Identification d'experts avec le Web 2.0

Identification d’Experts et de

Leaders d’opinion

Le Web 2.0 peut-il vous aider?

H. Basset – http://intelligencescientifique.wordpress.com - 2010

H. Basset - Identification d'experts & Web 2.0 2

La Méthode Idex 2.0 (déposée à l’INPI)

L’identification d’experts se fait traditionnellement sur la seule base d’indicateurs bibliométriques:

Nombre de publications d’un auteur Impact factor des revues Etc.

La Méthode Idex 2.0, décrite brièvement ci-après, suggère une méthodologie pour exploiter aussi les nouvelles sources dites Web 2.0 (réseaux sociaux, blogs, etc.)


Cette présentation est un résumé des présentations et publications suivantes:

Journées ADBS Santé, Lille, 1er Avril 2010 French Customers’ day, Elsevier, Paris, 8 Juin

2010

Basset, Hervé. Identification d’experts scientifiques et de leaders d’opinion: la méthode Idex 2.0. Bases, N° 271, Mai 2010.

Tous les exemples et données brutes ont été retirés


Sommaire

1. Introduction2. Méthodes, astuces, Sources

3. Limites, Discussion

4. Conclusion

5. Sources


Définitions Leaders d’Opinion

Are people who influence the opinion, attitudes, beliefs, motivations and behaviors of others

Key opinion leaders (KOLs), also known as thought leaders, are the experts in their field upon whom Physicians depend for original research leading to disease understanding and new therapies. Physicians rely on them to write the articles, author the textbooks, and give the presentations that they absorb to become better doctors

KOL (Key-Opinion Leaders) for the Pharmaceutical Industry Influential experts, independent senior doctors, recognized speakers and publishers. Some KOLs also

belong to administration, the FDA or EMEA. Key opinion leaders generally belong to a specific area of expertise, such as oncology, cardiology, diabetes,

or sometimes do specialized work in very niched therapeutic areas. They are engaged by industry

To provide advocacy activity (lobbying) To advise on marketing and to provide market feedback To help boost sales of new medicines To help « educate » the profession and the public (publications, congresses)

« Scientific experts who are enlisted by pharmaceutical companies as consultants to conduct basic research, assess the market, design and conduct clinical trials, drive marketing and educational activities » Thomson


Challenges

Experts renommés sont déjà connus MAIS:

Dans un domaine que vous connaissez moins? Experts nationaux? Comment faire si vous ne pouvez pas souscrire

aux sources payantes?


Overview: Life Science 2.0

+++++++++++++++++ Mashups Delicious, NetVibes Twitter Cloud computing: Google Docs Lab Notebooks Slideshare, FlickR Google Knol Podcast Nature Article 2.0


Les Info-Pros

sources

CONNAISSANCE environnement

légal

pour la collecte de données

COMPETENCES pour l’organisation

pour la communication


Sommaire

1. Introduction

2. Méthode, Astuces, Sources3. Limites, Discussion

4. Conclusion

5. Sources


Méthode

1. Identification des besoins: 1er traitement de la demande initiale: interprétation, premiers tests Entretien avec le demandeur

2. Etablir un plan Préciser quelles sont les données attendues par le demandeur

Littérature, brevets, Réseaux sociaux, etc.

Préciser sous quelle forme seront les livrables (fichier excel, etc.)

3. Evaluation du calendrier et de la date de livraison (deadline)

=> Définition d’un besoin réel et précis


Données à évaluer

Critères principaux (Key-data): Publications Littérature, Congrès Brevets, Essais Cliniques Ouvrages de référence

Critères secondaires (Minor Criteria): Réputation Comités éditoriaux: congrès, revues Sociétés savantes Réseaux sociaux, Blogs, etc.


Paid Services Web 2.0

CONSULTANCY

DATA

By Yourself


Services payants: consultants

KOL identification:

http://www.heartbeatexperts.com

http://thomsonreuters.com/products_services/science/science_products/a-z/kolexperts


Littérature - Bibliométrie

Par vous-même

Services avec abonnements: Scopus, Web of Science, etc.

Sources gratuites et Web 2.O: GoPubmed, Novoseek, Scholar Google…


Bibliométrie - Méthode

1. Construire une requête pertinente2. Exportation des données brutes (1er ensemble= 200 auteurs)

3. Pondération en rapport avec votre contexte• Impact Factor, ISI JCR®, Ranking dans le domaine, Article

Influences Scores • H-index, SJR, SNIP, etc.• Journaux influents, Les journaux les plus lus• Publications récentes (- de 5 ans)• Etc.


Bibliométrie: Définitions

Impact Factor: The impact factor, often abbreviated IF, is a measure reflecting the average number of citations to articles published in science and social science journals. It is frequently used as a proxy for the relative importance of a journal within its field, with journals with higher impact factors deemed to be more important than those with lower ones. The impact factor was devised by Eugene Garfield, the founder of the Institute for Scientific Information (ISI), now part of Thomson Reuters. Impact factors are calculated yearly for those journals that are indexed in Thomson Reuter's Journal Citation Reports (JCR). JCR now also includes Article Influence Scores: it takes into account differences in the citation patterns between fields, allowing for better comparisons across different fields.

H-index: The h-index is an index that attempts to measure both the scientific productivity and the apparent scientific impact of a scientist. The index is based on the set of the scientist's most cited papers and the number of citations that they have received in other people's publications. The index can also be applied to the productivity and impact of a group of scientists, such as a department or university or country. The index was suggested by Jorge E. Hirsch, and is sometimes called the Hirsch index or Hirsch number.

SJR: SCImago Journal Rank is a prestige metric based on the idea that ‘all citations are not created equal’. With SJR, the subject field, quality and reputation of the journal has a direct effect on the value of a citation.

SNIP: The Source Normalized Impact per Paper is a new journal indicator based on citation data from Scopus. A journal's SNIP can be thought of as similar to a normalised Impact Factor, which weights citations to adjust for the fact that some fields are more citation-rich than others. The median SNIP for the ~17,000 journals in Scopus is 0.52.


Autres metrics

Journals analyzer (IF, SJR, etc.)

Authors evaluation (citations, H-index, etc.)


Author mapping: complete list of publications, expertise, networks, location, etc.

Springer AuthorMapper • Thomson: www.researcherid.com

• Scopus Author Identifier

• Intellixir


Alternatives: les gratuits

Google Scholar (associé au logiciel gratuit Publish or Perish )

Novoseek (Medline + recherche sémantique dite 3.0)

GoPubmed (Medline + recherche sémantique dite 3.0)

Limites: Consistance des résultats? Confidentialité Institutions publiques: Web of Science imposé par l’OST


Autres Critères et Réputation

Affiliation Brevets, Essais Cliniques Congrès, Sociétés savantes, Comité éditorial Réseaux sociaux Publications dans des ouvrages de référence


Brevets STN Anavist: analysis and visualisation solutions for patents, literature,

pipelines, The VantagePoint: text mining software for Patents analysis

MicroPatents Business opportunities


Essais cliniques

www.ClinicalTrials.gov


Réseaux sociaux


Publications / Memberships

Dans des congrès (communications, posters, boards) Membres de sociétés savantes

Publications dans des ouvrages de référence VidalRecos, EMC, Handbooks, etc. SciTopics, Wikipedia, Blogs, Evidence-based sources, handbooks, etc.


Sommaire

1. Introduction

2. Méthode, Astuces, Sources

3. Limites, Discussion• Limites du Web 2.0• Outils payants Vs Outils gratuits

4. Conclusion

5. Sources


Limites du Web 2.0

« Social media is the pharmaceutical’s industry last

hope to rebuild its battered image » MAIS Les services Web 2.0 sont sous-utilisés par

les scientifiques Les Journaux à Comité de lecture et les

Congrès sont encore les canaux préférés pour la publication et le réseautage


Basis: 1.5 million of Scientists profiles in PubMed 5.5 Millions of Researchers WW (according Unesco) 1,730 Millions of Internet users (2009)

Social Networks FaceBook: (2009) 350 millions BioMedExperts: 100,000 6% of Scientists present in PubMed (0.02% / Facebook)

Blogs Estimated at 126 millions (2009), means 7% of Internet users Technorati estimation:

nearly 20 000 of which consider themselves to be science related (2008) 0.01% of blogs are science-oriented

Micro-Blogging: Twitter: 6 millions of users, 27 millions of Tweets per day According sciencebase.com: « hundreds of Scientwists »

Bookmarking Delicious Vs 2Collab/CiteUlike/Connotea

Wikis: Wikipedia Vs SciTopics

Is Web 2.0 adopted by Scientists?

What does Web 2.0 mean for researchers?. Research Information, Special issue, oct. 2009. Online.


Is Web 2.0 adopted by Scientists?

« If you spend much time in the science blogosphere, everyone seems to be talking about these great tools and the changes they’re making in research science. But when you step away from the enthusiasts and speak with the majority of scientists, you find out that they don’t have much interest in using many of these new technologies » D. Crotty

Reasons: Lack of time: potential users are overscheduled and overworked: they are already completely overloaded by current

literature to digest Authors of blogs or contributions are rarely prominent researchers: those prefer classic channels

(books, prestigious journals, congresses) which are more incentive, more lucrative, more prestigious A confused « market »: too many sites for a same purpose: Connotea, CiteUlike, etc. Services are inappropriate to the Scientists culture: « Scientists don’t find collaborators by chatting online

with strangers » Scientists use social networks to find a job (LinkedIn) not to chat with friends Science Blogs are only read by other Science bloggers, students, non-scientists/non

specialists and journalists

Flaws of Blogs: « me to » (too much with the same information) + « I do » (too ego-centered) More pressure on Corporate Researchers


Le Web 2.0 contre les services payants Certains services peuvent

apparaître comme plus efficace:

PubMed, Google Scholar Drugs.com Clinicaltrials.com

MAIS Ils sont rarement plus

exhaustifs que les services payants

0

500

1000

1500

2000

2500

3000

WoS Scopus GS

Time to collect data

• Efficacité?

According Meho & Yang, 2007, collecting meaningful data from Google Scholar

takes 30 as much time as collecting data from Web of Science


Outils gratuits Vs Services payants

“paid search is 325% more productive than the free web”Martin Akel & Associates. FREE Web search Vs. PAID search tools. 2007

BENEFICES OBJECTIFS des services payants Sont plus exhaustifs Sont plus vite mis à jour Sont compatibles avec les règles internes des companies

(informatique, Confidentialité, etc.)

Améliorent l’efficacité Font gagner du temps

BENEFICES SUBJECTIFS Collaborateurs apprécient les efforts financiers de leur

société; cela leur donne l’impression d’avoir un privilège


Sommaire

1. Introduction

2. Méthode, Astuces, Sources


4. Conclusion5. Sources


Conclusion Assurez-vous de bien analyser la question originale pour apporter une

réponse professionnelle et efficace

Beaucoup d’indicateurs et de livrables sont possibles, selon votre domaine d’intervention

Selon votre contexte, relativisez les indicateurs classiques

Services payants sont un gage de sécurité et de fiabilité

Web 2.0 n’est pas exhaustif mais peut aider! Relativisez l’importance réel du Web 2.0

Compilation de données hétérogènes requiert: Une bonne connaissance de l’environnement Temps et organisation


Sommaire

1. Introduction

2. Méthodes, Astuces, Sources


4. Conclusion

5. Sources


Sources KOL:

Wikipedia: Opinion leadership: http://en.wikipedia.org/wiki/Key_opinion_leader White paper: Key opinion leader identification and selection. January 2009. www.thomson-pharma.com Moynihan, Ray. Key opinion leaders: Independent experts or drug representatives in disguise?. British

Medical Journal. Volume 336, 21 Juin 2008. pp. 14021403 Brignull, Eve. Drilling for success; The search for strategic partners: beyond Key Opinion Leaders.

Presentation at PharmaBioMed 2009. http://www.pharmabiomed.com

Bibliometrics: Perish or Publish: http://www.harzing.com/pop.htm With Scopus: http://www.info.scopus.com/researchtrends/ SNIP & SJR: http://info.scopus.com/journalmetrics/ Un thésard en Sorbonne

Web 2.0 & Science: Research Information: Special issue: What does Web 2.0 mean for researchers?. Oct.-Nov. 2009. Online:

http://www.researchinformation.info/features/issue.php?issue_id=33 Crotty, David. Why Web 2.O is failing in Biology. Bench Marks blog, online, Feb. 2008:

http://www.cshblogs.org/cshprotocols/2008/02/14/why-web-20-is-failing-in-biology/

Free Versus Paid tools: Akel, Martin & Associates. FREE Web search Vs. PAID search tools: a comparison of productivity in the

Research Process, 2007. White paper. Online: www.elsevierforindustry.com


La Méthode Idex 2.0

Blog perso: http://intelligencescientifique.wordpress.com

Email perso: [email protected]

Identification d'experts avec le Web 2.0

Health & Medicine

Transcript of Identification d'experts avec le Web 2.0