Persuasion Strategies in Advertisements

• URL: http://arxiv.org/abs/2208.09626v2
• Date: Sat, 6 May 2023 07:28:51 GMT
• Title: Persuasion Strategies in Advertisements
• Authors: Yaman Kumar Singla, Rajat Jha, Arunim Gupta, Milan Aggarwal, Aditya Garg, Tushar Malyan, Ayush Bhardwaj, Rajiv Ratn Shah, Balaji Krishnamurthy, and Changyou Chen
• Abstract summary: We introduce an extensive vocabulary of persuasion strategies and build the first ad image corpus annotated with persuasion strategies. We then formulate the task of persuasion strategy prediction with multi-modal learning. We conduct a real-world case study on 1600 advertising campaigns of 30 Fortune-500 companies.
• Score: 68.70313043201882
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Modeling what makes an advertisement persuasive, i.e., eliciting the desired response from consumer, is critical to the study of propaganda, social psychology, and marketing. Despite its importance, computational modeling of persuasion in computer vision is still in its infancy, primarily due to the lack of benchmark datasets that can provide persuasion-strategy labels associated with ads. Motivated by persuasion literature in social psychology and marketing, we introduce an extensive vocabulary of persuasion strategies and build the first ad image corpus annotated with persuasion strategies. We then formulate the task of persuasion strategy prediction with multi-modal learning, where we design a multi-task attention fusion model that can leverage other ad-understanding tasks to predict persuasion strategies. Further, we conduct a real-world case study on 1600 advertising campaigns of 30 Fortune-500 companies where we use our model's predictions to analyze which strategies work with different demographics (age and gender). The dataset also provides image segmentation masks, which labels persuasion strategies in the corresponding ad images on the test split. We publicly release our code and dataset https://midas-research.github.io/persuasion-advertisements/.

Related papers

• PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent [71.20471076045916]
  Propaganda plays a critical role in shaping public opinion and fueling disinformation. Propainsight systematically dissects propaganda into techniques, arousal appeals, and underlying intent. Propagaze combines human-annotated data with high-quality synthetic data.
  arXiv  Detail & Related papers  (2024-09-19T06:28:18Z)
• Social Dynamics of Consumer Response: A Unified Framework Integrating Statistical Physics and Marketing Dynamics [0.0]
  This study examines the complex nature of consumer behaviour by applying theoretical frameworks derived from physics and social psychology. We present an innovative equation that captures the relation between spending on advertising and consumer response, using concepts such as symmetries, scaling laws, and phase transitions.
  arXiv  Detail & Related papers  (2024-04-01T11:23:31Z)
• Werewolf Among Us: A Multimodal Dataset for Modeling Persuasion Behaviors in Social Deduction Games [45.55448048482881]
  We introduce the first multimodal dataset for modeling persuasion behaviors. Our dataset includes 199 dialogue transcriptions and videos, 26,647 utterance level annotations of persuasion strategy, and game level annotations of deduction game outcomes.
  arXiv  Detail & Related papers  (2022-12-16T04:52:53Z)
• Using Persuasive Writing Strategies to Explain and Detect Health Misinformation [15.748429583896232]
  This research focuses on aiding the automatic identification of misinformation by analyzing the persuasive strategies employed in textual documents. We introduce a novel annotation scheme encompassing common persuasive writing tactics to achieve our objective. We provide a dataset on health misinformation, thoroughly annotated by experts utilizing our proposed scheme.
  arXiv  Detail & Related papers  (2022-11-11T03:26:37Z)
• Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion [52.49981085431061]
  Enhancing people's ability to write persuasive arguments could contribute to the effectiveness and civility in online communication. We derived four design goals for a tool that helps users improve the persuasiveness of arguments in online discussions. Persua is an interactive visual system that provides example-based guidance on persuasive strategies to enhance the persuasiveness of arguments.
  arXiv  Detail & Related papers  (2022-04-16T08:07:53Z)
• RESPER: Computationally Modelling Resisting Strategies in Persuasive Conversations [0.7505101297221454]
  We propose a generalised framework for identifying resisting strategies in persuasive conversations. Our experiments reveal the asymmetry of power roles in non-collaborative goal-directed conversations. We also investigate the role of different resisting strategies on the conversation outcome.
  arXiv  Detail & Related papers  (2021-01-26T03:44:17Z)
• Examining the Ordering of Rhetorical Strategies in Persuasive Requests [58.63432866432461]
  We use a Variational Autoencoder model to disentangle content and rhetorical strategies in textual requests from a large-scale loan request corpus. We find that specific (orderings of) strategies interact uniquely with a request's content to impact success rate, and thus the persuasiveness of a request.
  arXiv  Detail & Related papers  (2020-10-09T15:10:44Z)
• Learning to Infer User Hidden States for Online Sequential Advertising [52.169666997331724]
  We propose our Deep Intents Sequential Advertising (DISA) method to address these issues. The key part of interpretability is to understand a consumer's purchase intent which is, however, unobservable (called hidden states)
  arXiv  Detail & Related papers  (2020-09-03T05:12:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.