- 情感人工智能与广告(英文版)/全球话语与媒介研究
- - 作者：卢薪宇|责编:马昱
  - 出版社：上海交大
  - ISBN：9787313291721
  - 出版日期：2023/08/01
  - 页数：164
- 售价：27.6

内容大纲
    情感人工智能（Emotional AI）或情感计算（Affective Computing）是近年来人工智能领域发展的新方向，在营销等多个领域具有重要的实用价值和现实意义。本书系统回顾了情感计算的核心领域、关键技术及其在营销领域的应用，并通过实证研究为基于情感计算技术等的精准营销提供借鉴。
    本书分为上、中、下三篇。上篇系统介绍了人工智能技术在广告领域的应用，并着重介绍了情感智能／计算在广告领域的应用潜力。中篇深入介绍了情感智能／计算的最新核心技术，及其在营销领域的实际应用。下篇从一篇实证研究出发，考察了消费者在接触广告时的实时情绪状态对其广告反应的影响，对基于消费者实时情绪的精准匹配、算法推荐提供了数据支持和参考。
    本书适合广告领域研究者与从业者参考阅读。
作者介绍
卢薪宇，上海外国语大学新闻传播学院讲师、硕士生导师，上海市浦江人才，国际广告学TOP期刊Joumal of Advertising编委。美国明尼苏达大学大众传播学博士，印第安纳大学新闻学硕士。明尼苏达大学计算广告研究实验室兼职研究员。主要研究领域包括大数据与计算广告学、新媒体品牌传播、社交媒体与传播效果，聚焦新一代智能媒体技术在品牌传播中的应用和效果研究。
目录
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

内容大纲

作者介绍

目录

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