Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining

The contributors in this book share, exchange, and develop new concepts, ideas, principles, and methodologies in order to advance and deepen our understanding of social networks in the new generation of Information and Communication Technologies (ICT) enabled by Web 2.0, also referred to as social m...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Agarwal, Nitin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Dokoohaki, Nima (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Tokdemir, Serpil (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Lecture Notes in Social Networks,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Chapter1: Intent Mining for the Good, Bad & Ugly Use of Social Web: Concepts, Methods, and Challenges
  • Chapter2: Bot-ivistm: Assessing Information Manipulation in Social Media Using Network Analytics
  • Chapter3: Studying Fake News via Network Analysis: Detection and Mitigation
  • Chapter4: Predictive Analysis on Twitter: Techniques and Applications
  • Chapter5: Using Subgraph Distributions for Characterizing Networks and Fitting Random Graph Models
  • Chapter6: Towards Effective Assessment of Group Collaborations in OSNs
  • Chapter7: Dynamics of Overlapping Community Structures with Application to Expert Identification
  • Chapter8: On Dynamic Topic Models for Mining Social Media
  • Chapter9: Domain Specific Use Cases for Knowledge Enabled Social Media Analysis
  • Chapter10: Privacy in Human Computation: User awareness study, Implications for existing platforms, Recommendations, and Research Directions.