objective summaries feb 17

Artificial Intelligence in Social Media and its role in Digital Marketing

Venkatanaresh Tadoju

Department of Computer Science, Monroe College, King Graduate School

KG604: Graduate Research & Critical Analysis

Dr. Donna Tennyson

2/11/2023

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Objective Summary

Introduction

Capatina et al. (2020) joined hands to perform research on the way modern technology affects how businesses use marketing on social media platforms. The researchers performed the study to determine whether the future capabilities of AI in social media match the expectations of stakeholder owners and users. The research was conducted on the owners and employees of digital agencies in the year 2020 in Romania, Italy, and France. The researchers use different approaches, starting with a focus group followed by an online survey. The paper proposes a casual model to discover AI software's capabilities to match the needs of potential users. The paper aims to identify variables that explain how well respondents are knowledgeable about SMM. Additionally, Capatina et al. (2020) set out to find which of the four capabilities the users are likely to consider for a test. The researchers used the research to explain how different variables affect the likelihood of users to engage modern technology when it comes to social media marketing. Comment by Donna Tennyson: Who (OK) Comment by Donna Tennyson: Why (OK) Comment by Donna Tennyson: How (OK)

Summary of the findings

The paper is subdivided into a total of four sections which are the introduction, theoretical background, methodology, and findings. The research uses 150 owners and marketers in three countries to find the value of AI technology in SMM. SMM relies on various customer data like purchases, sales, and behavior to recommend the best products for customers. Marketers can also consider key data like images and sentiments as they contain information that is likely to go unnoticed. The focus group of digital marketing professionals helps build on the knowledge and awareness of AI. Capatina et al. (2020) completed the research with an online questionnaire with three experts in each of the three nations. According to the study, it is conceivable in Romania to pinpoint consumption locations and times and link sales to a brand's social media usage frequency. Comment by Donna Tennyson: What (OK)

Conclusion

The researcher also presented findings for the two remaining countries, France and Italy. In France, conversely, users' interest in responding to new products on social media is the main element that motivate them to engage in social media marketing testing using the proposed software. The software's capacity to categorize content generated from user activity impacted consumer interest in the new program. Finally, the capacity to classify social media postings based on where they are in the customer purchasing cycle and the capacity to choose the material for use regularly. Thus, each country had specific factors affecting the participation of users. Comment by Donna Tennyson: What (OK) Move the findings to the same section of the paper.

Reference

Capatina, A., Kachour, M., Lichy, J., Micu, A., Micu, A. E., & Codignola, F. (2020). Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users’ expectations.  Technological Forecasting and Social Change,  151, 119794. https://do