target design
miRGator
9
2
2
3
siRNA target finder Ambion
3
3
3
1
ClustalW
1494
1
1
3
multiple sequence alignment
ECR Browser
8
3
3
1
Tcoffee
63
2
2
2
Ensembl
3070
1
3
2
genome browsers
NCBI Map Viewer
56
3
2
3
UCSC Genome Browser
928
2
1
1
Bioinformatics Tools
Blogs + Discussion
Raw Numbers
Social Media
Rank
Expert 1
Rank
Expert 2
Rank
CPHmodels
49
2
2
2
3
-
D protein prediction
ESypred3D
17
3
3
3
SWISS
-
MODEL
228
1
1
1
IDT SciTools
4
2
2
2
PCR primer design
Primer3
728
1
1
1
Primer Design Assistant
0
3
3
3
DIANA
-
microT
12
1
1
2
microRNA target design
miRGator
9
2
2
3
siRNA target finder Ambion
3
3
3
1
ClustalW
1494
1
1
3
multiple sequence alignment
ECR Browser
8
3
3
1
Tcoffee
63
2
2
2
Ensembl
3070
1
3
2
genome browsers
NCBI Map Viewer
56
3
2
3
UCSC Genome Browser
928
2
1
1
Results
Bioinformatics Tools
Blogs + Discussion
Raw Numbers
Social Media
Rank
Expert 1
Rank
Expert 2
Rank
CPHmodels
49
2
2
2
3
-
D protein prediction
ESypred3D
17
3
3
3
SWISS
-
MODEL
228
1
1
1
IDT SciTools
4
2
2
2
PCR primer design
Primer3
728
1
1
1
Primer Design Assistant
0
3
3
3
DIANA
-
microT
12
1
1
2
microRNA target design
miRGator
9
2
2
3
siRNA target finder Ambion
3
3
3
1
ClustalW
1494
1
1
3
multiple sequence alignment
ECR Browser
8
3
3
1
Tcoffee
63
2
2
2
Ensembl
3070
1
3
2
genome browsers
NCBI Map Viewer
56
3
2
3
UCSC Genome Browser
928
2
1
1
Results
Conclusions:
This system can be used to determine
highly regarded tools
Explain that rankings are subjective;
try the top 3
-
5 resources
Provides patron with a starting point
when using the OBRC
Limitations
•
Quotation marks can be limiting if
resource >1 word
•
Very small part of the total social media
•
“Negative” discussion about a resource
Future Directions
•
Test > 3 bioinformatics tools/category
•
Increase number of expert ratings
•
Test applicability of system in areas other
than bioinformatics
Special thanks to:
Project collaborators and experts:
Ansuman Chattopadhyay, PhD
Carrie Iwema, PhD, MLS
Research and academic advisors:
Nancy Tannery, MLS
Rebecca Crowley, MD, MS
Funding from the Pittsburgh Biomedical
Informatics Training Program
NLM Grant 3 T15 LM007059
-
23S1
Thank you!
Any questions?
Robyn Reed
rreed@pitt.edu
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