盧薪宇|責編:馬昱
盧薪宇，上海外國語大學新聞傳播學院講師、碩士生導師，上海市浦江人才，國際廣告學TOP期刊Joumal of Advertising編委。美國明尼蘇達大學大眾傳播學博士，印第安納大學新聞學碩士。明尼蘇達大學計算廣告研究實驗室兼職研究員。主要研究領域包括大數據與計算廣告學、新媒體品牌傳播、社交媒體與傳播效果，聚焦新一代智能媒體技術在品牌傳播中的應用和效果研究。
目錄
Part 1 An Overview of Artificial Intelligence and Affective Computing Chapter 1 Artificial Intelligence and Its Applications in Advertising 1.1 Artificial Intelligence in Advertising 1.2 The Rise of Contextual Targeting in Advertising Chapter 2 Affective Computing and Key Areas 2.1 An Introduction to Affective Computing 2.2 Areas of Affective Computing 2.3 An Overview of Technologies of Affective Computing Part 2 Affective Computing: Key Technologies and Applications Chapter 3 State-of-the-Art Technologies of Affective Computing: Recent Advances 3.1 Emotion Recognition Using Visual Modal Features 3.2 Emotion Recognition Using Audio Modal Features 3.3 Sentiment Analysis Using Textual Modal Features 3.4 Affect Recognition Using Multimodal Features Chapter 4 Practical Applications of Affective Computing in Marketing 4.1 Practical Applications of Empathic Affective Computing 4.2 Practical Applications of Collaborative Affective Computing 4.3 Practical Applications of Interactive Affective Computing Part 3 Influence of Consumers' Temporary Affect on Attention and Reaction to Ads: A Computational Research Approach Chapter 5 Introduction 5.1 Research Purpose and Focus 5.2 Methodology Introduction 5.3 Chapters and Organization Chapter 6 Literature Review 6.1 Research on Attention to Ads and Influencing Factors 6.2 Research on the Influence of Affect on Attention 6.3 Mood Management Theory Explaining the Influence of Affect on Ad Attention 6.4 Research on the Influence of Affect on Ad Processing and Ad Evaluation Chapter 7 Hypotheses Development 7.1 Impact of Consumers' Affective State on Selective Attention to Ads 7.2 Impact of Consumers' Affective State on Ad Processing and Ad Evaluation Chapter 8 Computational Research Method 8.1 Data Collection and Analysis Procedures 8.2 Variable Computations Chapter 9 Results 9.1 Descriptive Statistics from the Super Bowl Ad Content Analysis 9.2 Descriptive Statistics of the Twitter Data 9.3 Hypotheses Testing Results Chapter 10 Summary and Discussion 10.1 Summary of Findings 10.2 Discussion of Findings 10.3 Implications 10.4 Limitations and Suggestions for Future Research Appendix References Index
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