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Data Science andArtificial Intelligence at theScholarly Communications Frontier
John SackFounding DirectorHighWire Press27 February 2018
Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions58
ArtificialIntelligence
DataScience
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Readers / Authors Editors / Publishers
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Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions59
ArtificialIntelligence
DataScience
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3 4
Readers / Authors Editors / Publishers
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AI-basedPortfolioManagement
• Could an AI ”edit” ajournal as it canmanage a stockportfolio?
• Discuss.
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Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions65
ArtificialIntelligence
DataScience
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3 4
Readers / Authors Editors / Publishers
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AI for Researchers: Readers/Authors
• “Keeping Up”– Which new articles match my fields?– Which articles are about my specific interests?– Which articles contain something related to my
specific interests?• “Writing Up”
– Draft my newest article for me– Where shall I submit my newest article first?
• ”Dreaming Up”– How might Gene A and Protein C be related?
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Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions74
ArtificialIntelligence
DataScience
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Readers / Authors Editors / Publishers
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HighWire Editors’ Workshop on AI:What Editors Asked Us For
• Journal Performance– Visualize the performance of a journal, its context and
competitors• Community Engagement
– Tools to attract and retain the best authors, and thebest papers, in advance of a paper’s submission
• Emergence of the New: fields, topics, authors,labs– Tools to see over the horizon
• Workflow Productivity/Efficiency– Deal with repetitive, expertise-burning tasks
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Meta’s“BibliometricIntelligence”to evaluatesubmissions
• Is my journal anappropriate venuefor thismanuscript?
• What is thepotential impactof this paper?
• To whom should Isend this paperfor review?
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Fishing in the Preprint Stream forProspective Papers
– Journals can leverage preprints by findingthe best and most appropriate articles to solicit
– Already happeningmanually
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Evaluationof FigureIntegrity
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“We suggest that agreat deal ofscientific fraud willbe, sooner or later,detectable byautomatic means.”
Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions83
ArtificialIntelligence
DataScience
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3 4
Readers / Authors Editors / Publishers
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Data-ScienceGuided Decision on
Which journals toSubmit a paper to:
Is this journala club
I aspireto join?
Data-ScienceGuided
Reading
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Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions85
ArtificialIntelligence
DataScience
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Readers / Authors Editors / Publishers
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Impact Vizor:Data-driven Insight into Editors’ Big Questions
• Rejected Articles– Who publishes my rejected articles?– Am I rejecting high-impact articles?
• Published Articles– Which articles are driving my impact up, or down?– Which types of articles are resonating?– Are this year’s articles higher impact than last year’s?
• Cohort Articles– What are the trending topics in my fields?– And who is publishing them?
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The Different Faces of Impact Vizors’ Viewers
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< RejectedArticleTracker
Section >PerformanceAnalyzer
< Hot Article(& Object)Tracker
Advance >Correlator ofCitations &Usage
< CitationDistributionSurveyor
Cohort >Comparator
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Which Sections of a Journal are Consistently Below Par?What Groups of Articles Are Cited Above and Below Average
Are New Articles Cited More or Less than Previous Ones?
3/17/2018HighWire Press -- CONFIDENTIAL
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JournalPerformance:Competitor
Streamgraph
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Q: Who is publishingIn my fields, andHow much? What isMy “market share”?
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JournalPerformance:
TopicStreamgraph
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Q: Which fields thatI publish in aregrowing, and whichare shrinking?
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Analytics Support forEvidence-Based
DesignHeat maps
Confetti (click) maps
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Topics: AI/DS. Authors/Editors
• AI Applications Overview• AI and Data Science in Publishing
• Some Cautions– The Hype Cycle, and Validation
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ArtificialIntelligence
DataScience
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Readers / Authors Editors / Publishers
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“People tend to
overstatethe short-term potential of new technologies and
understate
their long-term consequences.”- Paul Saffo- Ray Amara, ”Amara’s Law”
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Validation – Calibration - Confidence• HighWire’s Impact Vizor Validating Meta’s Predictions
– Correlate AI-Predicted Cites to Actual Cites– Examine N, R, R-Squared, and P-value, by Journal,
TOC, Collection
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