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Veracity of data : from truth discovery computation algorithms to models of misinformation dynamics /

Bibliographic Details
Main Authors: Berti-Équille, Laure (Author), Borge-Holthoefer, Javier (Author)
Format: eBook
Language:English
Published: San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2016.
Series:Synthesis lectures on data management ; # 42.
Subjects:
Computer algorithms.
Data editing.
Data integrity.
Databases > Evaluation.
Verification (Logic) > Computer programs.
data veracity
information extraction
misinformation dynamics
trust computation
truth discovery
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 1. Introduction to data veracity
  • 1.1 The fourth "V" of big data
  • 1.2 Main causes affecting data veracity
  • 1.3 Classification of truth discovery approaches
  • 1.4 Information extraction
  • 1.5 Fact-checking and trust computation
  • 1.6 Misinformation dynamics in networked systems
  • 2. Information extraction
  • 2.1 Introduction
  • 2.2 Information extraction pipeline
  • 2.2.1 Tokenization and sentence segmentation
  • 2.2.2 Normalization
  • 2.2.3 Part-of-speech tagging
  • 2.2.4 Named entity recognition
  • 2.2.5 Mention detection and coreference resolution
  • 2.3 Knowledge graph population
  • 2.3.1 Entity discovery and linking
  • 2.3.2 Relation extraction and inference
  • 2.3.3 Slot filling
  • 2.3.4 Slot filler validation
  • 2.4 Contradiction detection
  • 2.5 Conclusion
  • 3. Truth discovery computation
  • 3.1 Introduction
  • 3.2 Terminology
  • 3.2.1 Notations and basic principle
  • 3.2.2 Characterization of truth discovery methods
  • 3.2.3 Modeling assumptions
  • 3.3 Truth discovery methods
  • 3.3.1 Agreement-based methods
  • 3.3.2 MAP estimation-based methods
  • 3.3.3 Analytical methods
  • 3.3.4 Bayesian inference-based methods
  • 3.4 New developments
  • 3.4.1 Evolving truth discovery
  • 3.4.2 Zero-to-many truth
  • 3.4.3 Long-tail phenomenon
  • 3.4.4 Truth discovery from crowdsourced data
  • 3.5 Conclusion
  • 4. Trust computation
  • 4.1 Introduction
  • 4.2 Definitions
  • 4.3 Probabilistic trust computation
  • 4.3.1 Direct trust models
  • 4.3.2 Combining direct and indirect trust models
  • 4.3.3 Evaluation of trust computing schemes
  • 4.4 Trust propagation
  • 4.4.1 Overriding trust propagation
  • 4.4.2 Aggregation-based propagation
  • 4.5 Conclusion
  • 5. Misinformation dynamics
  • 5.1 Introduction
  • 5.2 Theoretical foundations
  • 5.2.1 Terminology in complex networks
  • 5.2.2 Complex network descriptors
  • 5.2.3 Network models
  • 5.3 Disease and rumor propagation models
  • 5.3.1 Epidemic spreading
  • 5.3.2 Rumor propagation
  • 5.3.3 Misinformation dynamics
  • 5.4 Theory under test: empirical feedback
  • 5.4.1 Source identification
  • 5.4.2 Dynamical role of source and intermediate nodes
  • 5.5 Misinformation containment and meme mutation in complex social systems
  • 5.5.1 Influence limitation: averting malicious viral processes
  • 5.5.2 Information mutation: meme tracking
  • 6. Transdisciplinary challenges of truth discovery
  • 6.1 Introduction
  • 6.2 From information to data
  • 6.2.1 Big data vs. sparse facts
  • 6.2.2 Decontextualization
  • 6.2.3 Uncertain, incomplete, and biased observations
  • 6.2.4 Data and information fusion across languages, modalities, and media
  • 6.3 From multisource data to networks of sources and networks of content
  • 6.3.1 Truth discovery in common multiplexes
  • 6.3.2 Time-dependent truth discovery
  • 6.3.3 Complex interconnected networks of sources and multimedia content
  • 6.4 Final remark
  • Bibliography
  • Authors' biographies.