Sentic Computing

Introduction1.1 Sentic Computing 1.1.1 Motivations 1.1.2 Aims 1.1.3 Methodology Background 2.1 Opinion Mining and Sentiment Analysis 2.1.1 The Buzz Mechanism 2.1.2 Origins and Peculiarities 2.1.3 Sub-Tasks 2.2 Main Approaches to Opinion Mining 2.2.1 From Heuristics to Discourse Structure 2.2.2 From Coarse to Fine Grained 2.2.3 From Keywords to Concepts 2.3 Towards Machines with Common Sense 2.3.1 The Importance of Common Sense 2.3.2 Knowledge Representation 2.3.3 From Logical Inference to Digital Intuition 2.4 Conclusions Techniques3.1 Affective Blending: Enabling Emotion-Sensitive Inference 3.1.1 AffectNet 3.1.2 AffectiveSpace 3.2 Affective Categorisation: Modelling Human Emotions 3.2.1 Categorical Versus Dimensional Approaches 3.2.2 The Hourglass of Emotions 3.3 Sentic Medoids: Clustering Affective Common Sense Concepts 3.3.1 Partitioning Around Medoids 3.3.2 Centroid Selection 3.4 Sentic Activation: A Two-Level Affective Reasoning Framework 3.4.1 Unconscious Reasoning 3.4.2 Conscious Reasoning 3.5 Sentic Panalogy: Switching Between Different Ways to Think 3.5.1 Changing Reasoning Strategies 3.5.2 Changing Reasoning Foci 3.6 Conclusions Tools4.1 SenticNet: A Semantic Resource for Opinion Mining 4.1.1 Building SenticNet 4.1.2 Working with SenticNet 4.2 Sentic Neural Networks: Brain-Inspired Affective Reasoning 4.2.1 Discrete Versus Continuous Approach 4.2.2 Affective Learning 4.3 Open Mind Common Sentics: An Emotion-Sensitive IUI 4.3.1 Games for Knowledge Acquisition 4.3.2 Collecting Affective Common Sense Knowledge 4.4 Isanette: A Common and Common Sense Knowledge Base 4.4.1 Probase 4.4.2 Building the Instance-Concept Matrix 4.5 Opinion Mining Engine: Structuring the Unstructured 4.5.1 Constitutive Modules 4.5.2 Evaluation 4.6 Conclusions Applications5.1 Development of Social Web Systems 5.1.1 Troll Filtering 5.1.2 Social Media Marketing 5.1.3 Sentic Album 5.2 Development of HCI Systems 5.2.1 Sentic Avatar 5.2.2 Sentic Chat 5.2.3 Sentic Corner 5.3 Development of E-Health Systems 5.3.1 Crowd Validation 5.3.2 Sentic PROMs 5.4 Conclusions Concluding Remarks6.1 Summary of Contributions 6.1.1 Techniques 6.1.2 Tools 6.1.3 Applications 6.2 Limitations and Future Work 6.2.1 Limitations 6.2.2 Future Work 6.3 Conclusions References