Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining
By Nitin Agarwal, Nima Dokoohaki, S. Tokdemir. 2019
61 citations recorded by the source corpus.
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.
Subfields: Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics
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Citations in the corpus
- Knowledge Infused Learning (K-IL): Towards Deep Incorporation of Knowledge in Deep Learning (2019, background): “However, (Sheth et al. 2017; Kho et al. 2019) have pointed out the importance of using domain-specific knowledge especially in cases where the problem is complex in nature (Perera et al. 2016).”