Social Media Analytics for User Behavior Modeling

Social Media Analytics for User Behavior Modeling

A Task Heterogeneity Perspective

Nelakurthi, Arun Reddy; He, Jingrui

Taylor & Francis Ltd

09/2021

116

Mole

Inglês

9781032175782

15 a 20 dias

181

Descrição não disponível.
1. Introduction. 2. Related Work. 3. User-Guided Cross-Domain Sentiment Classification. 4. Similar Actor Recommendation.

5. Source-Free Domain Adaptation of the Off-the-Shelf Classifier. 6. Social Media for Diabetes Management. 7. Conclusion and Future Work.
Deep Neural Network Models;SVM Classifier;Transfer Learning;Single Hidden Layer Neural Network;Link Prediction;RBF Kernel;Data Sets;Institutional Review Board;Matriz Factorization;Target Domain;User Soft-Score Weights;Unlabeled Examples;AOT Framework;Health Care Forums;task heterogeneity;Modeling User Behavior;machine learning algorithms;social media platforms;Sentiment Classification;inconsistent user behaviors;Source Domain;healthcare-related applications;Community Detection Problem;Social Media Data;Dm Care;Product Level Information;Diabetes Management Behaviors;Data Chunks;Residual Vector;Diabetes Self-care Activities;Concept Drift;Elastic Net Regularizer;Data Set;Tripartite Graph