Transparent Peer Review By Scholar9
Using Artificial Intelligence to Understand Consumer Behaviour on Social Media: Opportunities, Challenges and Ethical Considerations
Abstract
Social media is a blessing as well as curse for advertising agencies or marketers who want to understand consumer behaviour. Businesses need to manage the huge data generated by these platforms to get insights on consumer preferences and actions. But manually working on large data can lead to errors and time consuming process. To understand consumer behaviour this research paper is focused on using (AI) Artificial Intelligence to turn social media data into an analytical tool. Algorithms using (AI) Artificial Intelligence can process huge information and spot patterns and trends that human researchers may miss. Moreover this research paper provides solutions and solves any potential ethical issues using AI to analyse consumer behaviour on social media. This paper also highlights how important it is to apply AI technology to understand social media users. By doing so businesses/agencies can create more effective advertising campaigns and increase customer satisfaction.
Shreyas Mahimkar Reviewer
17 Sep 2024 04:01 PM
Not Approved
Relevance and Originality
The Research Article addresses a pressing issue for modern advertising agencies and marketers by focusing on how Artificial Intelligence (AI) can be utilized to analyze consumer behavior through social media data. The application of AI in this context is both relevant and original, as it leverages advanced technology to handle large datasets that are otherwise challenging to manage manually. The paper’s focus on AI’s role in extracting actionable insights from social media data is pertinent to current trends in marketing analytics.
Methodology
The Research Article explores the use of AI algorithms to process and analyze social media data. While the general approach is well-founded, the paper would benefit from a more detailed explanation of the specific AI algorithms employed and the methodology for analyzing data. Information on how these algorithms are implemented, including any data preprocessing steps, evaluation metrics, and validation techniques, would provide a clearer understanding of the methodology.
Validity & Reliability
The validity and reliability of the Research Article could be strengthened by providing more information on how the AI models are validated and how reliable the insights generated are. The paper should include details on the accuracy and robustness of the AI algorithms used, as well as any potential biases in the data or the models. Addressing these aspects would help in assessing the credibility of the findings.
Clarity and Structure
The Research Article is clear in its intent to demonstrate the benefits of AI in analyzing social media data for consumer behavior insights. However, the paper could improve in structure by clearly delineating sections on methodology, results, and ethical considerations. A well-organized structure would enhance readability and help readers follow the flow of information more easily.
Result Analysis
The Research Article discusses the potential of AI to uncover patterns and trends in social media data but lacks detailed result analysis. It would be useful to include specific examples or case studies demonstrating the effectiveness of AI in generating insights. Additionally, presenting quantitative results or metrics on how AI-driven insights compare to traditional methods would provide a more comprehensive analysis of the outcomes.
IJ Publication Publisher
Ok Sir
Shreyas Mahimkar Reviewer