1. 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

2. WorkshopsWebsite Software Licensing Consultations Molecular Biology Information Service

3. Online Bioinformatics Resources Collection (OBRC) http://www.hsls.pitt.edu/obrc/

4. Resources displayed by keyword ranking http://www.hsls.pitt.edu/obrc/

5. Challenges: Many tools exist and increasing in number User may retrieve several resources Common question – How do I know which one(s) to use?

6. 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

7. Why use the social media?? No official rankings of bioinformatics tools Opinions of several people Social media data has many applications

8. http://beta.socialguide.com/

9. Methodology Wrote 5 research questions Common bioinformatics queries Each question listed 3 possible resources to accomplish that task

10. Resources were ranked using social media data Experts (2) independently ranked resources Methodology Research questions

11. Methodology – Social Media Ranking Sources used for data collection  Google Blogs  Google Discussions Google Discussions includes Forums Groups Comments www.google.com

12. 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

13. Methodology – Social Media Ranking Searched “all time” Optimized for most accurate retrieval Resource in quotes Increased specificity, decreased noise Fewer hits

14. [(“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

15. Results Bioinformatics Tools Blogs + Discussion Raw Numbers Social Media Rank Expert 1 Rank Expert 2 Rank CPHmodels49222 3-D protein prediction ESypred3D17333 SWISS-MODEL228111 IDT SciTools4222 PCR primer design Primer3728111 Primer Design Assistant0333 DIANA-microT12112 microRNA target design miRGator9223 siRNA target finder Ambion3331 ClustalW1494113 multiple sequence alignment ECR Browser8331 Tcoffee63222 Ensembl3070132 genome browsers NCBI Map Viewer56323 UCSC Genome Browser928211

16. Bioinformatics Tools Blogs + Discussion Raw Numbers Social Media Rank Expert 1 Rank Expert 2 Rank CPHmodels49222 3-D protein prediction ESypred3D17333 SWISS-MODEL228111 IDT SciTools4222 PCR primer design Primer3728111 Primer Design Assistant0333 DIANA-microT12112 microRNA target design miRGator9223 siRNA target finder Ambion3331 ClustalW1494113 multiple sequence alignment ECR Browser8331 Tcoffee63222 Ensembl3070132 genome browsers NCBI Map Viewer56323 UCSC Genome Browser928211 Results

17. Bioinformatics Tools Blogs + Discussion Raw Numbers Social Media Rank Expert 1 Rank Expert 2 Rank CPHmodels49222 3-D protein prediction ESypred3D17333 SWISS-MODEL228111 IDT SciTools4222 PCR primer design Primer3728111 Primer Design Assistant0333 DIANA-microT12112 microRNA target design miRGator9223 siRNA target finder Ambion3331 ClustalW1494113 multiple sequence alignment ECR Browser8331 Tcoffee63222 Ensembl3070132 genome browsers NCBI Map Viewer56323 UCSC Genome Browser928211 Results

18. 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

19. Limitations Quotation marks can be limiting if resource >1 word Very small part of the total social media “Negative” discussion about a resource

20. Future Directions Test > 3 bioinformatics tools/category Increase number of expert ratings Test applicability of system in areas other than bioinformatics

21. 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

22. Thank you! Any questions? Robyn Reed rreed@pitt.edu