Flying to the Top, One Tweet at a - University of Pittsburgh

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4 Οκτ 2013 (πριν από 3 χρόνια και 11 μήνες)

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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