AI and Social Media Advertising
An Enabling Technology or An Effective Research Tool? Special issue of the Journal of Interactive Advertising; Deadline 31 Dec 2022
Author: ELMAR Moderator
Journal of Interactive Advertising
AI and Social Media Advertising
An Enabling Technology or An Effective Research Tool?
Call for Papers: Special Issue Article Collection on AI and Social Media Advertising
Huan Chen, Associate Professor, University of Florida
Yang Feng, Associate Professor, San Diego State University
With the constant advancement and innovation of technology, artificial intelligence (AI) has been widely adopted in the advertising industry and shaped every aspect of the advertising process (Rogers, 2021) such as consumer insight discovery, advertising creation, media planning and buying, and advertising impact evaluation (Qin & Jiang, 2019) with both short-term promotional effects and long-term brand relationships (Li, 2019). Accordingly, the number of academic research on AI and advertising has significantly increased in recent years and covers a variety of topics (Kim, 2021; Li, 2019; Rogers, 2021). Extant research has examined AI’s impact on consumer journey (Kietzman et al., 2018), AI’s prediction on consumer personality (Shumanov et al., 2021), public conversations on AI (Wu et al., 2021), AI’s role in advertising creativity (Chen et al., 2019; Vaskratsas & Wang, 2021), deepfakes and AI-generated ads (Campbell et al., 2021; Kietzmann et al., 2021), woke advertising (Feng et al., 2021), AI and influencer marketing (Feng et al., 2020; Thomas & Fowler, 2021), macro factors influencing AI advertising (Helberger et al., 2020), and methodological and technical issues of AI advertising research (Feng et al., 2019; Hayes et al., 2021; Yun et al., 2020).
A close examination of the current literature on AI and advertising suggests that scholars either examined AI as an enabling technology that brings possibilities and enhances the efficiency and effect of advertising via multiple AI-related technologies or adopted AI as a research tool that complements traditional research methods by uncovering hidden insights from a large scale of data. In order to further advance the conceptualization and theorization of AI advertising as well as promote the methodological development and diversity of AI technology in advertising research, we invite original manuscripts for this upcoming Special Issue Article Collection of the Journal of Interactive Advertising (JIA) dedicated to AI and Social Media Advertising.
The proposed special issue article collection focuses on two directions. The first direction examines the role of AI as an enabling technology in social media advertising practices, as well as its promises and perils. Relevant topics and themes for this direction might include, but are not limited to:
- The personalized advertising brought by the recommendation algorithms of social media, and its effectiveness and privacy concerns
- The role of comment ranking algorithms of social media in shaping consumer responses toward social media campaigns
- Consumers’ perceptions of chatbots used by brands on social media, and consumer-brand engagement of chatbots-enabled promotions
- The location-based advertising brought by the recommendation algorithms of social media, and its effectiveness and privacy concerns
- Consumers’ perceptions of AI-produced advertising compared to human-made advertising
- The effectiveness and efficiency of AI-assisted social media advertising plan
The second direction examines the role of AI as a research tool in social media advertising research, as well as its strengths and weaknesses. Relevant topics and themes for this direction might include, but are not limited to:
- Leverage computer vision and natural language processing to examine the visual and textual content of sponsored social media posts and identify the relationship between visual and textual content and consumers’ engagement with sponsored social media posts
- Use natural language processing to monitor consumer responses toward social media campaigns, such as sentiment analysis, topic discovery, etc.
- Leverage computer vision and/or natural language processing to extract creative ideas from user-generated posts in order to create customized brand posts for consumers
- Accuracy of AI-facilitated data analytics applied in social media advertising research
- How and when to use unsupervised vs. supervised machine learning to uncover insights from consumer-generated social media data
- How to integrate and triangulate AI-enabled methods with traditional qualitative and quantitative research methods in the context of social media advertising to generate rigorous and innovative discoveries
References: Available upon request. Due to the space limitation, the list of cited resources cannot be provided in this announcement.