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Journal of Computational Social Dynamics

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Published

2019-12-01

Issue

Vol. 4 No. 4 (2019): Journal of Computational Social Dynamics-2019-4th-Q

Section

Articles

How to Cite

Shah, A., & Nasnodkar, S. (2019). A Framework for Micro-Influencer Selection in Pet Product Marketing Using Social Media Performance Metrics and Natural Language Processing. Journal of Computational Social Dynamics, 4(4), 1–16. Retrieved from https://vectoral.org/index.php/JCSD/article/view/24

A Framework for Micro-Influencer Selection in Pet Product Marketing Using Social Media Performance Metrics and Natural Language Processing

Akshay Shah

iWeb Technology Solutions

https://orcid.org/0009-0009-3769-1830

Siddhesh Nasnodkar

iWeb Technology Solutions

https://orcid.org/0009-0007-3464-1470

Keywords: Micro-Influencer Selection, Pet Product Advertising, NLP, Sentiment Analysis, Social Media Performance Metric

Abstract

We propose an automated quantifiable method for micro-influencer selection in the niche market of pet product advertising. A designated set of micro-influencers was identified and used as the case study. Using igramscrapper, a Python API, key performance metrics—Followers Count, Engagement Rate, and Average Likes—were collected. The data underwent deduplication and normalization to a 0-1 scale to eliminate scale-induced biases. Weights were assigned to each metric according to their importance in marketing objectives: Followers Count (0.4), Engagement Rate (0.4), and Average Likes (0.2). A composite score was then calculated for each micro-influencer based on these weighted, normalized metrics. Additionally, an NLP-based Sentiment Score was generated from user comments. The study found a strong correlation between the composite score and Sentiment Score, thereby suggesting that the composite score could be used as a predictor of sentiment towards the micro-influencers. This implies that it is possible to predict public sentiment using the composite score, thereby adding another layer of data-driven decision-making capability to the system. We argued that understanding sentiment is crucial for micro-influencer selection in product advertising because it provides insights into how well the target audience is likely to receive the influencer's endorsements, thereby affecting the overall success of the advertising campaign.

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Submission Guidelines for the Journal of Computational Social Dynamics General Guidelines:

  1. Article Types: We accept a variety of article types including Original Research Articles, Review Papers, Short Reports, and Opinion Pieces.

  2. Language: Manuscripts must be written in English, and should be clear, concise, and free of jargon.

  3. Length: There is no strict word limit, but Original Research Articles should generally be between 4,000 and 10,000 words, including references.

  4. Formatting: Manuscripts should be submitted as a single Word or LaTeX document, formatted in double-spaced 12-point font.

  5. Abstract: An abstract of 250-300 words is required for all submissions, summarizing the key objectives, methods, findings, and implications of the research.

Manuscript Structure:

  • Title Page: Must include the title, author names, affiliations, and contact information for the corresponding author.

  • Introduction: Provide background, state the problem, and outline objectives.

  • Methods: Detail the methods and tools used in your research.

  • Results: Present the findings of your study.

  • Discussion: Interpret results, discuss their impact, and suggest future research directions.

  • Conclusion: Summarize the main points of the paper.

  • References: Citations should be formatted according to the APA/IEEE styles.

Ethical Guidelines:

Authors must ensure that their research adheres to ethical standards and that informed consent has been obtained for any human or animal subjects involved.

Plagiarism:

The Journal of Computational Social Dynamics uses plagiarism detection software. Any manuscript found to include plagiarized content will be rejected.

Peer Review Process:

All submissions undergo a double-blind peer review process. Authors can expect initial feedback within six to eight weeks.

Submission Process:
  1. Prepare your manuscript according to the guidelines.
  2. Submit your manuscript through our online portal at.
  3. After submission, you will receive a confirmation email with a manuscript ID for tracking purposes.
Revisions:

If revisions are requested, authors must resubmit the revised manuscript within the specified timeframe.

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The journal has a nominal publication fee, waived for authors who lack funding. Details are available on our website.

For any questions or concerns, please contact the editorial office at editorial@vectoral.org. Thank you for considering the Journal of Computational Social Dynamics as a venue for your research.

Published by Vectoral Publishing, the Journal of Computational Social Dynamics maintains high standards in peer-review and scientific inquiry. Authors who wish to submit manuscripts should adhere to the guidelines detailed on our website, www.vectoral.org/jcsd. Vectoral Publishing does not bear any responsibility for the accuracy of information or for any outcomes related to the use of the research published. For editorial correspondence and submissions, please reach out to editorial@vectoral.org.